Agryo is the global risk intelligence provider that enables financial institutions to assess and manage financial risks in the crop field level for underwriting agriculture insurance, loans, and trade finance globally; as well as meet sustainability goals

Agryo

agryo

Table of Contents Agrotech: What is Agrotech? History of Agrotech Recent Developments in Agrotech How Agrotech makes Agriculture easier for workers Agrotech in 2021 and Beyond: The Future What is Agrotech? Agricultural technology or agrotech is the use of modern technology to improve yield in farming, horticulture, aquaculture, and animal husbandry. Agrotech aims to increase food production and make agriculture easier for farmworkers. Using sophisticated equipment for otherwise time-consuming tasks has helped increase productivity and reduce time wastage in the agricultural industry. For instance, if a farmer chooses to use a tractor and plows for tilling a piece of land, the tilling job will take less time than if human workers were employed to till that same plot of land. Similar technologies are employed from the production stage of agricultural products until the harvest stage to reduce the workload on farmworkers and ensure that agricultural products get to the consumers right on time. History of Agrotech Agricultural technology is not new to humans: the first group of humans survived by farming and hunting animals. They the knife, hoe, and scythe. developed tools such as Then, a large percentage of the population was involved in agriculture because of the high demand for food and the low yield that farming with small tools provided. In the mid 18th century, new developments in technology allowed farmers to work on larger plots of land and harvest more crops. This eliminated the need for a large number of farmworkers and reduced the uncertainty associated with agriculture. The helped bring about the Industrial revolution by reducing the number of farmworkers: more workers were available for employment in the industries. Agricultural Revolution The 1890s saw the , which we all know today as the tractor. It ran on gasoline and could move forward and backward. Iowan John Froelich improved his tractors for the next 20 years and formed a company that later sold out to John Deere Manufacturing. development of Iowan John Froelich's traction motor Much later, developments such as genetically modified plants, hybrid plants, herbicides, and fertilizers took the world of agriculture by storm. Agricultural technology has evolved over the years: who knows what next is to come? Recent Developments : The GIS software offers a precision-based method of monitoring fields, plant health, weather conditions, crop yield, etc. GPS , on the other hand, helps farmers with smart machinery to optimize fertilizer and herbicide application, thus saving resources and time. 1. GIS and GPS Software software Genetically modified crops are being developed to meet the food demand of the world's growing population. These genetically modified are designed to have a different growth pattern than the original product or develop disease resistance. 2. Genetic Engineering: crops : Drones help farmers monitor the hard-to-reach areas of their farms, access the fertility of crops, apply fertilizers and pesticides, and successfully plan irrigation systems. can even be used to measure the extent of soil damage: for instance, in case of a flood. 3. Drones Drones : AI is used to optimize data in real-time: from weather conditions to temperature and soil conditions. It provides a system in which farmers can monitor crop development and yield. In addition, AI agriculture help in carrying out some tasks that would have required human labor. 4. Artificial Intelligence bots : , a decision-making tool, helps farmers monitor fish movement during feeding. This helps farmers understand fish appetite and provide better meals for the fish, resulting in improved growth and fish survival. Indirectly, more fish are produced to meet the protein demand of human consumers. 5. Digital Feeding Cage Eye How AgroTech Makes Agriculture Easier For Workers Agrotech is a blessing to the field of agriculture: it reduces work hours and improves productivity. Many years before agricultural technology developed, farmers had to work up to six out of seven days a week in the rain and sun to ensure that the harvest was good. If they didn't have that capacity, they had to employ and pay more workers. Agrotech removes that burden from the farmer, and it reduces the wastage of resources. Using GPS and GIS software helps the farmer spray pesticides and fertilizer onto the problem areas rather than spraying the whole farm. The use of genetically improved crops improves yield and reduces the number of crops destroyed by plant diseases. All of these factors increase profit after these crops are sold and indirectly increase the farmworker's income while reducing their work hours. Agriculture Technology in 2021 and Beyond: The Future In the years that have passed, agricultural technology has taken a different turn. The GIS and GPS technology, IoT Technology, Blockchain, Automation, and Genetically Improved Crops are gifts these years have given to agricultural technology. These developments have reduced work hours, created more jobs, increased yield, and provided food for us all. In the years to come, there will be much greater technological developments in the field of agriculture. Amid all these developments, consumer health and employment statistics should be taken into consideration. The future is uncertain: years from now, we could have farms completely run by robots.

Agrotech: Making Agriculture Easier for Workers

Welcome to HackerNoon’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. 1. What is your company in 2–5 words? Digital product agency disrupting healthcare. 2. Why is now the time for your company to exist? There is no denying that the pace of innovation and technology has accelerated in the last decade. However, the healthcare industry has not evolved as quickly as other industries. It faces unique challenges, like a lack of agility, strict regulations, antiquated processes, and slow innovation. Although there are many people in the sector working to improve quality and accessibility, systemic problems and financial interests limit what can be achieved. Our strategy is to bring agility to this setting by using our knowledge of technology, user-centric approach, and in-depth knowledge of the business to create software that is strategically planned, scalable, and cleverly constructed. 3. What do you love about your team, and why are you the ones to solve this problem? When we first set out, we were quite excited about developing digital solutions that prioritized the needs and wants of users and delivered genuine value. By then, we collaborated with businesses in every sector of the economy, including real estate, retail, food, entertainment, agronomy, retail, and finance. Even though we've produced incredible products and gained a lot of knowledge from the process, we believed that focus and mission were still lacking. In 2020, during the pandemic, we made a strategic shift and decided to focus 100% on healthcare, allowing us to fully immerse ourselves in the industry, gain specialized knowledge, and, most importantly, have a shared, meaningful purpose. This change gave our entire team a compelling mission and a defined path. Who wouldn't find satisfaction in working on initiatives for a sector of the economy that ultimately saves lives? I guess that’s what I love most about the team and why we are the ones who solve problems. We’re a team of focused, knowledgeable, and creative people with a shared purpose: improving healthcare. 4. If you weren’t building your startup, what would you be doing? I would probably be building another startup. I’ve been an entrepreneur since I was a teenager, so I’m sure that if Light-it had not succeeded, I would be building something else. 5. At the moment, how do you measure success? What are your metrics? We work with OKRs (Objectives and Key Results), and they are measured quarterly. We have company-wide OKRs and OKRs per department. They help us stay aligned with the same goals quarter to quarter. 6. In a few sentences, what do you offer to whom? In broad terms, we partner with our clients to help them ideate, design, and develop healthcare digital products. The challenge we resolve is the lack of expertise in developing healthcare software with a product mindset and keeping strategy, budget, compliance, and user experience in mind.  There are hundreds of software development firms with no experience in healthcare, which can lead to short-term gains at the expense of long-term scalability and maintenance. We at Light-itadopt a unique strategy. We follow industry best practices, implementing scalable models across several platforms and providing end-to-end product development services with extensive user experience support and consulting. Since we have an agile approach, startups are our bread and butter. Nevertheless, our interactions with health systems have also been excellent. Our introduction of an agile vision and innovative mindset has been extremely effective in these circumstances, given their customary bureaucratic and slower ways. Finding a reliable partner is usually difficult for a healthcare organization, but finding someone who can offer both high-tech development and strategic advice is much more difficult. That's what makes us unique. 7. What’s most exciting about your traction to date? **Light-it'**s traction has been steadily growing year after year, an incredibly encouraging trend. Last year was particularly exciting for us as we forged partnerships with industry giants like ABInBev Foundation, the world's largest beer company, and Inviza, a groundbreaking RPM and DTX product for the US Air Force.  These collaborations are not only about business and transactions – they validate our position as leaders in our field and serve as a powerful encouragement to continue our hard work. 8. Where do you think your growth will be next year? We have been collaborating with startups, supporting them through the entire product development process, from launch to scaling. Now that we are collaborating with Health Systems, we plan to continue doing so because we have seen such a positive impact. We don't intend to expand the company too quickly because, as a team, we want to keep our boutique approach. We aim to keep our crew size between one hundred and two hundred. We always have new projects coming up. In my opinion, one of the biggest promises in health technology is generative AI. Puppeteeris a spinoff company we launched last year, and it is the result of the realization that 2024 was going to be the year of generative AI and that humanity will either have to accept it or perish. Our first round is presently being raised, and we have high hopes for it this year. Regarding our long-term future, Light-it's DNA will always embrace new technologies and pathways, so who knows what else might emerge! "You win, or you learn" strikes a chord with me. Every new endeavor, whether it succeeds or fails, adds to our development and resiliency. I'm committed to establishing a positive work environment that prioritizes curiosity, boldness, ownership, and dedication to ongoing development while also considering the well-being of our team. 9. Tell us about your first paying customer and revenue expectations over the next year. The first paying customers we had were family members and friends building e-commerces. Since then, we’ve worked with startups from pre-seed to Series D, with Fortune 500s and some of the biggest health systems in the world! In terms of revenue, we expect to keep growing at the rate of 50% per year. 10. What’s your biggest threat? We have all heard that AI will replace software engineers, so I guess that should be my biggest thread as a software development company owner. Still, I’m convinced that our team has minds that no AI can substitute: Empathy, strategy, and creativity are some of the skills needed in a product team that AI can't substitute. Would you like to take a stab at answering some of these questions? The link for the template is HERE. Welcome to HackerNoon’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. Welcome to HackerNoon ’s Writing Prompts! Would you like to take a stab at answering some of these questions? The link for the template is HERE. HackerNoon The link for the template is HERE. 1. What is your company in 2–5 words? Digital product agency disrupting healthcare. 2. Why is now the time for your company to exist? There is no denying that the pace of innovation and technology has accelerated in the last decade. However, the healthcare industry has not evolved as quickly as other industries. It faces unique challenges, like a lack of agility, strict regulations, antiquated processes, and slow innovation. Although there are many people in the sector working to improve quality and accessibility, systemic problems and financial interests limit what can be achieved. Our strategy is to bring agility to this setting by using our knowledge of technology, user-centric approach, and in-depth knowledge of the business to create software that is strategically planned, scalable, and cleverly constructed. 3. What do you love about your team, and why are you the ones to solve this problem? When we first set out, we were quite excited about developing digital solutions that prioritized the needs and wants of users and delivered genuine value. By then, we collaborated with businesses in every sector of the economy, including real estate, retail, food, entertainment, agronomy, retail, and finance. Even though we've produced incredible products and gained a lot of knowledge from the process, we believed that focus and mission were still lacking. In 2020, during the pandemic, we made a strategic shift and decided to focus 100% on healthcare, allowing us to fully immerse ourselves in the industry, gain specialized knowledge, and, most importantly, have a shared, meaningful purpose. This change gave our entire team a compelling mission and a defined path. Who wouldn't find satisfaction in working on initiatives for a sector of the economy that ultimately saves lives? I guess that’s what I love most about the team and why we are the ones who solve problems. We’re a team of focused, knowledgeable, and creative people with a shared purpose: improving healthcare. 4. If you weren’t building your startup, what would you be doing? I would probably be building another startup. I’ve been an entrepreneur since I was a teenager, so I’m sure that if Light-it had not succeeded, I would be building something else. Light-it Light-it 5. At the moment, how do you measure success? What are your metrics? We work with OKRs (Objectives and Key Results), and they are measured quarterly. We have company-wide OKRs and OKRs per department. They help us stay aligned with the same goals quarter to quarter. 6. In a few sentences, what do you offer to whom? In broad terms, we partner with our clients to help them ideate, design, and develop healthcare digital products. The challenge we resolve is the lack of expertise in developing healthcare software with a product mindset and keeping strategy, budget, compliance, and user experience in mind.  There are hundreds of software development firms with no experience in healthcare, which can lead to short-term gains at the expense of long-term scalability and maintenance. We at Light-it adopt a unique strategy. We follow industry best practices, implementing scalable models across several platforms and providing end-to-end product development services with extensive user experience support and consulting. Light-it Since we have an agile approach, startups are our bread and butter. Nevertheless, our interactions with health systems have also been excellent. Our introduction of an agile vision and innovative mindset has been extremely effective in these circumstances, given their customary bureaucratic and slower ways. Finding a reliable partner is usually difficult for a healthcare organization, but finding someone who can offer both high-tech development and strategic advice is much more difficult. That's what makes us unique. 7. What’s most exciting about your traction to date? **Light-it'**s traction has been steadily growing year after year, an incredibly encouraging trend. Last year was particularly exciting for us as we forged partnerships with industry giants like ABInBev Foundation, the world's largest beer company, and Inviza, a groundbreaking RPM and DTX product for the US Air Force.  These collaborations are not only about business and transactions – they validate our position as leaders in our field and serve as a powerful encouragement to continue our hard work. 8. Where do you think your growth will be next year? We have been collaborating with startups, supporting them through the entire product development process, from launch to scaling. Now that we are collaborating with Health Systems, we plan to continue doing so because we have seen such a positive impact. We don't intend to expand the company too quickly because, as a team, we want to keep our boutique approach. We aim to keep our crew size between one hundred and two hundred. We always have new projects coming up. In my opinion, one of the biggest promises in health technology is generative AI. Puppeteer is a spinoff company we launched last year, and it is the result of the realization that 2024 was going to be the year of generative AI and that humanity will either have to accept it or perish. Our first round is presently being raised, and we have high hopes for it this year. Puppeteer Regarding our long-term future, Light-it's DNA will always embrace new technologies and pathways, so who knows what else might emerge! "You win, or you learn" strikes a chord with me. Every new endeavor, whether it succeeds or fails, adds to our development and resiliency. I'm committed to establishing a positive work environment that prioritizes curiosity, boldness, ownership, and dedication to ongoing development while also considering the well-being of our team. 9. Tell us about your first paying customer and revenue expectations over the next year. The first paying customers we had were family members and friends building e-commerces. Since then, we’ve worked with startups from pre-seed to Series D, with Fortune 500s and some of the biggest health systems in the world! In terms of revenue, we expect to keep growing at the rate of 50% per year. 10. What’s your biggest threat? We have all heard that AI will replace software engineers, so I guess that should be my biggest thread as a software development company owner. Still, I’m convinced that our team has minds that no AI can substitute: Empathy, strategy, and creativity are some of the skills needed in a product team that AI can't substitute. Would you like to take a stab at answering some of these questions? The link for the template is HERE. Would you like to take a stab at answering some of these questions? The link for the template is HERE. The link for the template is HERE.

Light-it: Empowering Healthcare through Purpose-Driven Digital Solutions

The transaction that first gave Bitcoin any sort of monetary value happened in October 2009 when a Finnish computer science student Martti Malmi (‘Sirius’) sold 5,050 coins for $5.02, meaning each Bitcoin was worth $0.0009. In today’s terms, if he had held on to his coins, he’d be (circa) NZ$555,500,000 richer. Today, we all know “someone who knows someone” who invested around that time and has become a multimillionaire; and we’re kicking ourselves for not doing the exact same thing… With the fourth Bitcoin halving firmly in our rearview mirror and some very recent all-time highs for Bitcoin, new investors (or even existing ones wanting to build or increase their crypto portfolio) might be asking if they’ve waited too long to invest… On the other hand, those who have HODLd - or ‘held on for dear life’ - for a while might be fretting about the lack of an immediate, dramatic change in price over the past weekend. An Immediate Ascent Is Always Unlikely… In the past, halvings have been followed by periods of increased demand and price surges due to the dynamics of supply-demand - but this is never immediate and market dynamics, sentiment, and regulatory factors all influence Bitcoin's price trajectory, making a straight-line ‘ascent’ unlikely. While analysts anticipate an upward trend (which has been the case historically post-halving), the reality is nuanced, and these events are often followed by periods of consolidation and correction - including rallies, reactions, and a lot of volatility on (hopefully) the way up. TLDR: If you were expecting prices to skyrocket overnight, you should have been reading my blogs sooner to get those expectations in check! The Danger of Letting Disappointment Drive Decision-Making Some analysts predicted that the halving would trigger an immediate price slump that would lead to widespread ‘panic selling’; but this hasn’t yet happened... Prices have currently remained buoyant (increasing by 9%); and as a result, investor morale remained buoyant. There was no immediate sell-off… But things often change very quickly in crypto, and this is when underwhelming can lead to panic as pricing drops. In particular, ‘newbies’ who have recently invested in Bitcoin ETFs might not be used to the asset class’s volatility and when pullbacks occur, they could decide that they prefer a move back to more traditional (and more predictable) vehicles. These ‘knee-jerk’ reactions could still lead to a ‘sell-off’, despite looking at only a ‘moment in time’ being a dangerous way of making investment decisions. TLDR: We might not have seen an immediate slump, but this doesn’t mean we shouldn’t be pre-prepared for one with a sound investment strategy to boot. Taking a Broader View on Volatility… The recent halving of Bitcoin block rewards is foundational to Bitcoin’s well-known four-year cycle. This cycle has been historically closely linked to price, with the cycle progressing through ‘Bull’ (rising prices), ‘Bear’ (falling prices), ‘Accumulation’ (a leveling out of prices), and ‘Expansion’ (steady growth). Understanding this cycle is foundational to an ability to take a much broader view of volatility. In terms of ‘what’s next’, we can expect a lot of analysis around any retracements (minor pullbacks or changes in the direction of a financial instrument in terms of price). These retracements are often temporary in nature and do not necessarily indicate a shift in the larger trend. TLDR: In analyzing your next investment move, it’s important to understand what point we are at in the asset cycle. Playing the ‘Long Game’ Seasoned investors all tell us that playing the ‘long game’ is often far wiser than making knee-jerk decisions. As the saying goes, time in the market beats timing the market. Given the crypto market’s volatility, strategies you can employ include: Dollar cost averaging (DCA): Regularly invest fixed amounts regardless of market conditions to average out costs and reduce risk. The hold-on-for-dear-life (HODL) strategy: Hold onto assets long-term despite market fluctuations, focusing on fundamentals rather than short-term movements. Diversification: Spread investments across different assets (such as types of coins) to minimise risk from volatile market swings. ** Too many investors don’t ‘Keep calm and invest on’, getting caught up in ‘timing the market’ in terms of entry or running aground when the market becomes more volatile. An ability to confidently navigate volatility is key to avoiding being a ‘Sirius’ and will help you have the confidence to invest, HODL, and sell successfully. **Disclaimer: Crypto is volatile, carries risk, and the value can go up and down. Past performance is not an indicator of future returns. Please do your own research. The transaction that first gave Bitcoin any sort of monetary value happened in October 2009 when a Finnish computer science student Martti Malmi (‘Sirius’) sold 5,050 coins for $5.02, meaning each Bitcoin was worth $0.0009. In today’s terms, if he had held on to his coins, he’d be (circa) NZ$555,500,000 richer. Today, we all know “someone who knows someone” who invested around that time and has become a multimillionaire; and we’re kicking ourselves for not doing the exact same thing… The transaction that first gave Bitcoin any sort of monetary value happened in October 2009 when a Finnish computer science student Martti Malmi (‘Sirius’) sold 5,050 coins for $5.02, meaning each Bitcoin was worth $0.0009. In today’s terms, if he had held on to his coins, he’d be (circa) NZ$555,500,000 richer. Today, we all know “someone who knows someone” who invested around that time and has become a multimillionaire; and we’re kicking ourselves for not doing the exact same thing… With the fourth Bitcoin halving firmly in our rearview mirror and some very recent all-time highs for Bitcoin, new investors (or even existing ones wanting to build or increase their crypto portfolio) might be asking if they’ve waited too long to invest… halving On the other hand, those who have HODLd - or ‘held on for dear life’ - for a while might be fretting about the lack of an immediate, dramatic change in price over the past weekend. An Immediate Ascent Is Always Unlikely… An Immediate Ascent Is Always Unlikely… In the past, halvings have been followed by periods of increased demand and price surges due to the dynamics of supply-demand - but this is never immediate and market dynamics, sentiment, and regulatory factors all influence Bitcoin's price trajectory, making a straight-line ‘ascent’ unlikely. While analysts anticipate an upward trend (which has been the case historically post-halving), the reality is nuanced, and these events are often followed by periods of consolidation and correction - including rallies, reactions, and a lot of volatility on (hopefully) the way up. TLDR: If you were expecting prices to skyrocket overnight, you should have been reading my blogs sooner to get those expectations in check! TLDR: If you were expecting prices to skyrocket overnight, you should have been reading my blogs sooner to get those expectations in check! The Danger of Letting Disappointment Drive Decision-Making The Danger of Letting Disappointment Drive Decision-Making Some analysts predicted that the halving would trigger an immediate price slump that would lead to widespread ‘panic selling’; but this hasn’t yet happened... Prices have currently remained buoyant (increasing by 9%); and as a result, investor morale remained buoyant. There was no immediate sell-off… But things often change very quickly in crypto, and this is when underwhelming can lead to panic as pricing drops. In particular, ‘newbies’ who have recently invested in Bitcoin ETFs might not be used to the asset class’s volatility and when pullbacks occur, they could decide that they prefer a move back to more traditional (and more predictable) vehicles. These ‘knee-jerk’ reactions could still lead to a ‘sell-off’, despite looking at only a ‘moment in time’ being a dangerous way of making investment decisions. TLDR: We might not have seen an immediate slump, but this doesn’t mean we shouldn’t be pre-prepared for one with a sound investment strategy to boot. TLDR: We might not have seen an immediate slump, but this doesn’t mean we shouldn’t be pre-prepared for one with a sound investment strategy to boot. Taking a Broader View on Volatility… Taking a Broader View on Volatility… The recent halving of Bitcoin block rewards is foundational to Bitcoin’s well-known four-year cycle. This cycle has been historically closely linked to price, with the cycle progressing through ‘Bull’ (rising prices), ‘Bear’ (falling prices), ‘Accumulation’ (a leveling out of prices), and ‘Expansion’ (steady growth). Understanding this cycle is foundational to an ability to take a much broader view of volatility. In terms of ‘what’s next’, we can expect a lot of analysis around any retracements (minor pullbacks or changes in the direction of a financial instrument in terms of price). These retracements are often temporary in nature and do not necessarily indicate a shift in the larger trend. TLDR: In analyzing your next investment move, it’s important to understand what point we are at in the asset cycle. TLDR: In analyzing your next investment move, it’s important to understand what point we are at in the asset cycle. Playing the ‘Long Game’ Playing the ‘Long Game’ Seasoned investors all tell us that playing the ‘long game’ is often far wiser than making knee-jerk decisions. As the saying goes, time in the market beats timing the market. Given the crypto market’s volatility, strategies you can employ include: Dollar cost averaging (DCA): Regularly invest fixed amounts regardless of market conditions to average out costs and reduce risk. Dollar cost averaging (DCA): Regularly invest fixed amounts regardless of market conditions to average out costs and reduce risk. The hold-on-for-dear-life (HODL) strategy: Hold onto assets long-term despite market fluctuations, focusing on fundamentals rather than short-term movements. The hold-on-for-dear-life (HODL) strategy: Hold onto assets long-term despite market fluctuations, focusing on fundamentals rather than short-term movements. Diversification: Spread investments across different assets (such as types of coins) to minimise risk from volatile market swings. ** Diversification: Spread investments across different assets (such as types of coins) to minimise risk from volatile market swings. * * Too many investors don’t ‘Keep calm and invest on’, getting caught up in ‘timing the market’ in terms of entry or running aground when the market becomes more volatile. An ability to confidently navigate volatility is key to avoiding being a ‘Sirius’ and will help you have the confidence to invest, HODL, and sell successfully. ** Disclaimer: Crypto is volatile, carries risk, and the value can go up and down. Past performance is not an indicator of future returns. Please do your own research. Disclaimer: Crypto is volatile, carries risk, and the value can go up and down. Past performance is not an indicator of future returns. Please do your own research.

Making Cents (Sense!) of Post-Halving Pricing…

As we head towards mid-April, the investment world is abuzz with speculation and hype around the upcoming ‘Bitcoin halving.’ But what is a Bitcoin halving, and why is it so significant in terms of price? More pointedly, should we place our faith in predictions about the current Bitcoin halving, leading to a bull run? And if prices do inflate, will they stay there? TLDR: If the ‘Bitcoin halving’ and the crypto market has a relationship status, it would probably be: ‘It’s complicated…’! Quick recap - what is a Bitcoin halving event? Bitcoin operates using a technology known as blockchain (a secure digital ledger) that records transactions across a network of decentralized computers spread around the globe, ensuring transparency and immutability. Unlike traditional currencies, where new money can be printed by central banks and governments, the supply of Bitcoin is limited, and there will only ever be 21 million Bitcoins in existence, making it a deflationary digital currency. To understand the halving, let’s do a quick overview of a few key terms: A block is simply a batch of transactions - i.e., payments between people - that are bundled together and added to the list of previous blocks, making a blockchain! A blockchain miner is a participant in the network who uses computational power to validate and add these blocks (batches of transactions) to the blockchain. A block reward is the amount of new Bitcoin given to a blockchain miner for adding a new block to the chain. A Bitcoin halving is an in-built, pre-programmed event that takes place every 210,000 blocks or roughly every four years. During a halving event, the block reward is cut in half. Currently, mining a new block gets you a reward of 6.25 Bitcoin, and after halving, the reward drops to 3.125 Bitcoin. As more people adopt Bitcoin and demand rises, the halving ensures that supply growth slows down, creating an environment reminiscent of precious metals like gold. A halving event’s influence on price A fixed supply of 21 million Bitcoins means that, over time, these become increasingly scarce. Based on past experience, it is believed that the halving will have a profound economic impact on Bitcoin's ecosystem. With the reduction in block rewards, the flow of newly mined Bitcoins decreases, leading to a decrease in selling pressure from miners. In the past, halvings have been followed by periods of increased demand and price surges due to the dynamics of supply and demand. It is this history of post-halving price increases that has fueled the excitement and anticipation surrounding each event. It’s not that simple… However, while some analysts anticipate an upward trend (which has been the case historically post-halving), the reality is much more nuanced. These events spark widespread excitement but have also been followed by periods of consolidation and correction. Market dynamics, sentiment, and regulatory factors all influence Bitcoin's price trajectory, making a straight-line ‘ascent’ unlikely. Understanding the broader context The halving of Bitcoin block rewards is foundational to Bitcoin’s well-known four-year cycle, which is often referred to as the ‘halving cycle’. This cycle has been historically closely linked to price, with the cycle progressing through ‘Bull’ (rising prices); ‘Bear’ (falling prices); ‘Accumulation’ (a levelling out of prices) and ‘Expansion’ (steady growth). Importantly, it’s rarely smooth sailing within each of these phases, and there might be rallies, reactions, and a lot of volatility on (hopefully) the way up. ( depicting Bitcoin’s entire price history.) Chart Many analysts have also raised the possibility of a ‘Super Cycle’ off the back of the recently. These have led to an injection of investment in the industry over the last 3-4 months, setting out an unprecedented landscape in terms of all prior cycles. We have had several huge all-time highs (ATHs) hitting the market ahead of this halving and a number of new everyday investors with an interest in crypto as part of their investment portfolio. What this will do to the typical variance in price post-halving is still unknown. Bitcoin ETFs being approved Staying calm Given the crypto market’s volatility, strategies that seasoned investors often employ include: Dollar-cost averaging (DCA): Regularly invest fixed amounts regardless of market conditions to average out costs and reduce risk. The hold-on-for-dear-life (HODL) strategy: Hold onto assets long-term despite market fluctuations, focusing on fundamentals rather than short-term movements. Diversification: Spread investments across different assets (such as types of coins) to minimize risk from volatile market swings. It’s important that Bitcoin investors understand the basic essence of this market cycle, together with Bitcoin's long-term value proposition. This will empower them to ‘stay calm’ and not run aground (such as ‘panic selling’ prematurely) when the market hits rough seas. Only then will they be able to confidently navigate volatility and tap into its potential for the future.

What Everyday Investors Need to Know About a ‘Bitcoin Halving’ 

Humans! One interesting twinkle in the dark, vacuous expanse of the cosmos. Trapped on a floating ball of rock to mope into space and be tormented by relentless, conflicting emotions. Prison within and prison without. Awaiting the summon of death. What the hell is this existence and what is its use? At least we have each other. Right? Yes, we do. Plus, the resources of the earth. And most importantly, there's that small voice that keeps telling us to become more. So, we stagger on. Nothing is certain in this great maze of existence but we don't just give in. We grope for purpose in the confusing unknown. We do what we do in search of fulfillment. Thus, we solve problems for those we love. We really dig in and harvest ingenious creations from within us. It makes us happy, so we keep going. We keep chasing that which our heart yearns for. What is it many have asked? What is it that we really want? Some of the smartest among us have given a name to it, and I dare agree with them. It is what it is; Freedom! Freedom from wants, death, and ourselves. Freedom from whatever dares limit us. Freedom from this great bondage that is us. Hence, in our relentless yearning, we build this great bridge of science. Into matter, into space, into life. Into technology! Oh that we may find that which we seek. Oh that we may find; Autonomy! Autonomy Has Always Driven Technology Humans have always been bound by limitations that we constantly rebel against. Imagine the caveman days. Small, slow, and weak as we were, we were completely bound by the harsh laws of the jungle. Dominated by powerful creatures. Yet, our big brain brought us to the very top of the food chain. Inventions like the spear, knife, and arrow with advanced hunting strategies helped us overcome the powerful beasts that ruled the wild. Then, we created our own societies and were ruled by tribal laws. Not very different jungle laws though but strong humans were in charge now. Then came the reign of religion, and priests were in charge. Then came countries with cunning politicians. Then came capitalism with wealthy businessmen who are now running the show. All these changes have been driven by advancements as humans try to take more control of their lives. From being ruled by wild beasts to strong men to priests to politicians and businessmen, people have always invented systems that gave them more control of their lives. And this progress is not only evident in the technology of our leadership but also in the everyday devices that we use. First, we had caves and stone tools, then came villages and metal tools, and then came towns and analog machines. Now, we have cities and digital technology. This drive for autonomy in our technology has culminated in what we call a decentralized internet or web3. Autonomy in Web3 Web 3 remains a relatively recent technology that is yet to be widely understood. Yet, it is already being widely adopted as the advantages are very obvious. Simply put, web3 aims to put the Internet and financial system under the control of everyone and not just a few giant corporations. Why is this necessary you may ask? Well, the answer is simple: "Power corrupts and absolute power corrupts absolutely!" The internet and financial systems represent the most critical technologies that humans have been able to develop. Hence, there is a great power in the hands of anyone who controls them. It's no wonder that top government officials and tech billionaires dominate the list of most powerful people in the world. This great power which allows such people to exercise control around the world is akin to the legendary absolute power that absolutely corrupts the wielders. And we have already seen this corruption at play. For example; , , , etc. Facebook has recorded multiple user data breaches Twitter has been accused many times of stifling free speech US politicians were caught cheating through insider trading in the stock market Hence, the internet and financial market which have lasting effects on people’s lives need some level of democracy. This is what web3 promises. Cryptocurrencies were introduced as a means for people to transact directly without passing through middlemen in the banking institutions who often benefit fraudulently from people’s money with little or no punishment. Combining crypto with blockchain technology provides the world with a global decentralized financial internet that no one fully controls and everyone can benefit from. Is Autonomy Truly Possible? Many reservations have been raised about the practicality of web3 and whether it can be truly autonomous. For example; fundamental blockchain infrastructures are often hosted on web2 servers with centralized control. Also, mining cryptocurrency is energy intensive which makes the entire system dependent on power companies. Would the power companies and server owners not be the new bosses in town? Well, that's a critical problem that is yet to be solved. However, blockchain technology is slowly solving the centralized server problem through compressed distributed storage of the technology on the devices of its users. Basically, a blockchain is a database, and every device that connects to the blockchain has a version of the database stored on it. This makes it possible for the billions of devices that users use to connect to the blockchain to function as servers distributed around the world instead of just one central server. Fingers crossed for what will come in the future. About the electricity problem, well, most cryptocurrencies have a limited amount of tokens to be mined, hence, mining is not a forever thing. Also, alternative versions of power like solar make it possible for miners to set up affordable sources of personalized power. Hence, centralized power companies can possibly be bypassed. With these considerations, the autonomy that web3 promises can foreseeably be accomplished. Future of Autonomy Picture this... You fall asleep now and awaken in the autonomous age. Robots run the world now. The planet is one big country run by the United Nations and headquartered in Earth City (a giant circular artificial island built in the Atlantic Ocean on longitude 0 degrees and latitude 0 degrees). Networks of underwater hyperloop lines and speed train bridges interconnect all the continents in minutes and the former countries are nothing but political provinces for proper documentation and security. Autonomous vehicles with little or no accidents dominate the roads and autonomous spaceships transverse space to transport people and resources around the solar system. Humans have finally colonized the solar system. The world lives in abundance as automated high-tech farms meet all our agricultural needs. Basic amenities like water, electricity, and education are free, and everyone gets a living wage to cover secondary needs like real estate around the planets, internet access, and transportation. Advanced amenities like technology, art, entertainment, exploration, and financial trading are where businesses operate. Web3 is fully operational. Hologram devices are all over the place for people to experience the dinterverse (decentralized internet metaverse) which uses all those devices as servers. DAOs, running on open-source technology, are the global means of voting, with Auth ID being the prominent open-source platform for decentralized technology. Industry-based crypto coins are the means of exchange (e.g., techon for technology, agrocoin for agriculture, muse for music, etc.) and cryptex trading (forex trading of the time) is the primary means of employment for everyone with people speculating on which industry will do better based on the season. Bitcoin is, however, immortalized as the only currency accepted around the world across all industries. Global poverty has been eradicated and financial inequality is very low around the world with cryptex trading available to everyone. A decentralized financial system was the game changer as it led to an explosion of prosperity through relatively easy cryptex trading. You investigate your trade on your holophone. You're doing very well and will be making another $50,000 this week. You smile to yourself as you glance out the window of your noiseless starjet (silent speed jets that ferry people around the world in minutes). The city below is a great wonder as people said. You're on vacation in Earth City. It's your first time. You came for it. The statue of autonomy or "the human spirit" as it is fondly called. Many weep upon first beholding its glory. The symbol of human victory on the earth. It appears on the horizon. The shiny bust of a crowned androgynous human child stops at the waist so it's neither male nor female. Completely transparent as if entirely made of glass, hence, the name human spirit. With both hands upraised in freedom, it holds Bitcoin (the first global crypto) in the right hand and a scroll in the left. Your ship does the ceremonial circling of the statue. Then it passes the scroll and you behold those legendary words. You read it in a low voice. "We humans hold that all of us are born free. Free to live, free to love, free to prosper!" A smile crawls up your face, and you resolve to uphold this great motto. Then you hear a phone ring. A familiar ancient music. It gets louder and louder. It's your phone. You were dreaming of course. You curse as you pick up your phone. It's your boss calling you to return to work. You cut the call and sigh in disappointment. That dream was just beautiful. Then it occurs to you: The current world is one big nightmare! WHAT DOES THIS MEAN Web3 is upon us. Cryptocurrencies are everywhere and blockchain infrastructure gets more sophisticated every day. Many crypto millionaires roam the earth to prove the real value of the technology. Decentralization is on its way. Below are the predictions you should know about web3; Decentralization is the future. Digital commodities e.g., NFTs, in-game items, virtual real estate, and decentralized exchange (DEX) will create a new industry. Currencies will become more globalized. Companies will become smaller and more personalized. Self-service will become the new way of operating the financial industry. HOW DO I PREPARE FOR AUTONOMY Educate yourself on cryptocurrencies, blockchain technology, and the metaverse. Invest in promising crypto coins. Participate in public web3 forums. Fund web 3 projects if you can. Learn how to make money on your own from the internet.

Behold: The Autonomy We Always Sought

দেখুন: যে স্বায়ত্তশাসন আমরা সবসময় চেয়েছি

Siehe: Die Autonomie, die wir immer gesucht haben

He aquí: la autonomía que siempre buscamos

Voici : l’autonomie que nous avons toujours recherchée

देखिए: वह स्वायत्तता जो हम हमेशा से चाहते थे

見よ、私たちが常に求めていた自律性

보라: 우리가 항상 추구했던 자율성

Eis: a autonomia que sempre buscamos

Вот: автономия, к которой мы всегда стремились

Bakın: Her Zaman Aradığımız Özerklik

Kìa: Quyền tự chủ mà chúng tôi luôn tìm kiếm

看哪：我们一直寻求的自主权

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References Acknowledgments This work is financially supported by the National Key Research and Development Program of China (2017YFA0303 704), the National Natural Science Foundation of China (12274233, 62273001), the Major Scientific Research Project of Anhui Province (KJ2021ZD0005), the Compiled Scientific Research Plan Project of Anhui Province (2022AH040020), the Outstanding Research and Innovation Team Project of Anhui Province (2022AH010005), the University Collaborative Innovation Project of Anhui Province (GXXT-2021-091). References [1] Pareek NK, Patidar V, Sud KK. Image encryption using chaotic logistic map. Image Vision Comput 2006; 24:926-934. [2] Fang P, Liu H, Wu C, Liu M. A survey of image encryption algorithms based on chaotic systesm. Visual Comput 2022; 2022: 1-29. [3] Zhang Y, Wang B. Optical encryption based on interference. Opt Lett 2008; 33: 2443-2445. [4] Zhang Y, Wang X. A symmetric image encryption algorithm based on mixed linear–nonlinear coupled map lattice. Inform Sciences 2014; 273: 329-351. [5] Tedmori S, AI-Najdawi N. Image cryptographic algorithm based on the Haar wavelet transform. Inform Sci 2014; 269: 21-34. [6] Chai x, Gan Z, Chen Y, Zhang Y. A visually secure image encryption scheme based on compressive sensing. Signal Process 2017; 134:35-51. [7] Luo Y, Zhou R, Liu J, Cao Y, Ding X. A parallel image encryption algorithm based on the piecewise linear chaotic map and hyper-chaotic map. Nonlinear Dynam 2018; 93:1165-1181. [8] Zia U, McCartney M, Scotney B, Martinez J, AbuTair M, Memon J. Survey on image encryption techniques using chaotic maps in spatial, transform and spatiotemporal domains. Int J Inf Secur 2022; 21:917-935. [9] Chen J, Zhu Z, Fu C, Yu H. A fast image encryption scheme with a novel pixel swapping-based confusion approach. Nonlinear Dynam 2014; 77:1191-1207. [10] Wong K, Kwok B, Yuen C. An efficient diffusion approach for chaosbased image encryption. Chaos Soliton Fract 2009; 41:2652-2663. [11] Matthews R. On the derivation of a “chaotic” encryption algorithm. Cryptologia 1989; 13:29-42. [12] Massoudi A, Lefebvre F, De Vleeschouwer C, Macq B, Quisquater JJ. Overview on selective encryption of image and video: challenges and perspectives. Eurasip J Inf Secur 2008; 2008:179290. [13] Liu F, Koenig H. A survey of video encryption algorithms. Comput Secur 2010; 29: 3-15. [14] Chiaraluce F, Ciccarelli L, Gambi E, Pierleoni P, Reginelli M. A new chaotic algorithm for video encryption. IEEE T Consum Electr 2002; 48:838-844. [15] Lian S, Sun J, Wang J, Wang Z. A chaotic stream cipher and the usage in video protection. Chaos Soliton Fract 2007; 34:851-859. [16] Yang S, Sun S. A video encryption method based on chaotic maps in DCT domain. Prog Nat Sci 2008; 18:1299-1304. [17] Valli D, Ganesan K. Chaos based video encryption using maps and Ikeda time delay system. Eur Phys J Plus 2017; 132:1-18. [18] Kumar RR, Ganeshkumar D, Suresh A, Manigandan K. A new one round video encryption scheme based on 1D chaotic maps. in: 2019 5th Int Conf Adv Comput Commun Syst; 2019:439-444. [19] Li x, Yu H, Zhang H, Jin X, Sun H, Liu J. Video encryption based on hyperchaotic system. Multimed Tools Appl 2020; 79:23995-24011. [20] Yasser I, Mohamed A, Samra AS, Khalifa F. A chaotic-based encryption/decryption framework for secure multimedia communications. Entropy 2020; 22:1253. [21] Hosny KM, Zaki MA, Lashin NA, Hamza HM. Fast colored video encryption using block scrambling and multi-key generation. Visual Comput 2022; 2022:1-32. [22] Dua M, Makhija D, Manasa PYL, Mishra P. 3D chaotic map-cosine transformation based approach to video encryption and decryption. Open Comput Sci 2022; 12:37-56. [23] Hamidouche W, Farajallah M, Sidaty N, Assad S, Deforges O. Real-time selective video encryption based on the chaos system in scalable HEVC extension. Signal Process: Image Commun 2017; 58:73-86. [24] Chen H, Tanougast C, liu Z, Blondel W, Hao B. Optical hyperspectral image encryption based on improved Chirikov mapping and gyrator transform. Opt Laser Eng 2018; 107:62-70. [25] Fu C, Chen J, Zou H, Meng W, Zhan Y, Yu Y. A chaos-based digital image encryption scheme with an improved diffusion strategy. Opt Express 2012; 20:2363-2378. [26] Zhong J, Jiang D, Huang Q, Cao Y. A self-updating digital chaotic stream cipher. Int J Mod Phys 2018; 29:1850074. [27] Hua Z, Zhou Y. Image encryption using 2D Logistic-adjusted-Sine map. Inform Sci 2016; 339:237-253. [28] Li c, Lin D, Feng B, Lv J, Hao F. Cryptanalysis of a chaotic image encryption algorithm based on information entropy. IEEE Access 2018; 6: 75834-75842. [29] Man Z, Li J, Di X, Sheng Y, Liu Z. Double image encryption algorithm based on neural network and chaos. Chaos Soliton Fract 2021; 152:111318. [30] Kwok HS, Tang WKS. A fast image encryption system based on chaotic maps with finite precision representation. Chaos Soliton Fract 2007; 32:1518-1529. [31] Zhang X, Zhao Z, Wang J. Chaotic image encryption based on circular substitution box and key stream buffer. Singal Process 2014; 29:902-913. [32] Ye G, Wong KW. An efficient chaotic image encryption algorithm based on a generalized Arnold map. Nonlinear Dynam 2012; 69:2079-2087. [33] Rhouma R, Meherzi S, Belghith S. OCML-based colour image encryption. Chaos Soliton Fract 2009; 40:309-318. [34] Belazi A, Khan M, El-Latif AAA, Belghith S. Efficient cryptosystem approaches: S-boxes and permutation-substitution-based encryption. Nonlinear Dynam 2018; 87:337-361. [35] Wu Y, Zhou Y, Saveriades G, Agaian S, Noonan JP, Natarajan P. Local Shannon entropy measure with statistical tests for image randomness. Inform Sci 2013; 222:323-342. [36] Artiles JAP, Chaves DPB, Pimentel C. Image encryption using block cipher and chaotic sequences. Signal Process 2019; 79:24-31. [37] Xian Y, Wang X. Fractal sorting matrix and its application on chaotic image encryption. Infrom Sci 2021; 547:1154-1169. [38] Rukhin A,et al. A statistical test suite for random and pseudorandom number generators for cryptographic applications. NIST Special Publication 800-22, Revision 1.a 2010. [39] Wang X, Teng L, Qin X. A novel colour image encryption algorithm based on chaos. Signal Process 2012; 92:1101-1108. [40] Alvarez G, Li S. Some basic cryptographic requirements for chaos-based cryptosystems. Int J Bifurcat Chaos 2006; 16:2129-2151. [41] Khan M, Massod F. A novel chaotic image encryption technique based on multiple discrete dynamical maps. Multimed Tools Appl 2019; 78:26203- 26222. [42] Luo Y, Yu J, Lai W, Liu L. A novel chaotic image encryption algorithm based on improved baker map and logistic map. Multimed Tools Appl 2019; 78: 22023-22043. [43] Mansouri A, Wang X. A novel one-dimensional sine powered chaotic map and its application in a new image encryption scheme. Inform Sci 2020; 520:46-62. [44] Talhaoui MZ, Wang X. A new fractional one dimensional chaotic map and its application in high-speed image encryption. Infrom Sci 2021; 550:13- 26. [45] Chen H, Bai E, Jiang X, Wu Y. A Fast Image Encryption Algorithm Based on Improved 6-D Hyper-Chaotic System. IEEE Access 2022; 10:116031- 116044. [46] Azzeh J, Zahran B, Alqadi Z. Salt and pepper noise: Effects and removal. JOIV: Int J Inform Visual 2018; 2:252-256. [47] Gan Z, Chai X, Han D, Chen Y. A chaotic image encryption algorithm based on 3-D bit-plane permutation. Neural Comput Appl 2019; 31:7111- 7130.

Acknowledgments and References 

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References 8. Conclusion To sum up, a parallel computing technique based real-time chaotic video encryption strategy is proposed in this paper. It uses multiple threads to simultaneously perform confusion and diffusion operations on corresponding subframes to improve the computational efficiency. To evaluate the performance of the strategy, two chaotic maps are selected to implement cryptosystems. The encryption speed evaluation prove that such strategy significantly improves the encryption speed, and realizes realtime video encryption with different hardware platforms. The statistical and security analysis show that the deployed cryptosystems have outstanding statistical properties and resistance to attacks, noise, and data loss. Compared with previous works, the proposed strategy, to the best of our knowledge, achieves the fastest encryption speed, realizes the first real-time video encryption based on multiple-round confusion-diffusion architecture. This paper provides a feasible solution and a new path for related applications and research, respectively. CRediT authorship contribution statement Conceptualization, Methodology, Writingoriginal draft, Software, Supervision. Zhen Yuan: Investigation, Methodology, Software . Investigation, Software. : Conceptualization, Methodology, Writing - review & editing, Supervision. Dong Jiang: Wen-xin Li: Liang-liang Lu Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Data will be made available on request. This paper is under CC 4.0 license. available on arxiv

Advancing Video Encryption with Real-Time Parallel Computing Strategy: Conclusion

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References 7. Comparison To Previous Works As discussed above, existing algorithms can be divided into full and selective video encryption. The proposed strategy, clearly, belongs to the former category. In this section, therefore, the deployed cryptosystems are compared with several recent published papers on full video encryption. The results are shown in Tab. 9. For some selected works, videos of different sizes are used to evaluate the encryption speed. We list the encryption speed for the largest videos in the table. With the development of information science and hardware, the users put forward higher requirements for security. Thus almost all the latest works are based on confusion-diffusion architecture. To the best of our knowledge, however, these works only consist of one round of confusion and diffusion operation to improve the computational efficiency. And they cannot meet the requirements of real-time encryption, that is, the average encryption time (ms) of video frames is less than 1000 / FPS. Therefore, compare to previous works, the proposed strategy achieves the following advantages: i) It realizes real-time video encryption, provides a feasible solution for related applications, and points out a new path for related research. ii) By taking advantages of parallel computing technique, it proves that real-time video encryption based on multiround confusion-diffusion architecture is possible, and thus improves the security of real-time video encryption to the level of image encryption. iii) It works with many confusion, diffusion methods, and different chaotic maps. iv) It can be easily implemented with both software and hardware such as ARM, FPGA, etc. This paper is under CC 4.0 license. available on arxiv

Strides in Real-Time Video Encryption: Comparison To Previous Works

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References 3. Encryption Speed Evaluation To evaluate the encryption speed of the proposed strategy, two highly-cited chaotic maps are selected to implement PRBGs. The first PRBG uses two Piecewise Linear Chaotic Maps (PLCM) [26], which is defined as follows: Three hardware platforms are selected to carry out the evaluations. The specifications of the platforms are listed in Tab. 1. The software development environment are as follows: Ubuntu 20.04 operating system, OpenCV 4.2.0, and g++ 9.4.0. Second, we set the rounds of confusion and diffusion r to 5 (see section 6 for the reasons), perform five rounds of confusion operations on 100 images of size 960×960 with different number of assistant threads, calculate the average time to scramble an image, and plot the results in 2 (d)-(f). Similarly, we use different number of assistant threads to generate byte sequences, perform five rounds of diffusion operations on 100 images of size 960 × 960 using the generated bytes, and calculate the average time to complete five rounds of diffusion operations on an image. The relationship between the average diffusion time (including byte generations and diffusion operations) are drawn in Fig. 2 (g)-(i). Compared with the single-threaded versions of byte generation, confusion, and diffusion, clearly, the proposed strategy significantly speeds up these steps. Third, to evaluate the practical performance of the proposed strategy, a set of videos of different sizes are encrypted using the deployed cryptosystems. Similar to above experiments, the rounds of confusion and diffusion r is set to 5. The number of assistant threads n are set to 8, 12, and 32 for laptop, personal computer, and workstation, respectively (see section 6 for the reasons). The Frames Per Second (FPS) of the selected vidoes is 20, that is, the maximum time for encrypting a frame must be less than 50ms, otherwise, there will exist delay during encryption and transmission. Each video consists of 600 frames. The average encryption time are listed in Tab. 2, which shows that real-time 576×576, 672×672, and 960×960 video encryption are realized using Intel Core i5-1135G7, Intel Core i7-8700, and Intel Xeon Gold 6226R, respectively. This paper is under CC 4.0 license. available on arxiv

Enhancing Video Encryption Speed: Evaluating Chaotic Maps for PRBG Implementation

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References 6. Parameter Setup According to the encryption process, clearly, the number of assistant threads n and the rounds of confusion and diffusion r significantly affect the the encryption speed and the statistical performance of the deployed cryptosystems. In all experiments carried out in this paper, n is set to 8, 12, and 32 for laptop, personal computer, and workstation, respectively, and r is set to 5. The reasons for such settings are analyzed in this section. We use different number of assistant threads to encrypt a plain video of size 576 × 576 using three hardware platforms. The relationship between the average encryption time and the number of assistant threads are drawn in Fig. 8. Set n to the maximum number of threads supported by CPU is unnecessary, however, can guarantee the deployed cryptosystems reach their fastest encryption speed. The purposes of diffusion and confusion operations are to improve the plaintext sensitivity of the cryptosystems and decrease the correlation of the plain images. We, thus, generate byte sequences, perform 10 rounds of diffusion operations on a plain image, randomly select a pixel, change its value, perform 10 rounds of diffusion operations on the modified image with the same byte sequences, and calculate NPRC and UACI between the generated cipher images. The results are plotted in Fig. 9. Similarly, we perform 10 rounds of confusion operations on a plain image. The plain image and the scrambled images after 1-5 rounds of confusion operations are shown in Fig. 10. The correlation coefficients between the plain image and the scrambled images after different rounds of confusion operations are drawn in Fig. 11. When r is equal to 5, clearly, NPCR, UACI, and the correlation coefficient reach the upper and lower bounds, respectively. This paper is under CC 4.0 license. available on arxiv

Parameter Optimization for Robust Cryptosystem Performance in Encryption

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References 5. Security Analysis 5.1. Key Space And Sensitivity In addition, the cryptosystem should have high sensitivity to the change of key in encryption and decryption process. That is, even one bit of the key is changed, the attacker cannot obtain any information from the decrypted image. To analyze the key sensitivity of the proposed strategy, we randomly select key, use the deployed cryptosystems to ecnrypt an iamge, followed by decrypting the cipher image with the correct key. The images decrypted with PLCM and 2DLASM are plotted in Fig. 5 (a) and (e), respectively. Then we slight change the key by adding an increment δ = 0.000000001 on initial condition and control parameter, decrypted the cipher image with the slightly modified Key. The images decrypted by PLCM based cryptosystem using x0 + δ, p + δ, and x0 + δ, p + δ are shown in Fig. 5 (b), (c), and (d), respectively. The images decrypted by 2DLASM based cryptosystem using x0 + δ, µ + δ, and x0 + δ, µ + δ are shown in Fig. 5 (f), (g), and (h), respectively. We also calculate the correlation coefficients between the images decrypted with the correct key and the images decrypted with the slightly changed key, and list the results in Tab. 7. 5.2. Resistance To Differential Attacks To resist differential attacks, the encryption algorithms should have high sensitivity to the plain image, that is, a minor change in the plain image will lead to a completely change in the cipher image [41]. To evaluate the ability of the proposed strategy to resist such attacks, Number of Pixels Change Rate (NPCR) and Unified Average Changing Intensity (UACI) are calculated [42]. NPCR can be calculated according to the following equation: According to Refs. [43, 44], for an image of size 512 × 512, when the significance level is equal to 0.05, the expected values of NPCR and UACI are 99.5893% and [33.3730%, 33.5541%], respectively. An image encryption scheme passes the diffusion property test when NPCR is higher than the expected value, and UACI falls within the interval. In the proposed strategy, despite all assistant threads perform diffusion operations independently, they take the last pixel of the next subframe as the diffusion seed to reconstruct the relationship between all subframes. This guarantees that one pixel changed in any subframe, will result in a completely different cipher frame. To fully evaluate the resistance of the proposed strategy to differential attacks, we generate byte sequences, encrypt a set of plain images, randomly select and change a pixel in the plain images, encrypt the modified images with the same byte sequences, calculate NPCR and UACI between the generated cipher images. For each plain image, we repeat above steps for 100 times, fetch the minimum, maximum, and average values, and list the results in Tab. 8. 5.3. Resistance To Noise And Data Loss Images or video frames may be affected by noise while transmitting over the channel. When a cipher image has noise or losses part of data, the cyrptosystem needs to recover the original image with high visual quality [45]. To evaluate the robustness, we use the two deployed cryptosystems to encrypt a plain image with randomly selected keys, add 1%, 3%, and 5% salt-and-pepper noise [46] to the generated cipher images, use the same keys to decrypt the cipher images, and plot the plain and decrypted images in Fig. 6. Although the decrypted image are changed when there exists noise in the cipher image, the approximate information of the plain image is preserved, even when the slat-and-pepper noise as high as 5%. In real application, image cropping is very common, which may lead to data loss [47]. To assess the capability of the proposed strategy to resist the data loss, similarly, we use the deployed cryptosystems to encrypt a plain image, randomly select and remove 64 × 64, 128 × 128, or 512 × 512 blocks from the cipher images, replace the removed block with white or black blocks, decrypt the modified cipher images with the same keys, and show the results in Fig. 7. Clearly, the contours of the plain images are preserved, even though 256 × 256 blocks are removed from the cipher images. That is, when there exist 25% data loss in the cipher image, the deployed cryptosystems can still recover the information of the plain image. The proposed strategy, therefore, can resist noise and data loss. This paper is under CC 4.0 license. available on arxiv

Robust Cryptosystem Analysis: Key Space Sensitivity and Differential Attack Resistance

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References 4. Statistical Evaluation The essence of real-time video encryption is image encryption, which should provide excellent statistical properties to resist different types of attacks [28]. In this section, therefore, the uniformity, correlation, and randomness of the deployed cryptosystems are analyzed. The following experiments are performed using the laptop (Intel Core i5-1135G7), and the parameter setup are as follows: number of assistant threads: n = 8, confusion and diffusion rounds r = 5, the size of all plain images used for statistical evaluation is 512 × 512. 4.1. Uniformity Evaluation The histogram, variances and χ 2 of histograms are utilized to evaluate the uniformity of the deployed cryptosystems. The plain image is plotted in Fig. 3 (a), and its histograms of red, green, blue channels are shown in 3 (b), (c), (d), respectively. The cipher image encrypted with PLCM is shown in Fig. 3 (e). Its histograms of red, green, blue channels are shown in Fig. 3 (f), (g), (h), respectively. The cipher image encrypted with 2DLASM is shown in Fig. 3 (f). Its histograms of red, green, blue channels are shown in Fig. 3 (j), (k), (l), respectively. 4.2. Correlation Evaluation Since two adjacent pixels in an image usually have high correlation, the cryptosystems should decrease the correlation to resist statistical attacks [32]. Therefore, the correlation between two adjacent pixels in plain and cipher images are analyzed. We first randomly select 6000 pairs of two horizontally, vertically, and diagonally adjacent pixels from the plain and cipher images. The correlation distribution of red, green, and blue channels in plain image shown in Fig. 4 (a), (b), (c), respectively. The correlation distribution of red, green, and blue channels in cipher image are plotted in Fig. 4 (d), (e), (f), respectively. The correlation distribution of red, green, and blue channels in cipher image shown in Fig. 3 (i) are drawn in Fig. 4 (g), (h), (i), respectively. When the correlation coefficient of a cipher image is lower, the resistance capability of the encryption algorithm to statistical analysis attacks is stronger. To assess the correlation property of the proposed strategy, we encrypt a set of plain images using PLCM and 2DLASM, randomly select 20000 adjacent pixels in horizontal, vertical, and diagonal directions from the plain and cipher images, calculate the correlation coefficients, and list the results in Tab. 4. The deployed cryptosystesm, clearly, significantly decrease the correlation of the plain images. 4.3. Randomness Evaluation This paper is under CC 4.0 license. available on arxiv

Statistical Assessment of Cryptosystems for Image Uniformity, Correlation, and Randomness

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References 2. Strategy Description In diffusion, the following equation is employed[25]: This paper is under CC 4.0 license. available on arxiv

Mastering Chaotic Video Encryption: Deciphering the Diffusion Equation

Authors: (1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & jiangd@nju.edu.cn; (2) Zhen Yuan, School of Internet, Anhui University; (3) Wen-xin Li, School of Internet, Anhui University; (4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & lianglianglu@nju.edu.cn. Table of Links Abstract & Introduction Strategy Description Encryption Speed Evaluation Statistical Evaluation Security Analysis Parameter Setup Comparison To Previous Works Conclusions Acknowledgments & References Abstract Due to the strong correlation between adjacent pixels, most image encryption schemes perform multiple rounds of confusion and diffusion to protect the image against attacks. Such operations, however, are time-consuming, cannot meet the real-time requirements of video encryption. Existing works, therefore, realize video encryption by simplifying the encryption process or encrypting specific parts of video frames, which results in lower security compared to image encryption. To solve the problem, this paper proposes a real-time chaotic video encryption strategy based on multithreaded parallel confusion and diffusion. It takes a video as the input, splits the frame into subframes, creates a set of threads to simultaneously perform five rounds of confusion and diffusion operations on corresponding subframes, and efficiently outputs the encrypted frames. The encryption speed evaluation shows that our method significantly improves the confusion and diffusion speed, realizes real-time 480 × 480, 576 × 576, and 768 × 768 24FPS video encryption using Intel Core i5-1135G7, Intel Core i7-8700, and Intel Xeon Gold 6226R, respectively. The statistical and security analysis prove that the deployed cryptosystems have outstanding statistical properties, can resist attacks, channel noise, and data loss. Compared with previous works, to the best of our knowledge, the proposed strategy achieves the fastest encryption speed, and realizes the first real-time chaotic video encryption based on multi-round confusion-diffusion architecture, thus, providing a more secure and feasible solution for practical applications and related research. : Real-time video encryption, Parallel computing, Chaotic systems, Confusion and diffusion Keywords 1. Introduction With the rapid development of information and communication technologies, images and videos have shown enormous potential in data storage and network transmission, resulting in extensive application requirements for image and video encryption [1]. However, most conventional cryptographic schemes, such as DES, AES, RSA, etc., are designed to protect textual information, they are not suitable for images and videos [2]. As a result, many image encryption protocols have been proposed over recent years based on different techniques [3, 4, 5, 6], in which chaos based methods attract significant attention, due to the intrinsic characteristics of chaotic systems, including ergodicity, non-periodicity, non-convergence, sensitivity to initial conditions and control parameters, et al. [7]. Most chaos based image encryption algorithms comprises confusion and diffusion phases [8]. In the former phase, the pixel positions are scrambled over whole image without changing the values [9]. In the latter phase, the pixel values are modified sequentially with the byte sequences generated by chaotic systems [10]. Such confusion-diffusion architecture based image encryption protocols need to perform the two phases for multiple rounds until a satisfactory security level is achieved [11]. This, obviously, is very time-consuming and cannot meet the realtime requirements of video encryption. Existing works, therefore, realize video encryption through simplifying encryption process or encrypting specific pixels in the video[12, 13]. For the first category (also known as the full encryption), for example, Ref. [14] selects three chaotic maps to generate byte sequences, and directly performs XOR operations between the pixels and the generated bytes to encrypt the video; Refs. [15] use the generated bytes to encrypt the frame, and take the encrypted pixels as feedback to improve the plaintext sensitivity of the deployed cryptosystem; Ref. [16] performs one round of confusion operation on the video frame, followed by acting XOR operations between the pixels and the generated bytes to realize frame encryption; Since practical applications put forward higher requirements for security, most recently published works are based on one-round confusion-diffusion architecture[17, 18, 19, 20, 21, 22]. The second category is also known as the selective encryption, the algorithms belong to this category encrypt specific pixels in the video frame to reduce the computational complexity [23]. These categories of strategies, clearly, achieve high efficiency at the expense of security. Therefore, how to realize real-time video encryption without compromising the security has become an urgent problem to be solved. In the field of full video encryption, however, there are few related research. And to the best of our knowledge, existing works cannot realize real-time video encryption, i.e., the the number of frames encrypted in a second is larger than FPS (Frames Per Second) of the video or the average encryption time (ms) is less than 1000 / FPS. This paper, thus, takes the advantage of parallel computing, designs a five-round confusion-diffusion architecture based real-time chaotic video encryption strategy. To evaluate the performance, two cryptosystems are implemented using two different chaotic maps. Three hardware platforms are used to assess the encryption speed of the deployed cryptosystems. The evaluation results show that our strategy significantly improves the speed of byte generation, confusion, and diffusion, laying the foundation for the realization of real-time video encryption. The statistical and security analysis prove that the deployed cryptosystems have outstanding statistical properties and resistance to attacks, channel noise and data loss. The proposed strategy also suitable for many confusion and diffusion methods, and can be easily realized with both software and hardware. The rest of the paper are organized as follows: section 2 gives a detailed description of the proposed strategy. In section 3, two typical chaotic maps are selected to realize the strategy, and the encryption speed of the deployed cryptosystems are evaluated using three different hardware platforms. Section 4 and 5 carry out statistical and security analysis, respectively. Section 6 analyzes the reasons for the parameter settings used in this paper. In section 7 gives a comparison to recent published works, followed by a brief conclusion in section 8. This paper is under CC 4.0 license. available on arxiv

Real-Time Chaotic Video Encryption Based on Multithreaded Parallel Confusion and Diffusion

মাল্টিথ্রেডেড প্যারালাল কনফিউশন এবং ডিফিউশনের উপর ভিত্তি করে রিয়েল-টাইম বিশৃঙ্খল ভিডিও এনক্রিপশন

Chaotische Videoverschlüsselung in Echtzeit basierend auf paralleler Multithread-Verwirrung und -Diffusion

Cifrado de vídeo caótico en tiempo real basado en confusión y difusión paralela multiproceso

Cryptage vidéo chaotique en temps réel basé sur la confusion et la diffusion parallèles multithread

मल्टीथ्रेडेड समानांतर भ्रम और प्रसार पर आधारित वास्तविक समय अराजक वीडियो एन्क्रिप्शन

マルチスレッドの並列混乱と拡散に基づくリアルタイムのカオスビデオ暗号化

멀티스레드 병렬 혼동 및 확산 기반의 실시간 혼돈 영상 암호화

Criptografia de vídeo caótica em tempo real baseada em confusão e difusão paralela multithread

Хаотическое шифрование видео в реальном времени на основе многопоточной параллельной путаницы и диффузии

Çok İş parçacıklı Paralel Karışıklık ve Dağıtıma Dayalı Gerçek Zamanlı Kaotik Video Şifreleme

Mã hóa video hỗn loạn theo thời gian thực dựa trên sự nhầm lẫn và khuếch tán song song đa luồng

基于多线程并行混淆扩散的实时混沌视频加密

Hey there, fellow tech enthusiasts! My name is and today, I want to share with you some insides of mine. As a seasoned developer who's seen the ebb and flow of the digital tide, let's dive into the swirling vortex of what the future might hold for us in 2024. Grab your digital crystal ball, folks, because here come some spicy predictions! Alex Cloudstar, The Era of Augmented Reality 🌐 Picture this: virtual worlds blending seamlessly with our reality. That’s right, folks, AR is about to take a massive leap in 2024. From enhancing customer experiences in retail to transforming education, this tech is set to reshape how we interact with the world. Get ready for a mix of Pokémon GO-like experiences and practical applications that’ll blow your socks off! But I can’t say that I am a fan of this. Just like with other forms of technology, there's a risk of over-reliance and addiction. People might become so engrossed in AR experiences that they neglect real-world responsibilities or become detached from reality. While AR can create immersive experiences, it might also lead to further social detachment. If individuals start preferring virtual interactions over real-world interactions, it could potentially worsen issues related to social isolation and decrease physical human contact. AI, AI, AI Everywhere 🤖 Artificial Intelligence is no longer the next big thing; it's the now big thing. In 2024, we'll see AI continue to weave itself into our daily lives, from predictive analytics guiding business decisions to AI-powered assistants handling more complex tasks. But fear not, humans, for we shall remain the masters behind the machines! Quantum Computing: Unlocking the Unthinkable 🔐 Hold onto your hats, folks, because quantum computing is inching closer to reality in 2024. We're talking about mind-boggling computational power that could revolutionize industries, from healthcare to finance, solving problems that were once deemed unsolvable. It's like upgrading from a bicycle to a warp-speed spaceship! Sustainable Tech 🌱 With great tech comes great responsibility. In 2024, the tech world is taking a giant leap toward sustainability. From eco-friendly data centers to renewable energy-powered devices, the focus on reducing our digital carbon footprint is becoming more crucial than ever. Agrotech and Food Sustainability are essential. Technologies focusing on sustainable agriculture practices, precision farming, and resource-efficient techniques like vertical farming or smart irrigation play a crucial role in ensuring food security while reducing environmental impact. The Rise of Privacy Tech 🔒 Privacy concerns have been making headlines for years, and in 2024, they're taking center stage. As users become more aware of their data rights, we'll witness a surge in privacy-focused tech. Encryption, decentralized systems, and user-centric platforms will shine as guardians of our digital identities. Privacy is the new black, my friends! Now, you might be wondering, "How do I prepare for this tech revolution?" Well, fear not, intrepid developers, for I've got a few tips up my sleeve: Embrace change like a long-lost friend. Keep learning, exploring new technologies, and adapting like a chameleon in a digital jungle. Stay Agile, Stay Relevant: Engage with the tech community. Attend conferences, join forums, and collaborate on projects. The collective wisdom of the crowd is a treasure trove of insights. Community is Key: With great tech comes great vulnerabilities. Prioritize security in your code and stay updated on the latest cybersecurity trends. Focus on Security: As tech evolves, consider the ethical implications of your creations. Build responsibly, with an eye toward the greater good. Ethics Matter: The future is unwritten. Embrace uncertainty, for it’s where innovation thrives. Embrace the Unknown: So, dear readers, fasten your seatbelts, charge your devices, and get ready for a rollercoaster ride through the tech-scape of 2024. It's a thrilling time to be a part of this ever-evolving industry! Until next time, happy coding, and may your bugs be minimal and your breakthroughs monumental!

Tech Predictions for 2024: Taking A Peak Into a Senior Developer's Crystal Ball

Learn about the key performance metrics that mobile teams should track in their mobile apps so they can deliver better user experiences. In order to build the best experiences, engineers need the best data available. Mobile makes this challenge more complex, with variables that include device types, different operating systems, and connectivities, to name just a few. With a growing number of tools that all offer varying levels of visibility into your mobile app's health, performance, and stability, it can be difficult to know exactly which metrics you should be tracking. In this post, we’ll outline the most important performance metrics you need to track and how they help you get to the root cause of issues more quickly so you can build better mobile experiences. 1. Startup time Mobile users typically check their apps on the go and are accustomed to instantaneous results. Therefore, they won’t sit around and wait for the app to load. For example, if the Uber app takes too long to load, the user will probably switch to the Lyft app instead. In addition, users who had a poor experience in the Uber app and a decent experience in the Lyft app are much more likely to become a loyal Lyft user. Now, not only have you lost revenue from that user’s session, but your cost per acquisition and churn increased, not to mention the LTV that particular customer could have brought the company. Therefore, is essential to its success. ensuring your app’s startup time meets user expectations However, if the mobile team only has access to the , they probably miss key changes and respond reactively rather than proactively. average startup time For example, let’s say a company is launching its app into a new market, and the overall feedback is negative. The average startup time shows that the app is a few milliseconds longer than it was before the launch, but it doesn’t indicate that it became dramatically slower during the launch. So there must be another problem, right? Unfortunately, because the percentage of users in the new market is only a fraction of the overall user base, it makes sense that even an abysmal startup time in the new market would only minimally impact the total user base’s startup time. Instead, the team needs to be able to segment the data to better understand how startup time impacts the business. For example, how are high-value users suffering from slow startups? Are users in a new market experiencing worse performance? Are certain devices experiencing slower startups? This data puts your company back in control of the situation and omits the guesswork in time-sensitive scenarios that impact your revenue. To learn more, check out our eBook on . how to improve mobile app startup time 2. Crash rate are a surefire way to anger customers and for a good reason! It’s essentially the equivalent of a customer walking into a brick-and-mortar store where the staff kicks them out the door halfway through their shopping. Crashes This is a major issue for the company’s brand for two reasons: It as customers feel their time is disrespected. damages the reputation of your brand It hurts your revenue as customers can’t complete their immediate transaction, and you lose the lifetime value of that customer if they decide to switch to a competitor. Here are just a few examples from various industries where a crash directly translates to lost revenue: If an e-commerce app crashes during checkout, the customer won’t be able to make their purchase and likely won’t be back. E-commerce Apps: : If a POS system crashes during a live event, none of those live customers will be able to make a purchase or enter the venue. POS Systems : If a smart device, such as a toothbrush, crashes during the setup process, it’s very likely the customer will return the product. Smart Device Apps However, while tracking the average crash rate is a good start, it’s . still not enough to understand how crashes impact your business For example, if the current crash rate is just 0.5%, you might not see the need to drill deeper. However, what if all of the crashes that occur happen at the checkout screen? That tiny percentage could be cheating the business out of significant revenue. So, in addition to looking at the major metric numbers, it’s also important to have data that shows patterns in the crash rate. Specifically, how are various high-value areas in your app performing? Which devices tend to experience the most crashes? How is the app performing for high-value users? Are there any regions that experience particularly poor crash rates? And if so, should the app be fixed or removed from those regions? By segmenting crash details, your team can better prioritize fixing issues. 3. ANR rate are typically described as freezes or glitches. Application Not Responding (ANR) errors Essentially, if the main thread is blocked, the applications cannot run effectively. Therefore, the user cannot proceed, which can have a major impact on your business. For example, a retailer we worked with had an issue with ANRs. This issue was causing startup times to increase by almost 60%, translating to an estimated revenue loss of $6.5 million per year. , the engineering team was able to quickly address the issue and reclaim that lost revenue. With the right data Beyond revenue, ANRs can also in the Google Play Store and make it less visible to new customers. negatively impact an app’s rankings To effectively track ANRs, you can look at the stack trace and see how users responded to the issue. From there, the mobile team can prioritize what to fix first based on how many people leave at various thresholds, where high-value users are most affected, and which device types and screens are most affected by ANRs. To learn more, check out . this post on investigating Android crashes like ANRs 4. Region metrics Tracking region metrics is also very important as users in different regions have different devices and different connectivities. This can have a major impact on the business for several reasons. First, regions differ in their importance to a business’s bottom line. For example, perhaps only a portion of your users are in Singapore, but they might make up a large portion of your total annual revenue. Therefore, checking region metrics on a granular level will spotlight opportunities to improve the app, particularly for high-value users. Tracking segmented region metrics is also essential when launching into a new region. For example, suppose you expand into Australia, yet that geographic area only makes up 5% of all users on launch. In that case, it won’t impact median/average metrics enough to allow the team to effectively track performance. It’s also important to take into account cultural differences, and with a tool that provides region-specific metrics, the team can test specific aspects of the app just for that region. For example, an e-commerce checkout screen that converts well in the United States may not convert as well in Dubai. In addition, granular region metrics make it easy to roll out new features slowly. For example, the team can roll out a new feature in a smaller region and see how it performs. If it performs well, roll it out to more and more regions with higher-value users. This data can guide your team in answering critical questions like: Do we need to build a new app for this region? How is this new launch performing compared to launches in other regions? Which regions are the most problematic? And should we stop serving them altogether? ​​How are various critical areas of the app performing in one region versus another? 5. Session duration Another key metric to keep an eye on is session duration, as it signals how long users are using your app. If the average session duration changes dramatically in a week, it’s a pretty good hint that there is an issue with the app. For example, if you have a gaming app and notice the average session duration dropped from 15 minutes to 5 minutes, there’s a good chance that users had a poor experience. With this clue, you can ask questions like: Did we ship a bad release? Are users less engaged with the app? Is there a corresponding change in another metric that can help explain the change in session duration? Tracking session duration also allows the team to investigate patterns among the affected individual sessions and discover the root cause of issues. By analyzing session duration in parallel with other metrics, mobile engineers can draw a clearer picture of which issues are most intrusive to users. For example, an e-commerce store might have an OOM issue on the main scrolling feed of products that correlates strongly with a shorter session duration, whereas slow network calls on another screen have little to no correlation with the session duration. Therefore, tracking session duration is a great way to prioritize which issues should be fixed first as it directly reveals reduced user engagement. 6. Churn/retention rate It costs a lot more to acquire a new customer than it does to keep a current customer happy, and a leading cause of churn in mobile app users is a poor user experience. Downloading a new app only takes a few seconds, so if an app’s experience interrupts the user in a way that takes more than a few seconds of their time, don’t expect them to stick around. Therefore, track not only the overall churn and retention rate but also the churn and retention rates of segments of the user base (by devices, connectivities, regions, etc.). This will illuminate various opportunities to improve and prioritize retention. For example, you may find that while the churn rate is very high in one particular region, that region has few high-value users. Therefore, you may decide to invest engineering resources somewhere else where they will translate to larger business outcomes. Tracking churn and retention is also a great way to understand how users respond to new releases and various experiments. If there is a correlation between high churn and a new feature update, that’s a strong indicator that the team needs to roll back that feature update. Detailed data will allow the team to track the churn of various segments (such as specific regions or devices) to which the update is rolled out. Without segmented data, it will be difficult to see the impact that various feature updates have on small testing groups. Therefore, only once the feature is rolled out to a large group of users (and presumably caused many monthly active users to leave) will it become apparent that the feature rollout was premature. 7. User termination rate While some user terminations are nothing more than a user decluttering their phone, many terminations occur because the app has frozen, and the user has no choice but to swipe up and terminate the session. Of course, a user who is forced to terminate their session will likely be disgruntled and choose a competitor’s app instead. To prevent this, monitoring the average user termination rate is an excellent indicator of potential issues that could lead to churn, including: Failed ad loads are causing freezes Slow or broken user flows Failing purchases Server outages causing login errors Excessive media loading that causes slowdowns In addition to providing an overview of the average user termination rates, mobile teams need to know the source of every poor user experience. Therefore, one of the key features we built into Embrace is the ability to see . which screens cause frustrated users to abandon your app Therefore, rather than wasting valuable time and losing sales while engineers guess where the terminations are occurring, the mobile team is immediately directed to the issue so that they can fix the problem as efficiently as possible. 8. Timing of key user actions There are likely a few user actions within your app that absolutely must work 100% of the time. For example, if an office offers keyless entry, that feature must work every time. Otherwise, people may not be able to enter the office without calling additional support. Therefore, select a few key user actions and add them to the list of performance metrics the mobile team is tracking. In many cases, customer reviews don’t say where they experienced an issue in the app, so tracking specific user actions is a great way to catch issues that otherwise aren’t immediately apparent. This also helps you answer questions like: How many users experience issues in these critical areas of the app? Is there a direct correlation between issues in specific areas of the app and churn? How long do users try before giving up and abandoning the app? For example, one of our customers noticed that about 1% of all purchase attempts resulted in purchase failures. However, both of the associated network calls were resolving successfully, so there were no obvious errors to inspect. Therefore, they began tracking the exact moment a customer would make a purchase and found that the two network calls were happening out of order in 1% of purchase attempts, which resulted in a failed purchase. Though customers had been complaining about this issue, the mobile team couldn’t pinpoint the root cause without knowing the timing, outcome, and order of all events within the affected sessions. High-fidelity user experience data was vital in helping them reclaim 1% of their total sales. For a company doing $10 million in annual sales, that’s $100,000 that would otherwise be lost each year! 9. Memory usage It’s important to track your app’s memory consumption to identify any potential memory leaks. The efficiency of your app’s memory usage directly relates to how responsive your user experience is. This is why monitoring and optimizing memory usage plays a crucial role in delivering a seamless user experience. You can avoid issues with your app’s memory usage by: Optimizing your codebase and pinpointing areas where memory is unintentionally retained causes an increase in memory usage. Tracking your app’s memory consumption on a regular basis, noting any changes after new releases. Carefully monitoring memory-intensive operations like loading large images or processing large files and creating for abnormal spikes or sustained high memory usage. alerts A fine-tuned strategy regarding your app’s memory consumption creates responsive, stable, and effective apps that your users will love. 10. Connectivity Mobile apps operate in diverse environments with varying , including 3G, 4G, 5G, Wi-Fi, and sometimes limited or unstable connectivity. network conditions This is why it’s important to recognize the challenges posed by these varying conditions to create great user experiences. Indicators of poor network performance include: Latency and slow response times. Bandwidth usage. Inefficient API calls. Device-specific offline capabilities. For example, is an agricultural app that allows farmers and agronomists to document their findings while they’re in the field with their peers and colleagues. Farm Dog The app would crash often when network response times were exceptionally slow and when devices couldn’t determine whether they were connected. They noticed that Google Maps response times between 18-22 seconds when they should be only a few seconds. Without the proper tooling, they would need to use convoluted workarounds to solve issues using a proxy to simulate a bad network connection. However, with higher-fidelity data, they can see the exact conditions users have in the field, including: Network calls across device types, app versions, Wi-Fi, and cellular. Insight into 4xx and 5xx error trends across common domains to identify problematic pathways. The broken endpoints that prevent your users from starting up the app, loading key content, or completing crucial transactions. The duration of every network call from the client side reveals hidden points of latency. Armed with this information, the Farm Dog team simulated the issues their users faced, easily identified the problematic conditions, and fixed them. Set your mobile team up for success If you care about mobile experiences, then you need the data that enables your team to see all of the metrics mentioned above. Embrace helps you build better mobile experiences by giving you just that data, making your engineers more efficient and less bogged down by tedious work. Learn more about and download report to learn about key app frustrations according to users. Embrace The State of Mobile Experience Author: Colin Contreary Also published . here

10 Mobile App Performance Metrics You Need To Start Tracking

10টি মোবাইল অ্যাপ পারফরম্যান্স মেট্রিকস যা আপনাকে ট্র্যাকিং শুরু করতে হবে

10 Leistungskennzahlen für mobile Apps, die Sie benötigen, um mit dem Tracking zu beginnen

Diez métricas de rendimiento de aplicaciones móviles que necesita para comenzar a realizar un seguimiento

10 mesures de performances des applications mobiles dont vous avez besoin pour commencer le suivi

10 मोबाइल ऐप प्रदर्शन मेट्रिक्स जिनकी आपको ट्रैकिंग शुरू करने के लिए आवश्यकता है

追跡を開始する必要がある 10 のモバイル アプリのパフォーマンス指標

추적을 시작하는 데 필요한 10가지 모바일 앱 성능 지표

10 métricas de desempenho de aplicativos móveis que você precisa para começar a monitorar

10 показателей производительности мобильных приложений, которые нужно отслеживать

Takibe Başlamak İçin İhtiyacınız Olan 10 Mobil Uygulama Performans Metriği

10 số liệu hiệu suất ứng dụng di động bạn cần để bắt đầu theo dõi

您需要开始跟踪的 10 个移动应用性能指标

Scientific American Supplement, No. 799, April 25, 1891 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . THE RAISING OF THE ULUNDA. here THE RAISING OF THE ULUNDA. Shortly after the recovery of the Ulunda, below described, the North American and West Indian squadron of the Royal Navy visited Halifax, Nova Scotia. The simple and novel means adopted for raising the ship attracted considerable attention among the officers of the fleet, and by way of stimulating the studies of the junior officers in this branch of their duties, a prize was offered for the best essay on the subject, to be competed for by the midshipmen of the various ships. The essays were adjudicated upon by Captain W.G. Stopford, of the flag ship—H.M.S. Bellerophon—and the first prize was awarded to the following paper, written by Mr. A. Gordon Smith, of H.M.S. Canada. The article needs no apology, but it is only just, says the , to mention the fact that the writer is not yet eighteen years of age. Engineer The steamship Ulunda, on the remarkable raising and recovery of which this paper is written, is an iron screw ship of 1,161 tons, until lately belonging to the Furness line. It is a sister ship to the Damara, of the same company, and was built and engined by Alex. Stephens, shipbuilder and engineer, at Glasgow, being fitted with compound vertical engines, of 200 nominal horse power, having two cylinders of 33 inches and 66 inches diameter respectively, which are capable of sixty-five revolutions per minute, and give a speed of twelve knots an hour. For supplying steam to the engines there are two return-tube boilers, each having three furnaces, and there is also a donkey boiler, which is used in harbor for working the four steam winches on deck. She is divided into seven watertight compartments by athwartship bulkheads. The foremost one is the usual collision bulkhead. Between this and the foremost engine room bulkhead are Nos. 1 and 2 holds, separated by a watertight bulkhead. Abaft the after engine room are two more holds, divided in the same manner as the forward ones, and astern is another compartment, in which all stores are kept. Coal bunkers form a protection for the engines and boilers. Fore and aft the ship, as low down as possible, are a number of ballast tanks, which can be filled with or emptied of water as occasion requires to alter the trim of the ship. Extending over all holds there is a strong iron lower deck, about 8 feet below the upper deck, which is pierced with a hatch over each hold immediately under a corresponding hatch in the upper deck, for stowing and unstowing cargo. In the engine room there are six steam pumps, two of them bilge pumps, worked by the main crossheads, for clearing the engine room of water. For pumping out the ballast tanks there are two more, which have their own independent engines. The remaining two are for various purposes. Besides these there are several hand pumps on the upper deck. Having been built in 1885, the Ulunda is almost a new ship, and has been used principally as a cargo steamer, though she is provided also with a saloon and staterooms for a few passengers. She was on her way from St. John, New Brunswick, to Halifax, when during a thick fog she struck on Cowl Ledge, a reef between Bryer and Long Islands, on the southwest coast of Nova Scotia, about half a mile from the shore. The cause of the disaster was probably one of the strong tide eddies which exist in the Bay of Fundy, and which had set her in toward the shore. It was calm at the time, and she was making seven knots an hour; and, being close to the shore, leads should have been going in the chains. Had this precaution been taken, very probably she would have been able to stop or anchor in time to avert this catastrophe. There was no cargo on board, it being intended to ship one at Halifax for London. When ashore on this reef she was sold by public auction at Halifax, and fell to a syndicate of private individuals for £440. These gentlemen at once decided to raise her if possible, transport her into dock, and repair her. They commissioned Captain Kelly, of the Princess Beatrice, a ship then in harbor, to visit her and see what could be done for that purpose. He went with a hired crew to Annapolis, and from thence proceeded to the steamer by means of a tug, a distance of about forty miles. When they arrived they found the Ulunda with her head to sea, and her stern in only 2 ft. of water at low tide, with a list of 30 deg. to port and her foremast broken short off. At high tide the water flowed over the upper deck. On examination, the engine room was found full of water, which did not rise and fall with the tide, showing that it had been filled at high tide through its skylight. No. 3 hold was also full, but had a slight leak, which was shown by the water falling slowly at low tide and rising in the same manner at high water. The other three holds were hopelessly leaky. Upon investigation, it was decided to pump out the engine room compartment and No. 3 hold, and to make the iron lower deck watertight over the remaining holds. For this purpose three powerful pumps, with the necessary boilers, were obtained from Halifax, sent by rail to Annapolis, and then shipped on board a tug, from which they were hoisted into the Ulunda by means of the derricks on the mainmast. These were centrifugal pumps, capable of discharging 2,000 gallons a minute each. One was placed in the engine room, another with its suction in No. 3 hold, and when these two compartments were pumped dry, it was found that in No. 3 hold the leak was easily kept under, while in the engine room there was no leak at all. The third pump was not used. In the two foremost holds 2,000 large casks were then placed, and all the hatches over the leaky holds—Nos. 1, 2, and 4—were battened down, and made airtight with felt, pitch, tow, etc. A small hole was then made in Nos. 1 and 2 hatches, about 2 ft. square. When the tide had sunk its farthest, these two holes were closed and made perfectly airtight, in the same manner as the hatches had been. Before this took place the whole of the lower deck over the badly damaged holds had been prevented from bursting up by means of wooden shores, which were placed in rows about 4 ft. apart, and wedged firmly into position. The wood for the shores was obtained from Annapolis, and the casks from St. John. The ship went ashore on August 26, 1890. This work was commenced on September 8, and completed ten days afterward. The labor of repairing her could only be carried out at low tide, and only then with the greatest difficulty, as the decks were very slippery with weeds, etc., and inclined at an angle of 30 deg. Everything was ready for floating her off at high tide on the 18th, and the hatches were closed up on that day. She was raised off the rocks by the water rising and compressing the air in the two foremost holds, assisted by the buoyancy of the engine room and No. 3 compartments. At high water the bow was afloat, but she was aground by the stern. When, however, she was taken in tow by three tugs, she slowly slid down the reef and floated into deep water. One tug was placed on each bow, and the third was ahead. In this state she was towed into West Port, a distance of four miles, and there beached on a sheltered stretch of sand. The casks performed no part in floating the ship off, but were only there in case the great pressure of air should cause the escape of some of it, in which event all the space underneath the lower deck would soon have been occupied with water instead of air. These casks would then, of course, have served to displace a large amount of this water, and so keep her afloat. Luckily the deck did not leak, and the barrels were thus not instrumental in the raising. When beached the hatches were taken off, the casks removed, and a false deck was built about 7 ft. below the lower deck, and about 10 ft. above the keel. This was used as the bottom of the ship to take her round to Halifax, and was built in the following manner: A kind of iron platform, about 2 ft. wide, runs along the sides of the holds in the Ulunda for strengthening purposes, braced at intervals of 15 ft. by iron beams across the ship. On this was built the wooden deck. Beams for this deck were constructed of three 3 in. planks, and were laid down on the iron platform about 3½ ft. apart, and firmly wedged into the ship's side. On these beams a layer of 3 in. planks was placed in a fore-and-aft direction and nailed down; on this were three layers of felt, and on this again more planks were laid down in the same direction as before. The whole deck was then carefully calked and the sides made watertight with Portland cement. This deck only extended to the engine room bulkhead through the two foremost holds. It was prevented from bursting up by the pressure on the bottom of it, by means of shores, in the same manner as the iron deck had been served before. Shores were, therefore, connecting the three decks—the upper deck, lower deck, and wooden deck—this being done to equalize the pressure on the deck and the two permanent decks, and thus gain additional strength. extemporé No deck was built in either of the after compartments, inasmuch as No. 3 hold was kept clear of water as before by its pump, and in No. 4 the deck was not necessary. To have built one there, as in the two foremost ones, although it would have given a little more reserve of buoyancy to the ship, would have raised the stern higher than the bows, and so would have increased the upward pressure on the wooden deck, and thus have increased the liability to burst up. For the same reason, when raising the ship off the rocks, no compressed air was used in the after hold to lift the ship. The anchors and cables were in both cases transferred aft, for the same purpose, namely, to diminish the upward pressure forward. In the case of the wooden deck leaking, 200 of the same casks were placed between it and the lower deck in the foremost hold to retain some of the buoyancy of the forepart, which would otherwise be lost. No decks were built in the compartment before the collision bulkhead, as very little buoyancy was lost by that space being full of water, and all that was there was confined to that compartment by the bulkhead and the iron lower deck. While all these foregoing arrangements were being made for the exclusion of water from the inside of the ship, the engineers and firemen were employed clearing the engine room of some fifty tons of coal which had been washed from the open bunkers into the machinery by the sea, when the engine room was full and the ship on the reef. The greatest difficulty was experienced in digging out and excavating the engines from the coal and dirt, and still greater was the labor of cleaning all the mechanism and putting everything once more in an efficient steaming condition. But all was finished soon after the decks had been completed, and on October 12 she was ready for sea. On the following day she was floated off and started on her perilous voyage to Halifax, using her own engines, and making about five and a half knots an hour. Her steam pumps were by this time all ready for service to assist the big ones on deck in an emergency. She anchored once on her way round, at Shelburne, on the coast of Nova Scotia, arriving at Halifax at 1 p.m. on October 17. The trip round was a very anxious time for all hands, more especially when they were overtaken by a fresh gale in the Atlantic, for the forward deck was very liable to be burst up with the increased pressure on it caused by the pitching of the ship; also the rudder was entirely unable to bear any strain on it, because the lower part of the rudder post was unconnected with the stern post, part of the stern framing which connects the two having been broken off. Any heavy sea was therefore likely to carry away the rudder altogether, or the same accident might happen if the helm was put down too hard, rendering the ship unmanageable. She was placed in dry dock as soon as she arrived at Halifax, and it was not until then that the full extent of the damages, caused by the pounding on the rocks, could be fully realized. The first 20 feet of the keel had been torn completely out, and about 30 feet from the stern there was an immense hole, with the thick plates torn and bent like paper, the framing and stanchions being twisted into all sorts of shapes almost beyond recognition. Under the foremast the bottom of the ship was bent up in the form of an arch, having been raised 4 feet above its natural position, with an immense hole punctured on the starboard side, besides several smaller ones. Also the aftermost 20 feet of keel was torn and jagged, with several small holes in the skin, and the lower portion of the stern framing was broken off, leaving the rudder post to hang down unsupported at its extremity. It would strike one on looking at these gaping wounds that it would be nearly impossible to place the Ulunda in an efficient condition again, but the work of renewing the damaged plates is being carried out at a great rate, and in three months' time it is hoped that all the repairs necessary will be completed and the ship once more doing her duty. She has already cost her owners some $10,000, and $40,000 are estimated to cover all future repairs. The foremast was snapped off in a somewhat novel manner. She was pivoted on the rocks by her bows, and at high tide, the day after she struck, a breeze sprang up and turned her round; the tide sinking again, the whole weight of the ship came on the bottom of the ship where she was then touching, namely, just on the spot where the foremost was stepped, and right astern, leaving the center portion of the ship unsupported. This caused the foremast to rise, and it being held down by wire rigging, it snapped in several places, at the same time tearing up the shrouds from the deck. This accounts also for the arch-like bulge in the bottom at that spot and for the damages astern; also for the fact that Captain Kelly discovered the ship with her head to sea. Another incident happened when the ship was just rising off the rocks, which nearly resulted in a catastrophe. When the ship was just beginning to lift, the leak in No. 3 compartment was found to be gaining on its pump. A diver was at once sent down to ascertain the cause, and he found that a small hole, about 6 inches square, had been punctured in the skin, which until then had been kept tight by the rock that had caused it. It was necessary to close this leak at once. An iron bolt, which was screwed for a nut at one end, was obtained and passed through a strong piece of wood about 2 feet square. The inside of this board was cushioned with canvas and oakum, and it was taken down outside the ship by the diver and placed over the hole, with the feathered end of the bolt sticking through the hole; the diver was then sent down inside the hold, and with a nut set up the whole cushion until the flow of water was stopped. The leak was thus stopped which had threatened the arrangements for floating the ship with failure. It has been seen that the method of raising the Ulunda was very simple. She was floated off by the rising tide. If there had been only a small instead of an 18 foot rise, some other mode would have to have been adopted. No attempt was made to stop any of the leaks, except the one just stated, but a deck above the lacerations was made water-tight, and this, together with the sides of the ship hanging down, formed a kind of diving bell, the pressure of air in which, caused by the water outside, acting on this deck, being the principal means of buoying up the ship, assisted by the buoyancy of the two water-tight compartments. The deck afterward built was only necessary for the safety of the ship, she being able to float without it; but it would have been suicidal to trust the ship on the Atlantic in the state she was in when raised, since with any swell on, the compressed air would escape and its place be taken by water, the buoyancy necessary for keeping her afloat being thus lost. It only remains to be said that the risks run in steaming around to Halifax by herself were, as it was, very great, and had the wind and sea been less favorable, the undertaking would probably have proved a disastrous failure. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2004). Scientific American Supplement, No. 799, April 25, 1891. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/11649/pg11649-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

THE RAISING OF THE ULUNDA

Marrying and impact is nothing new. From dynamic and value chain traceability to the exploration of mechanisms like quadratic funding for public goods, the fusion of technology and impact continues to break new ground. web3 NFTs Now, there’s another innovation in the spotlight: . Born out of research by Protocol Labs started in the middle of last year, the new protocol answers the difficult question: How can we better align incentives to work on impactful work that might not have a business model or might be viewed as high-risk but potentially high upside? hypercerts Hypercerts propose a solution: Displaying impact on chain. As fractionalized, semi-fungible tokens, they enable the capture, definition, and representation of impact recorded on an immutable ledger. Such an improvement in transparency and evaluation structure paves the way for a better understanding of positive impact, fueling more funding and recognition. And, with a dash of retrospective funding magic, hypercerts’ ultimate goal is to empower humans to rather than mere intentions—by actually providing resources after the fact. fund tangible impact So, how exactly do hypercerts work, and how can they transform areas like carbon credits? Hypercert: The new public good primitive Leveraging , hypercerts’ creators defined a single hypercerts standard. Users can thus populate the tokens with unique information and create various classes of hypercerts—all managed within a single smart contract. This way, the hypercerts protocol represents a single, open, shared, and decentralized database for different impact funding mechanisms. ERC-1155 The philosophy is straightforward: Today’s economic systems don’t reflect what we value as humans, such as environmental and social well-being. Yet, we do have the power to design systems that guide our actions and reward the outcomes we desire. Hypercerts present an opportunity to establish structures that favor positive impact, support the funding of important causes, and implement transparent, trustworthy evaluation methods, effectively bridging the traditional divide between private and public sectors. NFTs have shown us that powerful and dynamic marketplaces can exist in the web3 world when the right tools are employed. By combining human values with large-scale structures, we can make a significant difference in our societies. Hypercerts facilitate coordination, laying the groundwork for various decision and funding mechanisms, including quadratic voting/funding, auctions, voting, bounties, grants, and more. And, while they don’t solve the coordination issues on their own, they do provide a solid foundation for these diverse strategies. The ability to “enable” makes hypercerts a great . In the context of web3, Francesco Renzi from Superfluid as a fundamental functionality upon which everything else is built. For example, in the automotive world, the wheel is a primitive that enables the construction of cars. So, introducing more primitives allows for the development of entirely new systems. public good primitive describes a primitive Therefore, hypercerts empower people to identify impactful work, leading to the creation of new building blocks for assessing community values, determining the most influential work, and, ultimately, enabling the development of novel utilities on top of these foundations. And for funders, hypercerts provide a convenient way to “put their wallet where their values are.” How do hypercerts work? Hypercerts serve as an interoperable data layer, creating a standardized method to capture key information about work intended to have a positive impact. Each token represents a claim detailing the scope of work performed by specific contributors within a given time frame and the scope of impact achieved during a specified period. Gitcoin has already retrospectively granted hypercert fractions to anyone who participated with at least $1 DAI in its Alpha Grants Round (in January) and Beta Grants Round (in April). All the metadata was stored on IPFS; the hypercerts protocol itself lives on Optimism (though you can also experiment with it on Ethereum’s Goerli Testnet). Each hypercert contains information about: The scope of work and its corresponding impact Time frames for both the work and its impact Contributors involved in the project Rights obtained through hypercert ownership Let’s look at how hypercert funding can work step by step Each effort involves various stakeholders: beneficiaries, contributors, prospective funders, retrospective funders, and evaluators. To receive funds, contributors develop an impact activity, create hypercerts defining the impact they aim to achieve and obtain funding from prospective funders. Upon minting the hypercerts, fractions are awarded to the prospective funders in—this is the initial, highest-risk stage. As the project progresses and creates impact, funders enter the scene to finance evaluators, who then assess the impact on beneficiaries. Evaluators create and publicize impact reports, allowing retrospective funders to compare the project’s goals with their results. This process can lead to the disbursement of award funds based on any further retrospective funding. At that point, the interesting thing is that hypercerts represent , enabling multiple evaluations to point to the same hypercert, increasing the variety of methodologies used, and allowing evaluations to differ over time. This, naturally, facilitates learning about the most effective impact assessment methodologies over time. completed work With an evaluation layer embedded into the semi-fungible “NFTs”, contributors must clearly define their goals and commitments beforehand, making evaluators’ jobs much easier. This separates the interests of projects and evaluators, as independent impact evaluators can remain neutral and are incentivized to develop a reputation for credibility. For hypercerts, ideal funders are then those who care about impact and seek to fund projects with credible impact claims and high-quality evaluations from reputable evaluators. For example, they could establish an impact evaluation pool, allocating a percentage of funding to reward impact evaluations for all projects under their consideration. If they choose to support an effort with retrospective funding, they can buy more hypercerts fractions from contributors and even the prospective funders who retain a fraction of their hypercerts. This mechanism has a crucial role: It allows contributors to work now, anticipating future cash flow for their positive impact, effectively "borrowing" from future funding. This approach incentivizes them to undertake public goods projects with uncertain yet potentially high impact and promotes a more efficient market by evaluating impactful outcomes post-hoc. We spoke to Carl Cervone, Holke Brammer, and Raymond Cheng, some of the key minds behind the hypercert protocol, about what happens at the very last step—once the contributors receive retrospective funding. Raymond shares that it’s the projects themselves that must decide how to use their funding best, often applying it to support ongoing operations and development. The way projects utilize funding will likely contribute to their overall reputation, as funding events on impact claims are expected to be a regular occurrence. According to Carl, retrospective funding supports various project needs, including compensating contributors, funding the next phase of work, or prospectively repaying backers who financed the work. The long-term goal is to encourage more people to do good work without waiting for grant proposals. Let’s talk carbon credits Carbon credits provide financial incentives for reducing greenhouse gas emissions by assigning a monetary value to the cost of polluting air. Since their trade began in 1997, they have become a key instrument for fighting climate change. But even today, carbon offsets continue to face significant challenges, such as a lack of standardization and methodology, low trust in credit quality, and fragmented marketplaces. But hypercerts could change that. Hypercerts offer a new perspective on carbon credits, democratizing the process and adding more rigor to evaluations. By addressing many of the Monitoring, Reporting, and Verification (MRV) challenges, they facilitate a more effective, trustworthy system for verifying and registering environmental impact. As Carl Cervone explains, hypercerts capture the work that was done, but there is still often still a need to evaluate the impact of the work. For example, we could create a hypercert for planting 10 trees. If you buy the hypercert, then you would own any impact that comes from our work. But someone would still need to measure how much carbon those trees removed. From water preservation to biodiversity, hypercerts force participants to fit their proposed impact into a framework, making it easier to incentivize or feel comfortable providing the funding. This allows contributors to better manage both capital and operating costs. For projects like tree planting, while the initial cost may not be high, the cost of maintaining the project can be significant. Hypercerts become a means to secure upfront funding to cover these costs and continue funding the sequestration process through the sale of additional fractions as the project starts generating impact. Yet, in order for that to happen successfully, there should be more transparency around how credits are created and where they are sourced from. Hypercerts can’t help us access data points to create this provenance and make sure that the data is verifiable. Imagine a small community starting a reforestation venture. They don’t have much capital, but with hypercerts, they can still secure initial funding for the project. As the trees grow and sequester carbon, the community sells more hypercert fractions, funding ongoing sustenance and further tree planting. This way, the community is incentivized to maintain the project for the long term, while backers can trust their contributions are making a real, measurable impact. It’s the retrospective funding piece that makes it really interesting. It encourages anyone to start working on a project—such as agroforestry—much like academic research. Let’s say a small-scale farmer or landowner wants to restore a degraded piece of land, knowing it has the potential to sequester huge amounts of carbon. They might think twice if they can't get money upfront or know for sure they'll earn carbon credits later. Without guaranteed upfront funding or the assurance of carbon credits, they may be reluctant to embark on this journey. With hypercerts, the landowner can begin the restoration work with the understanding that they will be able to generate and sell carbon credits based on the actual amount of carbon their project sequesters. As the project progresses and the land begins to recover, storing more carbon, the landowner can sell more fractions. If a contributor believes in their project’s potential, hypercerts can provide ongoing funding for maintenance and further restoration. Funders, on the other hand, can easily access the impact data of the project they fund, linking their funding directly to quantifiable carbon sequestration. This brings a more intuitive way to understand the information that’s being put in front of them. Simply put, hypercerts confront your impact goals with the results—so you can see all the information for yourself. So, where does this leave us? We believe that hypercerts do more than just legitimize carbon credits funding—they unlock projects previously deemed unviable due to a lack of initial funding. They represent a step toward a more inclusive, diverse impact dynamic, and we’re eager to see the ripples they create—in carbon and beyond. - By & Nicholas Edmonds Tereza Bizkova

Stories, News & Mentions about AGRYO

Agryo’s Stories on HackerNoon