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The Hitchhikers's Guide to PyTorch for Data Scientists

A complete guide to learn translations between any language pairs This blog is aimed at providing a step by step tutorial to learn to generate translations from a given language to any target language. The methodology we use for the task at hand is entirely motivated by an open source library a pyTorch implementation of which is available in python language, called Open-NMT (Open-Source Neural Machine Translation). It is designed to be research-friendly for deep learning enthusiasts to implement their ideas in the domain of machine translation, summarization, image to text conversion, morphology, etc. Though quite a lot of efficient translation systems by Google Translate, Microsoft, etc are existent, they are either not open-source or are closed under restrictive licence. Other libraries like models are existent for the purpose, but as research code. tensorflow-seq2seq is not only open-source but also provides greatly documented, modular and readable code for fast training and efficient performance of the models. Open-NMT We elaborate further, a detailed guide for setting up the library and using the toolkit for training your own custom translation system. This blog deals with generating translation for Hindi language from given English text. A Brief Overview of the Architecture of Open-NMT Open-NMT is based on the research by Guillaume Klein et al, found . here According to the Paper, the following details are revealed about its architecture: OpenNMT is a complete library for training and deploying neural machine translation models. The system is successor to seq2seq-attn developed at Harvard, and has been completely rewritten for ease of efficiency, readability, and generalizability. It includes vanilla NMT models along with support for attention, gating, stacking, input feeding, regularization, beam search and all other options necessary for state-of-the-art performance. The main system is implemented in the Lua/Torch mathematical framework, and can be easily be extended using Torch’s internal standard neural network components. It has also been extended by Adam Lerer of Facebook Research to support Python/PyTorch framework, with the same API. Setup of Required Modules The chief package required for training your custom translation system is essentially pyTorch, in which the Open-NMT models have been implemented. The priliminary step, of course is to clone the repository: OpenNMT-py git clone http //github. /OpenNMT/OpenNMT- OpenNMT- s: com py cd py Here’s a requirements.txt file to gather all the required packages: six
tqdm
torch>= git+https: future 0.4 .0 //github.com/pytorch/text Since PyTorch is has been continuously evolving, we recommend forking the PyTorch 0.4 version to ensure a stable performance of the code base. Run the following command to automatically gather pre-requisite dependencies: pip -r requirements.txt install Gather the Datasets The dataset comprises of a parallel corpus of source and target language files containing one sentence per line such that each tokens are separated by a space. For our tutorial, we use a parallel corpora of English and Hindi sentences stored in separate files. The data is gathered from various sources and combined. The data is then re-arranged so as to create a set of files as follows: : Training file containing 10000 English (Source Language) src-train.txt : Training file containing 10000 Hindi (Target Language) sentencestgt-train.txt : Validation data consisting of 1000 English (Source Language) sentencessrc-val.txt : Validation data consisting of 1000 Hindi (Target Language) sentencestgt-val.txt : Test Evaluation data consisting of 1000 English (Source Language) sentencessrc-test.txt : Test Evaluation data consisting of 1000 Hindi (Target Language) sentences sentencestgt-test.txt All of the above files are placed in the /data directory. We have used a limited amount of data for explanation and experimentation in this tutorial. However it is recommended to use a large corpora with millions of sentences to ensure a vast vocabulary of unique words for better learning and a . NOTE: close-to-human-translation Validation data is employed to evaluate the model at each step to identify the convergence point. It should contain a maximum of 5000 sentences typically. Here’s a sample showing how the text data is arranged in the corresponding files: Source Files :
They also bring out Tamil weekly newspapers.

They are hard — working people most them work labourers.
Tamil films are also shown cinema halls.
There are quite large Malayalees living here.

Target Files :तमिल भाषा में वे अनेक समाचार पत्र व पत्रिकाएं भी निकालते हैं .
ये लोग काफी परिश्रमी हैं , अधिकांश लोग मजदूरी करते हैं .
स्थानीय सिनेमा हालों में तमिल चलचित्रों का प्रदर्शन अक्सर किया जाता है .
मलयालम लोगों की बहुत बडी संख्या है . a number of a and of as in the local a number of Pre-Processing Text Data Execute the following command for pre-processing the training and validation data and extract features for training and generate vocabulary files for the model. python preprocess.py 
-train_src data/src-train.txt 
-train_tgt data/tgt-train.txt 
-valid_src data/src-val.txt 
-valid_tgt data/tgt-val.txt 
-save_data data/demo python preprocess -train_src data/src-train -train_tgt data/tgt-train -valid_src data/src-val -valid_tgt data/tgt-val -save_data data/demo .py .txt .txt .txt .txt Training the Translator model The chief command for trianing is really simple to use. Essentially, it takes as input, a data file and a save file. A summary of the default model used is as follows: NMTModel(
  (encoder): RNNEncoder(
    (embeddings): Embeddings(
      (make_embedding): Sequential(
        (emb_luts): Elementwise(
          ( ): Embedding( , , padding_idx= )
        )
      )
    )
    (rnn): LSTM( , , num_layers= , dropout= )
  )
  (decoder): InputFeedRNNDecoder(
    (embeddings): Embeddings(
      (make_embedding): Sequential(
        (emb_luts): Elementwise(
          ( ): Embedding( , , padding_idx= )
        )
      )
    )
    (dropout): Dropout(p= )
    (rnn): StackedLSTM(
      (dropout): Dropout(p= )
      (layers): ModuleList(
        ( ): LSTMCell( , )
        ( ): LSTMCell( , )
      )
    )
    (attn): GlobalAttention(
      (linear_in): Linear(in_features= , out_features= , bias= )
      (linear_out): Linear(in_features= , out_features= , bias= )
      (softmax): Softmax()
      (tanh): Tanh()
    )
  )
  (generator): Sequential(
    ( ): Linear(in_features= , out_features= , bias= )
    ( ): LogSoftmax()
  )
) 0 20351 500 1 500 500 2 0.3 0 20570 500 1 0.3 0.3 0 1000 500 1 500 500 500 500 False 1000 500 False 0 500 20570 True 1 train.py - python /demo -save_model demo-model data data The above command will run a default model, comprising a two layer LSTM possessing 500 hidden units for both, the encoder and the decoder. To specify utilization of your GPU for training, specify the -gpuid argument in the above command (say -gpuid 1 for specifying usage og GPU 1). Typically, the default model goes on till 100000 epochs, such that a check-point is saved after every 5000 epochs. So if your model converges and the validation accuracy reaches a stable point earlier, you can stop further training and use the previously saved checkpoint. Translate your own Data The following command may be executed to perform an inference step on unseen text in the Source language (English) and generate corresponding translations predicted: python translate -model demo-model_XYZ -src data/src-test -output pred -replace_unk -verbose .py .pt .txt .txt This will generate the translated output and store the predictions into a file namedpred.txt. The model was trained for 10000 epochs on a NVIDIA GEFORCE 2GB GPU. Training on a CPU will require a very high computational cost, hence it is recommended to use a high end GPU for training the model with a large amount of data at a faster rate. Sample Predictions of the Model Shown below, are couple of examples for the Hindi translations generated for corresponding English sentences after training the model. Trees are capable absorbing more carbon dioxide, 
thus maintaining equilibrium the air composition of of in PREDICTED : पेडों में कार्बन डाईआक्साइड के बुरे लोग 
इस प्रकार पेड - पौधे का प्रयोग करने के लिए मौजूद हैं. He has hope that the gods will good things the heavens, 
upon them throw from PREDICTED :वे उमीद है कि वे घर से कुछ नहीं बची हैं The Buddhist temple , 
the Dalai Lama Palace and dispensary Tibet are tourist attractions here of PREDICTED :यहां का बौद्ध मंदिर दलाई लामा का आवास तथा तिब्बती औषधालय स्थानिय लोगो में मिलता है . He lets the hair grow long.
PREDICTED : वह अपने बढा लेता है . As seen above, the predictions are not good enough yet with less training data to be used for any real time translation. For performing translations close to real world, the model has to be trained on on a large vocabulary and about a million sentences, which will parallely involve a lot of computational cost in terms of hardware requirements and training time. Evaluate your Trained Model Bilingual Evaluation Understudy Score The Bilingual Evaluation Understudy Score, or BLEU Score, refers to an evaluation metric for the purpose of evaluating Machine Translation Systems by comparing a generated sentence to a reference sentence. A perfect match in this comparison results in a BLEU score of 1.0, whereas a complete mismatch results in a BLEU score of 0.0. The BLEU Score is a universally adapted metric for evaluating translation models as it is independent of language, simple to interpret and has high correlation with manual evaluation. The BLEU score was proposed in a research conducted by Kishore Papineni, et al. “ “. BLEU: a Method for Automatic Evaluation of Machine Translation The BLEU SCore is generated after counting n-grams in the candidate translation matching with the n-grams in the reference text. Word order is not taken into account in this comparison. So how would we define a n-gram? Let’s say a 1-gram or uni-gram would mean each individual token and a bi-gram would represent each pair of word. The Code for calculating BLEU Scores, given your predicted candidate file and a reference file given in the GitHub repository, the link to whic is provided at the end of the blog. Here’s how we run the code to evaluate the model: python calculatebleu .py "pred.txt" "tgt-test.txt" Where pred.txt is our candidate predicted translation file and tgt-test.txt is the file containing the actual translations in the target language. Since our data vocabulary generated with 10k sentences consists only of a few thousand words, the BLEU Score we get on our prediction is quite poor (0.025). : Since our primary aim is focussed at elaborating on the usage of Open-NMT, we use only a small dataset, which is why the evaluation of our predicted translation results is a poor BLEU Score. A BLEU Score around 0.5 implies a decent translation. Increase the training vocabulary manifold by adding several thousands of more examples to improve the score. NOTE However Open-NMT allows us to train our own custom translator models between any pair of languages and is very convenient to use. The Code for generating the BLEU Score and the datasets used in training our model have been provided . here If you have any queries or suggestions, I would love to hear about it. Please write to me at abhishek.narayanan@dataturks.com.

Neural Machine Translation: Using Open-NMT for Training a Translation Model

If you've been in the digital marketing industry for some time now, it should come as no surprise that many SEO trends continue to change year after year. Gone are the days when you could use a single keyword tool and a bunch of keywords for an to work. Nowadays there’s no cookie-cutter approach to SEO. It’s completely based on the dynamic SEO trends — relying on how people want to search and consume content. So here's a look at some of the SEO trends to watch out for in 2022, as well as some tips on how you can prepare your SEO strategy this year to further increase your authority and rankings. SEO strategy 5 SEO Trends to Include in Your Online Strategy in 2022 Voice Search Optimization Will Be the Next Big Thing Voice search is becoming more popular among users as they want to interact with their devices without being forced to type or tap away on their keyboards. Voice search queries will likely become even more popular as more people start using smart speakers such as Google Home and Amazon Echo Dot at home. In fact, prefer voice searches over typing into the search boxes. This presents an opportunity for brands to optimize their websites for voice search queries, ranking higher in SERPs when users speak their queries into a search box on their smartphones or smart speakers. 71% of consumers As more people start using their devices hands-free while driving or doing other activities, it's important that your site can be easily accessed via voice search devices such as Google Home or Amazon Echo. And because these devices are getting smarter all the time, they'll be able to answer more complex questions than ever before – making them an increasingly popular way for consumers to interact with brands online. By ensuring your site displays well on these devices, you can gain an edge over competitors who may not be fully optimized yet. Mobile-First Websites Will Continue to Dominate the SERPs It's no secret that more people are using mobile devices than ever before — so much so that mobile traffic now accounts for more than ! To keep up with this SEO trend, Google announced that it would start ranking websites based on their mobile version rather than the desktop version. half of all internet traffic Google announced mobile-first indexing back in 2017, which means websites that have been built with mobile users in mind will receive priority when Google crawls their pages for content and links. Sites that haven't been optimized for mobile won't be penalized outright — at least not yet — but they may not rank as highly as those customized for mobile users.
This trend shows no signs of slowing down, so it's vital to ensure that your website is optimized for mobile users by 2022. The best way to ensure your website is mobile-friendly is to use one of the many online tools to test your site for speed and page load time. It's also wise to make sure that you're using responsive design so that your website looks good on any device. Integrating Social Media for Relevancy Is Becoming a Thing We've seen social media integration in SEO before — like Facebook's Open Graph protocol and Twitter Cards — but this is one of the SEO trends that's really starting to heat up.
Some sites have been using social media data to target their content for years now, but this is only the beginning. In 2022, more companies will integrate social media into their websites to make them more relevant and engaging for users who visit from different sources. It's no secret that video content is becoming more popular than ever — which means it's time to pay attention to video SEO! Video marketing is a great way to attract new customers, increase customer engagement, and share your brand message with the world — but if you don't optimize your videos properly, they won't rank as well in search engines like Google or Bing.
Many businesses are already using videos to increase their SEO, but they are still not using them optimally. Video Optimization for SEO Is Going Mainstream In 2022, we expect that a lot of businesses will start using videos as a way to optimize their SEO. This is because Google has started prioritizing video content over text on its search results page. So if you want your business to be seen, you should start creating more video content that can be optimized for SEO, especially if your business sells products or services online. SEO is a long game and nobody can afford to play it with a single strategy. While some companies may thrive in the short term, they will likely not be able to beat their competitors over time. The best way to do that is by tailoring your content based on specific user needs, wants and behaviours. SEO Will Become More Personalized As voice search becomes more popular, SEOs will need to shift their focus from keywords to intent-based searches. This means that instead of optimizing for specific keywords like "buy baby stroller" or "How do I use my iPhone camera effectively?" SEO specialists will instead optimize for "help me choose between these two strollers" or "Can you help me turn off my iPhone timer?" Wrapping Up The SEO landscape is always changing, so it can be difficult to track what's happening. If you want to stay ahead of the curve and ensure your website gets the best results possible, then you need to include these SEO trends in your 2022 online strategy to increase your exposure and, thereby, revenue,

SEO Trends to Watch Out for in 2022

Logistics is a sector where mistakes usually cost thousands of dollars at best and client relationships at worst. Problems with trucks, car accidents, theft, heavy unexpected traffic—over the years, I’ve learned the hard way how to be forearmed for every situation and minimize risks. Here are some steps that I outline and follow to perform swift operations. Even with the boom of AI systems, the human factor still remains crucial. Finding the Real Problem: If something doesn’t work—take your time to identify problems. Don’t blame others, but collect facts and analyze the whole picture. Whether it's breakdowns in communication, shipment delays, or inefficiencies in processes—find those underlying reasons. Remember, what lies on the surface might be a consequence, not the cause. Ask yourself and your team the right questions, conduct analysis, and ask your superior if needed. Do your best to pinpoint the problem and create the best solution to get this issue out of the way, and brief your team on steps to follow next time it occurs. Or keep it in your books—keeping track of your solutions is an important task, saving you time by not reinventing the wheel the next time something similar occurs. Analyzing Data: Check key performance indicators like on-time delivery rates, inventory turnover, and transportation costs to ensure everything stays on track—literally and figuratively. Use data metrics to gain insights into your operational process, and check what's off track. This way, if a problem occurs, you’ll see what caused it and know the underlying reasons precisely. And if you follow the previous step, you’ll check your book for ideas on how to solve it. Using Team Effort: Logistics is about collaborative effort, and practical problem-solving needs a team approach. Be mindful throughout your work, and foster a culture of open communication by creating a safe space for your employees to share, brainstorm, and experiment. When you face problems, you could significantly leverage the diverse expertise within your company to solve challenges. Cross-functional teams bring together experts with different skill sets and perspectives, which leads to great solutions. Promise you’ll never underestimate your team. Even the youngest, fresh perspectives can shed new light on business processes and offer surprising insights. Adapting: You never know what tomorrow brings, and it’s crucial to be able to adapt your strategy. Whether it’s a delayed shipment, weather advisories, new laws, or rules—have a plan B, C, and D to remain flexible and open to alternative approaches. My team and I sometimes play this game where we try to come up with new solutions to common issues in our sector or try to solve a problem that happened with our competitors. It helps to keep an eye on the prize and be prepared. You can't afford to say no to a customer or fail to deliver. Improving: Unfortunately, problem-solving is not a one-time thing but rather an ongoing process: Monitoring outcomes. Soliciting feedback from team members. Evaluating the effectiveness of your solutions helps refine your approach over time. This allows us to stay one step ahead and support our operational excellence. I’d also recommend exploring new solutions by attending professional events and talking to experts from your field to know how others are coping with the same problems. Connect with companies in other regions who are not your straight competitors to pick each other's brains. Embracing Technology: Technology is everything, and it plays a significant role in today's logistics operations. From inventory management systems to route optimization software, it streamlines processes and increases business efficiency. I believe it’s important to check what technological advancements are available in the market and, after carefully examining them, integrate them into your operations. This can help optimize your problem-solving capabilities. Logistics operations are not rocket science, however, it sometimes is if you don’t play your cards right or unforeseen accidents occur and you don’t have a plan B up your sleeve. Here, I've shared my advice on how you can use simple steps that don't require extra costs, people, or other resources, but manage the risks of time that you can take to think about how to improve your processes to make the most seamless and uneventful deliveries.

Mastering the Operational Logistics: Solving Problems When Client Relationships Are at Risk

Traditional logistics services are unable to cater to the increase in demand for efficiency and accuracy. Hence, AI solutions must be explored for cost optimization and resource usage. They must also at the same time ensure speed and precision. The success of AI largely depends on the accuracy and quality of data advancements. In essence, data annotation acts as the bridge enabling machine learning models to comprehend and address real-world issues. Over the years, data annotation has played a tremendous role in boosting growth across industries. Companies employ trained professionals to annotate data for their clients. Modern technologies utilize artificial intelligence (AI) and data annotation to cut costs and acquire customers. Data annotation is also facilitating rapid growth in the transportation industry by assisting machines develop an awareness of the world as it exists. The popularity of online shopping has also led to a rise in demand for logistics services by consumers. Both AI and data annotation have the capability to redefine each element of the through automated warehouse management, intelligent delivery route planning, predictive maintenance, and demand forecasting. So, let’s take a look at each of these elements. logistics industry Automated Warehouse Management: AI inventory management systems assist in better inventory decisions through the automation of several manual processes. Since manual processes like data entry and manual recording of items are very time-consuming and prone to human error, they may not offer real-time insights into inventory levels and demand patterns. AI is also useful in analyzing vast volumes of data and offering insights into inventory levels, demand, and supply in real time. It includes data analysis from point-of-sale items, historical sales data, and supplier data. It is also used for predicting demand for products and assisting businesses in adjusting their inventory levels to prevent overstocking or understocking. This assists retailers in bringing down costs linked with inventory stocking and improvement of order fulfillment times. Intelligent Delivery Route Planning or route optimization:  This is a major component of logistics as it establishes the best route for goods to be transported from one point to another. Data from different sources like GPS tracking, weather forecasts, and traffic sensors are used for determining the best route using AI algorithms. It can be used for optimizing routes as per weather conditions. The use of AI in businesses helps in time and cost saving enhancing the overall delivery experience. Predictive Maintenance: This is an important area in AI as it transforms the logistics industry by preventing downtime which is expensive leading to delays and loss of revenue. It utilizes data analysis and machine learning algorithms for predicting when maintenance is needed and assists logistics companies in identifying issues prior to their occurrence. AI is used to analyze data and identify patterns for predicting maintenance work including equipment repairs or replacement. AI assists businesses in identifying issues prior to them becoming serious and taking precautionary measures to limit business disruption. Demand Forecasting: This is an important part of supply chain management in e-commerce businesses as it assists them in optimizing inventory, improving supply chain planning, and limiting the risk of stockouts and waste. Moreover, it’s a complicated and challenging task for businesses dealing with a wide range of products and market segments. AI-backed demand forecasting assists eCommerce businesses in predicting sales and optimizing inventory levels resulting in enhanced supply chain efficiency and customer satisfaction. All in all, AI helps in transforming the manner in which businesses operate through the use of AI for data analysis and predicting future demand. Conclusion AI brings great opportunities for automating routine tasks, enhancing efficiency, and limiting costs. The implementation of AI in logistics assists businesses in reaping rewards and staying ahead of the competition. The continuing developments in AI have opened up the doors for endless possibilities. These include data integration and compatibility, scalability, accurate forecasting, bridging gaps in skills and knowledge, improving efficiency, etc.

The Vital Role Data Annotation Plays in the Logistics Industry

The rise of e-commerce has been remarkable over recent years, and it shows no signs of plateauing. As this sector expands, the demand for streamlined delivery systems also grows significantly. Central to this demand is the idea of last-mile delivery, a term initially used in the telecom sector and then adopted by logistics and supply chain management. Last-mile delivery is the last step in the delivery process. It's the journey a product makes from a distribution center or facility to the final destination, usually a customer's home. Even though it's the concluding phase, last-mile delivery can be the most intricate and costly in the entire supply chain. Thus, it accounts for a substantial part of the total delivery cost. Factors such as traffic congestion, misaligned delivery timings, and increasing customer demands for speed and flexibility contribute to it vastly. Considering the influence of these obstacles on operational proficiency and customer contentment, companies are constantly exploring innovative strategies to make this process more efficient and cost-effective. With technologies ranging from artificial intelligence to self-driving vehicles, last-mile delivery is undergoing a transformative phase, becoming more streamlined and customer-focused. Challenges in last-mile delivery While last-mile delivery presents an opportunity for e-commerce businesses to distinguish themselves from competitors, it also has a unique set of its own troubles. One of them is meeting the growing customer expectations. Today's consumers demand not only speedy delivery but also the flexibility to alter delivery times and locations, which can complicate logistics planning. Plus, customers often expect real-time updates on their orders, which requires sophisticated tracking systems. Geographical issues also pose serious challenges. Goods delivery to outlying suburban and rural locations, where residences are widely dispersed, can be both time-intensive and costly. Meanwhile, deliveries in cities face their own unique challenges such as heavy traffic, scarce parking, and restricted access, which all can cause delays. Cost management is another big problem. With fuel, labor, and vehicle maintenance costs steadily rising, keeping last-mile delivery affordable without compromising on efficiency is a balancing act. Moreover, the environmental footprint of logistics has gained significant public attention, regarding emissions and sustainable practices. Safeguarding the delivered goods, especially when handling high-value or perishable items, is another aspect companies must handle. And finally, scaling last-mile delivery operations to accommodate increasing volumes of orders while maintaining the same level of service quality is a constant struggle for many companies. Handy tech solutions Innovative technologies have the potential to reshape last-mile delivery, helping to address the challenges we've outlined earlier. Today, there’s an array of technological options that a business can integrate into its day-to-day operations. Autonomous Vehicles Several companies are already deploying drones for delivery. In the US, Amazon, with its Prime Air service, plans to deliver packages up to five pounds in 30 minutes or less using unmanned aerial vehicles. Alphabet's Wing has also received regulatory approval to start drone delivery services in several regions of Australia, Finland, and the US. Ground robots are another nice development. For example, Starship Technologies has deployed its delivery robots in multiple cities worldwide, including the US, the UK, and the company’s homeland of Estonia. They operate autonomously 99% of the time and can carry items within a 4-mile radius. The company operates AI and Machine Learning Route optimization software, such as Routific or ORTEC, use AI and machine learning algorithms to calculate the most efficient delivery routes. These systems consider various factors, such as traffic, weather conditions, and package destinations, to reduce travel time and costs. These advanced systems evaluate a lot of factors when plotting routes. They take into account real-time traffic data, weather conditions, package destinations, and even the capacity of the delivery vehicle. Importantly, these systems are dynamic. They continuously learn and adjust to changing conditions, ensuring the most up-to-date information is used for decision-making. For instance, if there's a sudden traffic jam due to an accident, the system can quickly re-route the delivery vehicle to avoid delays. Internet of Things IoT technology is being used to create smart logistics networks. Companies like Roambee provide real-time visibility into the delivery process through sensor data. Their devices monitor location, temperature, humidity, and more, providing crucial information for deliveries, especially for sensitive goods. For example, pharmaceutical products or perishable foods need to be kept at specific temperatures, and real-time monitoring allows companies to ensure these conditions are maintained throughout the whole delivery journey. Moreover, IoT-enabled predictive maintenance can alert companies about potential issues with their delivery vehicles before they result in costly downtimes. This information, derived from continuous monitoring and data analysis, allows companies to manage their fleet, proactively. Blockchain Technology VeChain, a blockchain platform, is an excellent example of using blockchain in logistics management. This tech enhances transparency and security by offering a full view of the supply chain. So, consumers can use VeChain to verify product authenticity, and businesses can improve logistics processes with it. Visibility provided by such services helps companies identify any bottlenecks or inefficiencies in their logistics network, which leads to more streamlined operations and enhanced performance. Plus, the security of blockchain technology means that this data is less susceptible to tampering or fraud. Real-life examples Many companies have embraced innovative technologies to improve their last-mile delivery operations. Here are a few examples from worldwide leading businesses. FedEx This global delivery provider has been exploring autonomous delivery solutions for some time, and one result is Roxo, the SameDay Bot. It’s a delivery robot designed to transport smaller shipments, specifically in urban environments where traffic and parking can be tricky. Roxo can navigate pedestrian paths and even climb stairs, which makes it an efficient option for quick, local deliveries. DHL Another logistics giant has leveraged AI and machine learning to optimize their delivery routes. The company has reported reduced delivery times, fuel costs, and CO2 emissions. Furthermore, DHL uses IoT for predictive vehicle maintenance, which allows them to improve efficiency by reducing unexpected downtime. Domino's Pizza The major fast food chain has partnered with Nuro, a leading autonomous delivery company, to use their autonomous vehicles for pizza delivery in the US. By providing customers with a unique pin to retrieve their order from the vehicle, Domino's has streamlined its delivery process and enhanced customer experience. Zipline Zipline is a company that uses drones for last-mile delivery of medical supplies. It operates in hard-to-reach places like rural Rwanda and Ghana, where conventional delivery methods just don’t work. By deploying drones, Zipline ensures that hospitals and health centers receive necessary supplies promptly. Potential problems Despite all these advantages, there are potential challenges that businesses need to navigate while using new tech solutions for their last-mile delivery. Regulatory issues may be a significant roadblock, especially concerning autonomous vehicles and drones. Different regions have various rules regarding unmanned vehicle operation, and compliance is important here. Cybersecurity is another concern. With businesses growing increasingly dependent on digital solutions, the threat of cyberattacks grows high. It's crucial to have strong security protocols to protect sensitive data, like customer details and payment information. The initial cost of these technologies can be significant. Deploying state-of-the-art AI systems, autonomous vehicles, or blockchain solutions requires a sizable investment. Some businesses, especially smaller ones, might find these upfront costs too much. And while some customers appreciate the convenience and speed these technologies offer, others may have privacy or safety concerns, particularly around drone deliveries and data sharing. Lastly, technical issues and the need for skilled personnel to manage these new technologies can also present challenges. Companies need to ensure they have the necessary technical expertise on hand to implement and operate these solutions. What lies in the future Looking ahead, new technologies are set to continue transforming the last-mile delivery sector. Innovations such as hyper-local fulfillment centers and advanced predictive analytics could lead to even faster and more efficient deliveries. We might also see wider adoption of blockchain for logistics, enabling even greater transparency and security in transactions. As technologies mature, we will likely witness increased cooperation between regulatory bodies and businesses to create supportive frameworks for innovations like drone delivery. This could make last-mile delivery even more efficient. The evolution of e-commerce logistics depends on our willingness to adopt these innovative technologies. Given the clear benefits — enhanced efficiency, cost-effectiveness, and customer satisfaction — it appears that businesses should be keen to invest in these advancements and utilize them. However, embracing these solutions should also come with a degree of caution. It's essential to navigate potential challenges, such as regulatory hurdles and cybersecurity risks, with due diligence. The right balance will allow businesses to optimize their last-mile delivery services effectively while maintaining customer trust.

Innovative Technologies for Last-Mile Delivery in E-commerce Logistics Scaling

are everywhere. They have become indispensable in our everyday lives. They are also ubiquitous in various industries, notably e-commerce logistics. Mobile applications Nowadays, apps are redefining how e-commerce is conducted. One of the main reasons for their effectiveness is that these apps help immensely in attracting personnel. The traditional barriers tied to experience and competence levels are significantly diminished. This is, in a large part, because a mobile app introduces a rigid workflow, making it difficult for users to stray from prescribed tasks. Furthermore, these applications enable a high level of oversight, so all activities carried out by the user are thoroughly monitored. Apart from that, they assist in all areas: from product browsing to delivery tracking. They act like the bonding agent that links customers, retailers, and delivery services, allowing instant information exchange and effortless cooperation. For businesses, they enhance operational efficiency, improve customer relations, and provide a competitive advantage. For consumers, they offer a swift, engaging, and user-friendly interface for satisfying their shopping desires. How mobile apps influence e-commerce make different parts of the business, like finding products and delivering them, a lot easier thanks to their simple and clear interfaces. Mobile apps On the frontend, they deliver an engaging and personalized user experience. Advanced algorithms analyze user behavior to recommend products, tailor promotions, and facilitate personalized interactions. Mostly, apps are designed for easy navigation, quick checkouts, and secure payment processing. Many also offer features like wish lists, product comparisons, and customer reviews. On the backend, mobile applications are instrumental in managing inventory, processing orders, handling customer inquiries, and tracking deliveries. They help in making various office tasks more automatic and precise, reducing mistakes and making sure the operations run smoothly. In addition, these apps keep a bunch of helpful information that companies can use to tweak their operations, guess what their customers might want next, and make wise decisions about what's to come. Also, a good many of mobile apps have built-in tools for accessibility. These include voice-enabled search functions, speech synthesis, and the option for high-contrast displays. Such features guarantee that e-commerce platforms cater to the needs of all customers, including those with visual, auditory, or motor difficulties. What's their role? From what we can tell, mobile apps offer a bunch of tools and features that simplify and speed up a lot of operation parts, like taking care of inventory, tracking orders, and sorting out delivery systems. Inventory Management Applications like TradeGecko and Vend offer robust solutions here. These apps synchronize data across multiple sales channels, making it easier to manage stock levels, predict demand, and prevent both overstocking and stockouts. Features such as real-time inventory tracking, automated reordering, and reporting help businesses maintain optimal inventory levels and streamline their supply chain operations. Order Tracking For order tracking, mobile apps have significantly improved transparency and communication between businesses and customers. Applications such as AfterShip and Route offer real-time tracking and automatic updates on shipment progress, giving customers clear visibility of their orders' status. These platforms also allow businesses to customize their tracking pages, reinforcing brand identity and improving customer experience. Delivery Systems Mobile applications have revolutionized the way businesses coordinate their deliveries. Apps like Onfleet and Bringg provide sophisticated dispatching, route optimization, and driver-tracking features. They facilitate efficient delivery operations, reducing costs, improving delivery speed, and, as a result, enhancing customer satisfaction. Mobile apps in scaling One of the most critical challenges in e-commerce is scaling logistics to accommodate business growth. This requires managing larger volumes of orders, delivery routes, inventory, and customer communication, all of which can quickly become complex. Mobile applications help the scaling process. In a sense, they can grow along with a business. As the volume of transactions increases, mobile applications can handle the increased data and complexity without the need for significant investments in new hardware or infrastructure. They enable businesses to manage growth without disrupting existing operations, and their modular nature allows for additional features to be integrated as needed. For example, ShipBob, a logistics platform designed for e-commerce businesses, faces the challenge of managing increased order volume, as business operations grow. ShipBob offers a unified platform where companies can manage orders from various sales channels. The app provides inventory management across multiple warehouses, order management, and even advanced analytics to improve decision-making. With ShipBob, businesses can scale their logistics seamlessly without the headache of dealing with increased complexity. Similarly, applications like EasyPost allow businesses to manage an extensive network of carriers. As businesses expand geographically, they need to work with more delivery services. EasyPost offers API solutions that integrate with numerous carriers, making it easier for businesses to ship worldwide without getting bogged down by the complexity of managing multiple relationships. Sellbrite and Zoho Inventory provide further support for scaling logistics. Sellbrite facilitates multi-channel selling, allowing businesses to list and sell products across numerous online marketplaces from a single interface. This centralized control simplifies the management of increased sales channels as businesses grow. Zoho Inventory, on the other hand, is a robust inventory management solution that can manage the growing complexity of stock control. It handles tasks like inventory tracking, order fulfillment, and also integrates with multiple online sales channels, keeping all systems synchronized as a business scales. Who uses them, and how? ASOS This British online fashion retailer also made great progress in scaling its logistics with a mobile application. They integrated their operations with Metapack, a delivery management software that offers a range of features, including track-and-trace functionality, returns management, and delivery personalization. With Metapack's capabilities, ASOS was able to enhance its delivery process and manage a greater volume of orders. Stitch Fix Stitch Fix, an online personal styling service, used mobile applications to scale its operations and deliver personalized style boxes to customers across the United States. They used an app called Style Shuffle, which allows users to rate clothing and accessory items, thus helping the company gather data about customer preferences. This helped the company streamline its inventory management and improved the efficiency of its operations. Instacart Instacart, a North American leader in online groceries, turned to mobile apps to grow the scale of its operations. They developed their in-house app that connects customers, personal shoppers, and grocery stores for efficient delivery or pickup of groceries. This allowed them to manage a complex logistical challenge of coordinating between multiple stakeholders. As a result, Instacart became able to handle a growing volume of orders and expand their operations. The Home Depot The Home Depot, a leading home improvement retailer, provides another example of successful logistics scaling through the use of mobile applications. Facing increasing demand online, they realize the need to optimize their e-commerce logistics to handle the surge in orders. The company turned to mobile tech. The app they used was Roadie. It’s an Uber-like system that connects businesses with local drivers who can deliver goods on routes they were already taking. The Home Depot turned to Roadie to help make its delivery process smoother and deal with more orders. The company also created their own app that helped customers keep tabs on their orders, find things in stores, and even use augmented reality to see what products would look like in their homes. The payoff was a big boost to The Home Depot's e-commerce operations. Conclusion So, for e-commerce, mobile apps enhance clarity and speed, which results in an improved shopping journey for consumers, as well as businesses becoming able to work more efficiently. It's easy to expect that, with time, apps will gain an even bigger role in e-commerce logistics. We’ll probably be seeing a constant stream of more and more specialized apps, designed to offer even more help. Likely, they will introduce new methods to boost operational efficiency, cut costs, and amplify customer satisfaction. As these changes come, businesses that can use mobile apps well will lead the pack, ready for the opportunities and challenges the future brings. Try to be one of them.

Mobile Applications and their Impact on E-commerce Logistics Scaling

For 3PL companies, optimizing supply chain coordination and improving performance offers significant growth opportunities. That’s why, to meet all the market demands and deliver exceptional customer experiences, logistics firms are transitioning to the that combines key operations to handle complex logistics effectively. In this article, I'll explain the integrated approach and how to establish a functional logistics system. integrated logistics model What Does the Integrated Logistics Approach Mean? Integrated logistics is a business model that emphasizes coordinated efforts across all departments. It involves uniting a company's management activities and components to better product fulfillment, delivery, and customer satisfaction. supply chain In the integrated approach, including material procurement, production, storage, distribution, transportation, marketing, and delivery. Resources, technology, and operations are linked up in a solid system. every aspect of the supply chain is interconnected, The concept gained popularity as a response to such logistical challenges from omnichannel retail as: a need for better process regulation and optimization. increased customer demands and expectations. necessity for accelerated fulfillment and 24-hour deliveries. provides organizations with the necessary for solving supply chain disruptions and minimizing risks. By implementing this model, companies connect logistical processes like order processing, distribution, customs clearance, forwarding, and reverse logistics. Integrated logistics flexibility and agility What Are the Benefits of Integrated Logistics? Improved Operational Efficiency Integrated logistics encourages regular assessment and upgrade of all support elements, such as product support and customer care that drive operational efficiency through —including routine maintenance and training courses for procedure fine-tuning. recurring evaluations In-depth testing and analysis enable improvement recommendations, reducing error-prone systems and customer dissatisfaction. Cost Savings Logistics impacts eCommerce business costs. A streamlined approach to logistics can cut expenses at various stages, from procurement and shipping to warehousing and delivery. Collaboration and shared information . simplify cost monitoring and waste reduction The key benefit of integrated logistics is that the model involves fewer parties, ensuring competitive pricing, identifying inefficiencies, and creating cost-saving opportunities. As a result, an integrated logistics model provides a higher profit margin and reduced operational costs. Upgraded Customer Service High customer satisfaction depends on the provider’s ability to anticipate and meet their needs and expectations. Integrated logistics manufacturing, management, technology, and marketing to optimize product design, features, quality standards, and packaging in line with customer expectations. combines Flexibility and Resilience Flexibility and resilience are necessary during supply chain disruptions. Integrated logistics fosters supply chain agility through end-to-end visibility and team collaboration. By unifying various processes, integrated logistics solutions and tools (automation, design interfaces, EDI exchanges, IT, and ) to unexpected changes, delays, and speed fluctuations. IoT enable effective responses Data and Technology Integration Efficient supply chain management as well as timely order deliveries rely on data for efficiency and informed decision-making. Integrating logistics data and systems consistency, and accuracy, positively affecting customer service, internal operations, and marketing. , improves data integrity How to Get Started With Integrated Logistics? Before getting into the technical aspects, it's important to adopt the right mindset for any innovation or change and outline the fundamental elements of integrated logistics before delving into the technical side. To create an integrated logistics system that delivers a great experience for both employees and clients, business owners and stakeholders should focus on these essential components: A company needs established and dependable routes by air, water, and land to ensure timely deliveries. The diversity of routes and alternative options, as well as cargo transportation methods, play an important role in achieving 100% fulfillment. Transportation: Effective client support and communication are fundamental to the success of integrated logistics. Handling requests, inquiries, and suggestions requires a proactive and qualified support team committed to problem-solving rather than offering superficial responses. Expertise: Every essential asset must be available throughout the supply chain, with the logistics network accommodating a multimodal approach. The readiness for various performance scenarios directly affects the entire supply chain resilience. Infrastructure: Close communication with customers, feedback collection, and understanding their needs and common logistics challenges are crucial for logistics companies. Awareness of what customers expect from an “ideal logistics partner”, provides valuable insights into the company's strengths and weaknesses. Partnership: Logistics service providers must keep large storage space in the warehouses and production centers for efficient customer goods processing. For logistics companies Infrastructure upgrade is not just desirable, it’s a necessity to maintain high-quality standards. Storage: Effective integrated logistics management relies on tools and software products as the foundation of a secure network that simplifies information exchange among workers and timely disruption notifications. Technology: Integrated logistics further enables companies to replace paperwork with digital assets wherever it’s possible, accelerating operations, reducing redundancy, and freeing up employees for more critical tasks. Additionally, enhances supply chain coordination through real-time analysis and forecasting, injecting greater accuracy into the process. Digitization: digitization What Is the Future of Integrated Logistics? Logistics service providers are increasingly adopting integrated logistics models to match changing customer needs and global trends—in addition to improving cost savings, optimizing business operations, and achieving faster progress with the help of innovation. In the future, integrated logistics will encourage more collaboration, like crowdfunding platforms. As businesses adopt these methods, it will further affect customer expectations regarding delivery speed and time. especially for eCommerce startups

Integrated Logistics: A Game-Changer for Logistics Industry

Real-world containers are the physical structures that are designed to transport goods and materials. These containers are used in industries like warehousing, shipping, etc. These containers are made of robust materials that can be transported in a variety of transportation. Software Containers, on the other hand, are a virtualization technology that provide a lightweight isolated environment for applications and their dependencies. How do containers work? Containers leverage the host operating system's kernel and resources. These lightweight environments separate the application within it and its dependencies from the host environment and other containers. The host OS provides necessary resources to the container, like storage, networking and system libraries. Are Containers the Same as VMs? Containers and virtual machines (VMs) serve different purposes and have distinct characteristics. Containers offer lightweight isolation at the operating system level, sharing the host's kernel. They provide faster startup times, efficient resource utilization, and higher density compared to VMs. VMs, on the other hand, create a completely virtualized environment with a separate guest operating system, allowing multiple operating systems to run on a single physical host. VMs provide stronger isolation but are typically heavier in terms of resource usage. Pros and Cons of Containers Pros Portability: Containers provide consistent deployment and execution across different environments, making it easier to move applications between the development, testing, and production stages. Scalability: Containers enable easy horizontal scaling, allowing applications to handle increased workloads efficiently. Efficiency: Containers have a smaller footprint, faster startup times, and efficient resource utilization, enabling higher density on host machines. Isolation: Containers offer process and file system isolation, ensuring that applications and their dependencies are encapsulated and don't interfere with each other. DevOps-Friendly: Containers facilitate the adoption of DevOps practices, enabling faster application development, deployment, and continuous integration. Cons Limited Compatibility: Applications requiring low-level kernel access or specific hardware dependencies might face challenges when running inside containers. Networking Complexity: Container networking requires careful configuration and management to ensure proper communication between containers and with the outside world. Security Considerations: Container security practices, such as image scanning, isolation, and access control, are crucial to prevent potential vulnerabilities. Containers have revolutionized the way applications are developed, deployed, and managed. They offer lightweight and portable environments, simplifying the process of running applications consistently across different platforms. By embracing containers and leveraging their advantages while addressing the associated challenges, organizations can unlock greater efficiency and flexibility in their application ecosystems. Also published . here

Comparing Physical Logistics with Virtualized Deployments

As of 2022, the global market for digital twins was valued at And experts estimate an impressive annual growth rate of 37.5% from 2023 to 2030. $11.12 billion. Digital twins help connect the physical and virtual worlds, which means we can predict when things need fixing, work more efficiently, and create less waste. So, embracing the potential of digital twins is a crucial move as the logistics sector steps into the new Industry 4.0 era. Which benefits can this technology bring to the logistics and supply chain industry? Let’s take a closer look at them in this article. What Is Digital Twin Technology? Digital twins are virtual replicas of real objects. For example, if you want to make changes in a supply chain, you can create a digital twin to test things virtually without disrupting actual operations. These digital twins combine the Internet of IoT, Big Data, AI, and ML to construct virtual environments. Sensors on physical objects collect real-time and historical data, which is then used in the digital twin. AI and ML simulate real-world conditions, behaviors, and interactions within this digital realm. So, with digital twins, teams can create precise models, explore different scenarios, and predict problems before they happen in reality. , digital twins are used to model production lines accurately, helping operators identify bottlenecks, enhance efficiency, and minimize downtime. They can even simulate how new components interact with existing systems before physical implementation. In manufacturing In logistics, digital twins can simulate entire supply chains, offering valuable insights into areas like warehouse operations, inventory management, and transportation efficiency. By pinpointing potential disruptions, companies can develop stronger, more resilient, and efficient logistics networks. This technology has the potential to boost revenue by and improve product quality up to 10% by as much as 25%. How Does It Work? It all starts with a group of experts, data scientists, or math professionals, who closely study the data and physical characteristics of a real-world object or system. They use this knowledge to build a digital model that mimics the real thing. Then, developers create virtual models that constantly receive real-time data from the physical object through sensors. It allows the digital twin to replicate events in real time. Digital twins can be as simple or complex as you need, and the quality of the virtual model depends on the data you provide. You can use this technology during product development to provide feedback or as a standalone prototype to predict what might happen once you create the physical version. What Are the Use Cases of Digital Twin in Logistics? Warehouse Management A digital twin model provides up-to-the-minute insights into all activities within the warehouse. It's like having a map that can direct you to the best spots for inventory, help you monitor supplies, and figure out the quickest paths for your busy loaders. It also lets you assess how layout and process changes might affect operations without actually implementing those changes. This helps you make the most efficient use of your space and resources. For example, IBM offers a system that uses sensor data and point-of-sale information to create a virtual replica of your inventory. Their digital twin can forecast demand, streamline the supply chain, and add automation to warehouse inventory. Transportation Management With real-time data on location, condition, and status, businesses can identify and resolve potential issues with packages or cargo. Digital twins also help with selecting the quickest routes based on real-time traffic data from various options. It's basically a personal GPS that finds the fastest path, ensuring efficient deliveries and reduced fuel consumption. With a digital twin, even vehicles let you understand their surroundings and performance to make informed decisions about fleet management. For example, FedEx uses digital twins to map out the best routes for their trucks and monitor shipments around the clock. Supply Chain Management Digital twins provide a comprehensive view of supply chain management, incorporating production, inventory, demand, and procurement data with real-time insights for informed decision-making. Digital twins, using advanced analytics and AI, optimize resource utilization, planning, and risk reduction. They identify vulnerabilities in supply chains and warn us to take proactive measures. Real-time data enables timely issue resolution and ensures customer satisfaction remains high. How Can You Get the Best Results from Digital Twins? Creating digital twins is a complex task. If you want to get started with this technology, you should first focus on the specific areas that match your goals. You need to make accurate digital models of complicated things, and they have to match the real world in real-time. Also, for digital twins to work well, you need to have good-quality data at every step of the supply chain. So, if you put good data in, you'll get good results.

Logistics Will Be Reimagined With Digital Twins: Here's How

In recent years, supply chain and logistics industries have faced growing challenges. From labor shortages to unpredictable weather and shifts in supply and demand due to the pandemic, logistics has become far more complex. To tackle this complexity, a different approach is needed. Traditional methods of optimizing individual functions or the entire business no longer suffice. What businesses require now are logistics solutions that consider the entire complex system. This is where comes into play. quantum computing What Is Quantum Computing? , a super-fast type of computing, has the potential to greatly speed up various processes. It can solve problems much faster, , compared to regular computers. Quantum computing up to 100 million times However, it's important to note that quantum computers are currently expensive to make and not ready for widespread use. Still, their potential to solve real-world supply chain issues is significant. Quantum bits, or qubits, are the building blocks of quantum computers. They can exist in multiple states simultaneously, allowing for more complex calculations, unlike traditional bits. are interconnected, similar to how various factors affect a complex supply chain. This interconnectedness is a unique feature of quantum computing. Qubits Although there's more work to be done, many tech companies are already offering access to quantum computing features. Tech giants like , are leaders in quantum computing development. For example, IBM delivers quantum computing solutions useful for supply chain efficiency challenges. Microsoft and IBM How Can It Benefit Logistics? I believe that the growth and progress of quantum computing could have a substantial impact on the logistics and supply chain sectors. With improved sharing of information and collaboration among transportation providers, regulators, and customers, quantum computers have the potential to enhance operational decision-making. This could lead to smoother service and improved results for the entire supply chain, benefiting society as a whole. Here are the 3 most promising use cases for quantum computing. Last-Mile Delivery Quantum algorithms can be a game-changer in the world of last-mile delivery. By enabling global routing optimization and more frequent re-optimization, quantum computing could decrease door-to-door freight transportation costs, all while enhancing customer satisfaction. A good example here is IBM's collaboration with a commercial vehicle manufacturer. They used a mix of regular and quantum computers to figure out , considering the need for 30-minute delivery time windows and truck capacities. the best way to deliver packages to 1,200 places in New York City The result? They found a way to make deliveries cheaper and more efficient with quantum computing. Contribution to Supply Chain Visibility is crucial today, with investing in it to become market leaders. Quantum computing can help in this aspect of the supply chain as well, processing vast amounts of data at incredible speeds, and enabling real-time insights and decision-making. Supply chain visibility 92% of global companies Quantum computing's ability to handle complex calculations and simulations makes it It can assess multiple scenarios simultaneously, taking into account various factors and variables. ideal for optimizing supply chains. Quantum computing empowers businesses to make smarter decisions, manage risks effectively, and enhance customer satisfaction, ultimately staying ahead in the competitive market. Disruption Management Traditional systems for dealing with disruptions often rely on a set of rules, manual interventions, and a step-by-step process. These systems, while tried and tested, have limitations. They are usually isolated and can't provide a deep understanding of how to handle disruptions effectively. Quantum computers can improve decision-making by and measuring their impact on different parts of the network. Which results in quicker recovery times, cost savings, and fewer hiccups for both operations and customer service. running simulations of various disruption scenarios Moreover, classifies and predicts disruptions, making the process even more precise. quantum ML Sustainable Maritime Routing When it comes to planning maritime routes for sustainability, it's not a straightforward task. Large fleets, unpredictable weather, and shifts in demand make it tough to find precise solutions using regular computers. Quantum technology can simulate and , considering lots of factors. The tech handles the complicated math needed to make routes more sustainable, makes shipping better for the environment, and changes the whole maritime logistics system to work better. analyze many different maritime route options all at once What’s the Future of Quantum Computing? With the ability of quantum computing to quickly run complex plans and simulations, it can make the decision-making process much more efficient and easier. By embracing quantum techniques, we can make our current computing systems better while we await the future of logistics and supply chain optimization. I am confident that quantum computing is set to shape the future of supply chains.

Quantum Computing Will Transform the Logistics Industry Within the Next Decade

is a statistical method used for analyzing a dataset in which there are one or more independent variables that can be used to predict the outcome of a categorical dependent variable. In simpler terms, it's a technique used for classification problems where the target variable is binary (i.e., it can take on two possible values, such as 0 or 1). Logistic regression The main goal of logistic regression is to find the best-fitting model to describe the relationship between the independent variables and the probability of a particular outcome. It uses the logistic function (also known as the sigmoid function) to map predicted values to probabilities. Difference Between Linear Regression and Logistic Regression is used when the target variable is continuous and can take any numerical value. It predicts a value that is unbounded, which means it can be any real number. Linear regression uses a straight line to model the relationship between the independent variables and the dependent variable. Linear regression , on the other hand, is used when the target variable is categorical and represents two classes (binary classification). It predicts the probability that a given instance belongs to a particular class. The output of logistic regression is bounded between 0 and 1, thanks to the logistic (sigmoid) function. Logistic regression Real World Applications of Logistic Regression Logistic regression finds applications in various fields due to its simplicity, interpretability, and effectiveness in binary classification problems. Some real-world applications include: : Medical Diagnostics Predicting whether a patient has a particular disease based on symptoms and test results. : Finance Credit scoring to determine if a borrower is likely to default on a loan. Predicting the likelihood of a customer subscribing to a service based on demographic data. The logistic regression model uses the logistic function (also known as the sigmoid function) to model the relationship between the independent variables and the probability of a particular outcome. Mathematical Formula for Logistic Regression The logistic regression model can be mathematically expressed as: Logistic Function (Sigmoid Function): The logistic function is defined as: Here, ( ) is the output (probability), and is the linear combination of the independent variables and their coefficients: S t t The logistic function transforms any value of to a value between 0 and 1. This is crucial in logistic regression because we want to model probabilities. t Transformation of Linear Combination into Probabilities The linear combination t represents the weighted sum of the independent variables. When we apply the logistic function to t, we obtain a value between 0 and 1. This value represents the estimated probability of the event =1 given the values of the independent variables. Y In logistic regression, the goal is to find the best-fitting set of coefficients that maximizes the likelihood of the observed data. This is typically done through optimization techniques like gradient descent. Binary and Multinomial Logistic Regression Binary Logistic Regression: is used when the dependent variable has two possible categories or classes. These classes are typically coded as 0 and 1, representing the absence or presence of an outcome or event. Binary logistic regression For example, binary logistic regression can be used for tasks like: Predicting whether an email is spam (1) or not spam (0). Determining if a patient has a certain disease (1) or does not have it (0). In binary logistic regression, the logistic function is used to model the probability of belonging to one of the two classes. Multinomial Logistic Regression: , also known as softmax regression, is used when the dependent variable has more than two categories. It's an extension of logistic regression that can handle multiple classes. Multinomial logistic regression For example, multinomial logistic regression can be used for tasks like: Predicting the type of fruit in a basket (e.g., apple, banana, orange). Classifying different species of animals (e.g., cat, dog, bird). In multinomial logistic regression, the logistic function is extended to handle multiple classes. The softmax function is used to compute the probabilities of each class, and the class with the highest probability is predicted. Here's how it works: : Softmax Function The softmax function takes a vector of scores (one for each class) and transforms them into probabilities that sum to 1. It assigns a probability to each class based on the scores. : Prediction The class with the highest probability is predicted as the outcome. Code Step 1: Import necessary libraries import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score Step 2: Load and prepare the Titanic dataset data = pd.read_csv('train.csv') Step 3: Select relevant features and target variable X = data[['Pclass', 'Sex', 'Age', 'SibSp', 'Parch']]
y = data['Survived'] Step 4: Data Cleaning and Encoding # Convert categorical variable 'Sex' to numeric
X['Sex'] = X['Sex'].map({'male': 0, 'female': 1})

# Handle missing values in 'Age' (replace with mean)
X['Age'].fillna(X['Age'].mean(), inplace=True) Step 5: Split Dataset # Split the dataset into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) Step 6: Initialize the Model model = LogisticRegression()
model.fit(X_train, y_train) Step 7: Evaluate the Model # Step 5: Make predictions
y_pred = model.predict(X_test)

# Step 6: Evaluate the model
accuracy = accuracy_score(y_test, y_pred)
print(f'Accuracy: {accuracy * 100:.2f}%')

# ------------------ OUTPUT -------------- #
Accuracy: 82.68%

Mastering Logistic Regression: A Comprehensive Guide with Practical Example

Let's learn about via these 42 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Logistics /Learn Repo 1. Artificial Intelligence and Logistics 4.0 Are Transforming the Way We Manage Inventory The growing competition in logistics has forced companies to look for new alternatives to remain among the best players in the market. AI has come to the rescue 2. The Story of Shuttle Planet, Early Traction, and a Bunch of Misfits "Keep going; don’t let fear stop you too much. Focus on the fact that every effect has a cause, find out what that cause is." 3. How Optimizing Outbound Logistics Saves Your Business Time and Money Outbound logistics play a critical role in a company's overall supply chain management and can significantly impact its bottom line. 4. Sea of Transformation: Chatbots in The Logistics Industry The usage of the new age customer support technology bots, popularly known as Chatbots is on the rise. Researches show that more than 80% of the customer communication that is done on websites or mobile apps are done through chatbots. Chatbots are highly valuable for the companies because they can work round the clock, are easy to use and do not make any kind of errors. 5. How Estimated Time of Arrival is Calculated in Logistics Tech We focused on how to enhance ETA in Logistics and how to calculate it. Computing the estimated time of arrival is one of the ways toward customer satisfaction. 6. Toilet Paper Mania Leaks Supply Chain Opportunity: What Will Venture Do? W.W.V.D? Even before the pandemic hit, global supply chains contained an estimated $176 billion of inefficiencies. 7. Hacking the Way Business is Done With Diversity [Infographic] Understanding how diversity should properly be represented through business and the supply chain. 8. Analyzing The 6 Most-Promising Logistics and Supply Chain Trends in 2022 Here's a review of the key logistics and supply chain trends of 2022 to help T&L leaders decide on their innovation strategy and what technologies to invest in. 9. 4 Effective Ways Augmented Reality Solve Issues in Logistics Industry 10. Logistics Security: 5 ways to protect the Supply Chain Against Cybersecurity Attacks This article explains how to protect the supply chain sector against cybersecurity attacks. 11. How Technology Has changed the Logistics Industry Improved technology has also increased productivity in the supply chain.  It is helping to make the shipping process more efficient. 12. How IoT is Transforming Transportation, Supply Chain, and Logistics In today’s connected world IoT can speed up the rate of delivery actions of vehicles used for logistics and transportation purposes. 13. Implementing Business Technology Improves Startup Operations Considering all the ways technology is currently improving your business can help you think more broadly about how further implementation can affect operations. 14. Reconstructing Our Food Supply Chains with Blockchain Technology Blockchain technology can streamline and restructure the way that we interpret global supply lines, a change that may be vital for addressing climate change. 15. How the International Parcel Service Works The international parcel service has a special operation, which we will try to describe below. If you want to know and understand it, do not stop reading. 16. Startup Interview with Shachar Tal, Loginno Co-Founder Hackernoon's startup interview with Shachar Tal, Loginno's co-founder. 17. Using Web3 to Detangle the World’s Supply Chain The global supply chain is in a gridlock. Let's fix that. 18. 5 Best Transportation Management Systems (TMS) in 2021/2022 Having a robust TMS adopted to your logistics business has become a staple. A sneak peek at the best ready-made TMS solutions in 2021. Check out fresh insights. 19. The History and Perks of Third Party Logistics Software in Warehouse Management 3rd Party Logistics Software can be a powerful tool in managing your online business by consolidating much of the logistics under one easy-to-use site. 20. How 3PL is Changing eCommerce Supply Chain Dynamics Outsourcing supply chain and logistics to the 3PL providers have proved to be helpful for businesses. They offer various services for improving processes, risks mitigation, and saving resources. 21. Technologies That Are Transforming Logistics Industry How Big is the Number Game? 22. Hacking the Way Business is Done With Diversity [Infographic] Understanding how diversity should properly be represented through business and the supply chain. 23. This Startup is Bringing Ecommerce to Brazilian Favelas Nestled in a 10-square-kilometer area in the southwest zone of São Paulo, the favela (slum) Paraisópolis is home to more than 100,000 Brazilians. 24. How RPA is Helping Supply Chain Management Logistics and Supply Chain is one of the fastest-growing and the most competitive sectors in the world. Over the years, businesses have invested billions of dollars in scaling up their process and infrastructure to lower the price and look for opportunities to increase efficiency. 25. Supply Chain 4.0 Powers Greater Efficiency and Visibility in Logistics Learn how the digital supply chain allows organisations in Logistics and other sectors to become more agile and respond to market shifts with smarter solutions. 26. Integrated Logistics Management Software: Uber For Supply Chain Management As per statistics, upto 61% of customers want quicker deliveries, while 66% consider that the delivery method must be central to their shopping experience. Also, 93% of customers say that they wish to stay informed and receive constant and live updates from the retailers about the expected shipments. 27. 8 ways in which AI helps the logistics industry The world of logistics has been completely transformed with the advent of newer technologies, especially AI, and it is not a luxury anymore but a necessity for a business in this industry to thrive. 28. What happens inside an Amazon warehouse: A software engineer's guide Have you ever wonder what happens inside of an Amazon warehouse? As a software engineer, the supply chain field has plenty of technical challenges. 29. Blockchain Technology a Natural Progression for Supply Chain Companies We estimate that the application of Blockchain to global supply-chain alone could result in more than $100 billion in efficiencies. Add improvements in provenance and traceability of pharmaceuticals and food. 30. China's Information Warfare via LOGINK Continues Unabated: Here's How It's Done The PRC has created LOGINK, a logistics-focused software, for the purposes of data collection in accordance with its information warfare efforts. 31. Global Trading on the Blockchain - Opportunity or A Pipedream? Industries and governments are continuously seeking ways to optimize the movement of goods, data, and currencies across global supply chains. Global growth needs a jumpstart. 32. 12 Years of Blockchain: Where Are The Applications? There were a lot of talking about where and how blockchain is suitable. Attempting to stick the blockchain everywhere and to everything is a parody. 33. How Automatic Vehicle Location Improves Safety for School Buses Real-time communication has become an essential aspect of many industries, and transportation is no exception. With the rise of GPS tracking and internet-enabled devices, it has become easier to track vehicles and provide real-time updates to drivers and passengers. Aleksandr Ulanov, a senior software developer with extensive experience in Ruby development and real-time technologies, has been at the forefront of this development. In his recent work with 4mativ, he has developed a ground-breaking AVL platform that provides real-time updates on the location of school buses to parents and schools. In this interview, Aleksandr discusses the challenges he faced and the solutions he found in developing this platform, as well as the importance of real-time updates in the transportation industry. 34. Blockchain Application to Transform Supply Chains Towards Sustainability The self-updating and verifiable nature of the blockchain means that it can be useful in improving supply chains in an efficient and sustainable manner. 35. How the Conflict Between Russia and Ukraine is Affecting Supply Chains The war in Ukraine has disrupted global supply chains by tying up the production of two of Europe's biggest suppliers while disrupting trade through them. 36. Integrate a Route Optimization API to Save Millions in Last Mile Costs An overview and cost/benefit analysis of how route optimization API integrations can drive instant positive returns in last mile logistics. 37. Delivering Hydroponic Salad via Drones and Being Paid in Bitcoin [An Interview] Hydroponics, drones and Bitcoin. Three technological concepts that are used in a new project from the Parallel Garden team in cooperation with Parallel Polis. As we enter an era of social distancing, delivery of food by drone can be a pioneering act. We bring you an interview with the authors of the Hydroponic Flyer 2020 project. 38. How New Tech Will Help Avoid Delivery Delays This Holiday Season If every cloud has a silver lining, eCommerce has found one in COVID-19. Due to the fear over risks of infection, consumers, in general, are avoiding in-person shopping in brick-and-mortar stores and choosing to shop online instead. In the first eight months of 2020, online sales generated $497 billion in revenue. Adobe estimates that COVID-19 has lifted eCommerce sales by $107 billion since March. 39. Growing Your Construction Business? There’s an App for That. Thanks to modern technology, it’s possible to update blueprints, create and sign contracts, and care for your construction workers from your smartphone. To help take your company to the next level, check out these top construction apps. 40. Logistics App Development Overview: An Essential Guide Applications for logistics help collect and process data and control logistics processes. 41. How to Bridge the Physical and Digital World Through Digital Twinning A digital twin is a virtual form of a real-life product or a service. Heres why that matters! 42. Our Uber Eats orders would soon start getting delivered by robots! Our Uber Eats orders would soon start getting delivered by robots! Thank you for checking out the 42 most read stories about Logistics on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

42 Stories To Learn About Logistics

Practically 95% of any human reaction is a form of prediction. From how one gets dressed to the chosen commute, every decision is guesswork based on parameters such as the weather, traffic, and time of day. Yet, as inventory forecasters predict demand on multiple levels, the number of external factors impacting their decisions also skyrocket, making it extremely difficult for humans to make the predictions. Robust inventory management is the unsung hero in logistics—and it’s encouraging the global supply chain AI market to reach by 2028. But it’s dependent on one thing: Accurate forecasting. $17.5 billion providers and data teams today need to be hot on understanding the , what sources they require to meet their objectives, and how to maintain its quality. Logistics power of data With that in mind, let’s explore how paying more attention to data quality and advanced analytics can optimize inventory forecasting and improve operational efficiency. Why Accurate Data is Essential in Forecasting McKinsey reports that applying AI-driven forecasting to supply chains reduces errors between . But the limited usefulness of the data collected remains the top barrier to successful implementation, keeping the rate of AI adoption since 2018 at a low 6%. With the right data and tools, inventory forecasters can predict anything from how much time they have to release trending products to the risks and costs of missing out on the opportunity. 20% and 50% Take fast-fashion brands, for example. They distribute up to 20,000 clothing stock-keeping units (SKUs) across ten countries in the EU, where price sensitivity and sizes vary per location. Then the new Barbie movie is released, and suddenly everyone wants to wear pink. That’s over 200,000 SKUs to consider . barbie-fying While stores like Gap are ahead of the game in creating a , others are apprehensive, knowing that the merchandise will end up on sale if movie ratings are low. Gap x Barbie collection Inventory forecasters need to weigh everything from budget to the predictability of movie success—and they want these figures yesterday. With accurate data regarding operations, such as delivery speed, workers available, and vehicle capacity, alongside external inputs, including consumer trends, AI-powered analytics tools can help inventory teams make data-driven decisions instantly. AI for Data Collection and Storage Many organizations possess sufficient data to leverage the benefits of AI-driven forecasting: A quality forecast could be achieved on 80% internal and 20% external data. The trick is ensuring that data is collected, stored, and visible to inventory teams. And this truth is something data champions like and are more than aware of. For stores to better support customer fulfillment and omnichannel retailing, the two companies have started putting drones to work as a method of tracking warehouse inventory. Gather AI IFM From counting parcels to spotting at checkout, computer vision AI technology tools can detect and track objects and SKUs as they move through the warehouse or store. This helps provide the continuous and reliable updates needed for making real-time data-driven decisions while removing room for human error. retail theft Automating data collection, such as the number of items on shelves and the locations of particular pallets, helps inventory teams understand their operations and needs in real time. While storing operational, financial, and external data required to meet inventory objectives in central repositories enables data teams to capture a holistic view. That’s why retailers and companies must devote more time to their data collection and storage methods, looking at how they can increase data visibility. This includes ensuring strict access controls and encryptions to protect data and keep it in the hands of those with authorization. logistics AI for Data-Driven Inventory Forecasting At the analytical stage of the data lifecycle, AI forecasting tools, fed with continuous and reliable data, can predict sales down to the SKU level. This way, sellers can adjust production levels, manage procurement, and allocate resources effectively. This alignment of inventory with demand reduces handling and storage costs and improves overall operational and financial efficiency. Here’s how to implement forecasting models with success: What business changes could affect the inventory variables? What product expiration periods, storage space, and storage conditions are required? How could staff turnover and ship maintenance affect this? Defining reasonable ranges for these parameters is crucial to avoid creating unrealistic outputs leading to adverse business decisions. Define the critical parameters: Unexpected events will likely skew AI predictions. The smoothing technique is a statistical approach to eliminating outliers from datasets. It helps to minimize the variation in data between periods where an anomaly occurred, creating a more representative data set for AI-powered forecasting models to learn from. Apply data smoothing: Take Covid-19, for instance. The data captured during this time falsely illustrate business as usual and would require smoothing. If data is incomplete, logistics teams struggle to have an accurate historical representation, and assumptions go awry. For this reason, that is ‘synthesized’ or ‘artificial’ information generated from existing data—is used to train AI-powered forecasting models with potential scenarios. The machine can define more data classifications and increase predictability by reading a broader data set. Train what-if simulations with augmented data: augmented data— What-if scenarios are critical in cases of limited data samples, which diminishes confidence in forecasting with accuracy. They are also valuable for addressing distant future uncertainty where it is challenging to predict unexpected events. Depending on the size of your data, you may choose a simpler AI model or a more complex one where larger data sets and many iterations are available to train numerous parameters. Harnessing the power of data-driven inventory forecasting is the key to unlocking logistics companies’ full potential in today’s complex supply chain landscape. With robust forecasting models, inventory managers can ensure the right products are available when customers need them, leading to enhanced customer satisfaction, loyalty, and a competitive edge. Organizations can go on to assess market opportunities, plan new product launches, manage product lifecycles, and make optimal supply chain decisions aligned with business objectives. This article was originally published by Hristo Hadjitchonev on . 150sec

From Instinct to Insights: Data-Driven Inventory Forecasting in Logistics

Applications for logistics help collect and process data and control logistics processes. After a brief downturn caused by the COVID-19 pandemic, the logistics industry has returned to robust growth. By 2027, the global logistics market is expected to exceed 13.7 billion euros. The main competitive advantage in logistics is the speed of delivery. To some degree or another, all innovations and improvements in transportation and warehousing relate to reducing delivery times and improving the safety of shipping and storage. Software applications help make the logistics business more efficient. Our review focuses on logistics app development and the business benefits of implementing software solutions. Types of Logistics Applications Application types depend on the area of logistics in which they are applied. are designed to collect, process, and store data related to transportation. Routing and fleet management software applications App users can track the fleet location, analyze fuel consumption, repair costs, and distance traveled, and look through the vehicle maintenance history. Apps can remind users of scheduled fleet maintenance. Timely decisions based on data analysis allow the company to optimize routes, save resources, and increase business efficiency. are built to keep records of goods delivered to storage, track the location of assets, and monitor temperature, humidity, expiration dates, and other parameters. Asset tracking and warehouse applications A warehouse IoT system consists of devices equipped with humidity and temperature sensors. Gadgets transmit data via LoRaWAN to the AWS server. AWS Lambda, Amazon SNS, and AWS IAM services are used to store and process data. A cross-platform mobile logistics application receives and analyzes device data. Sensors' data-receiving process Many goods require strict adherence to storage conditions. The C++ application, developed using the Qt framework, displays the temperature and humidity of the warehouse in real time and notifies users in case of significant deviations from the set values. The app's functionality contains statistical time reports on fluctuations in temperature and humidity. A warehouse app pre-design This monitoring system allows companies to reduce storage costs and minimize raw material losses. Transportation and warehouse software can be integrated into a single system that covers the entire supply chain, from order processing to delivery of goods to the consumer, including return shipping. The world's leading suppliers of logistics management systems are the German company SAP and the American company Oracle. The HMI application displays information related to product placement and order priority. Warehouse process automation is growing along with the warehouse industry. The size of the warehouse automation market increased by $10 billion over the ten years from 2012 to 2022, with further growth of $12 billion by 2026 projected. Size of the warehouse automation market worldwide from 2012 to 2026 (in billions of U.S. dollars). Source: Statista The logistics industry is driving the growth of autonomous IoT and robotics markets as companies incorporate robots and drones into their workflows. Mobile logistics robots are expected to generate more than $9.8 billion in revenue by 2025. Revenue from logistics robots until 2025. Source: Statista The global warehouse robotics market is forecast to triple in dollar terms in the next ten years. Features Logistics App Devs Should Optimize For All software applications, regardless of their scope, need to possess shared features to be beneficial: Speed and efficiency, Reliability, Data security, A reasonable price, Easy to install and use, Integration with internal and external systems Logistics applications have unique features related to the scope. Mobile applications for the logistics industry have unique features. Truck Tracking Apps can get vehicle location information using real-time GPS location. The simple and effective system helps track vehicles, optimize delivery, and provide consignees with information about where their cargo is. The system consists of GPS devices installed on trucks and an application that stores the GPS coordinates transmitted by the sensors and displays them on a map. The Qt framework, its useful tools, and C++, QML, and JavaScript helped create a cross-platform app for iOS and Android, and the Kalman filter helped improve the accuracy of the GPS positioning of logistics vehicles. Best Routes You can plan the best delivery routes and save time, fuel, and overhead costs without having a bunch of reports and files, but only by installing a logistics application on your smartphone. Route planning and optimization support solving the “last mile” problem when consumers want fast and inexpensive delivery, although this is often the most expensive and time-consuming part of the logistics process. For example, a navigation system developed for a delivery service assists couriers in choosing the best routes. The manager assigns tasks to the courier through the web portal, indicating the delivery addresses on the map. He always knows the couriers' location by receiving GPS positioning data. Route optimization Couriers use mobile cross-platform applications that depict the shortest route calculated using mathematical algorithms. The application sends notifications to the company manager and the shipper when the courier marks the delivery. Multilingual Support Misunderstandings and translation errors can be troublesome when decisions should be taken quickly. Multilingual logistics applications are user-friendly and can attract more customers to your company. Offline Functions The web connection is not always stable. If the mobile app has offline functionality, app users can enter data, view saved numbers, and access reports even when the network is unavailable. Chat and Calls to the Driver Built-in messaging and calling can be useful communication channels between company managers, shippers, and drivers. Logistics managers can learn about car accidents or breakdowns on the road and adjust the route. Customers can obtain the necessary delivery data directly from the driver. Network Protocols and Technologies Support Logistics software solutions typically interact with IoT devices, robots, and sensor-enabled systems to obtain the GPS positioning, temperature, humidity, and other data. Applications can support various communication protocols such as Wi-Fi, Bluetooth, NFC, and BLE. The customizable GPS tracking platform is built for asset monitoring. The system consists of a GPS tracking device with BLE, Wi-Fi, and GSM/HSPA communication interfaces and a cloud platform that stores the location and status of assets and displays this data to users in real time through a web interface and a mobile app. An asset tracking system is a GPS tracking device, a server, a mobile app, and a web app for displaying the asset’s location and condition. A cross-platform application for iOS and Android with Google Maps allows employees to monitor the location of assets 24/7. Asset tracking not only helps with warehouse management but also extends to other related areas. For example, the plug-and-play solution can be applied to localized online advertising of shops, restaurants, and other places using a distributed BLE beacon system, a web server, and a mobile application. Using the Android Studio IDE, the developers have created an SDK that can be integrated into any Android application. The Android application uses the iBeacon protocol to receive data from beacons located in shops, restaurants, and entertainment venues. The application then sends it to the web server, which determines the user's location. Data related to discounts, sales, and promotions is stored on the server and can be sent to recipients using push notifications. Interaction of components in our Bluetooth Low Energy beacon system This system allows various businesses, such as small coffee shops, boutiques, or cinemas in shopping and entertainment centers, to effectively advertise their services and promotions to their target audience. Cross-Platform App Capabilities Cross-platform logistics applications can run on iOS, Windows, and Android operating systems on mobile and desktop platforms without any or minimal differences in the UI. Users can choose the most convenient way to use the app. Logistics Software App Benefits The implementation of logistics applications contributes to the diminishing of transport and storage costs and the reduction of human errors. There are other crucial benefits to developing transport and warehouse applications: Good company image The convenient interface of the logistics application captivates users and positively affects the company's image. Automated fleet tracking and management By automating fleet management, the company frees up labor resources and saves time. The manager receives real-time data on the state of the company's vehicles, corrects routes, and uploads data. Customer trust and confidence Senders and recipients are always aware of the cargo location and delivery times, thanks to mobile logistics applications. Customers are confident in the safety of goods because they control the logistics process 24/7 and can contact the driver on the way. If the delay does occur, the customer receives comprehensive data on the timing of cargo receipt and never remains in the dark. Fewer paper documents Reducing paperwork to a minimum saves time and resources. Benefits of having software apps for your logistics business Logistics App Development Outsourcing When entrusting the development of logistics applications or software and hardware complexes to an outsourcing company, you should state your wishes and requirements regarding the final product in as much detail as possible. Requirements may take into account the following points: application platform (mobile, desktop, or web version), operating system, application functionality, UI design, description and brief technical characteristics of the device with which the application will communicate, equipment communication protocols, certification requirements (if the project involves hardware development with subsequent certification). Software application development is not always beneficial. Sometimes software solutions turn out to be unsuccessful, inconvenient, or of little use. Also published here.

Logistics App Development Overview: An Essential Guide

What is the Biggest Number Game? The in the world is valued at an incredible $4 trillion. Logistics is the lifeblood of nearly all industries, including ecommerce, fashion, and other high-end tech-related sectors. The industry has spawned a multitude of ideas. This industry has created the potential for new initiatives to emerge and grow into essential contributors to the GDP. Because of its dynamic nature, this industry is looking for operational transformation. largest tech industry Technology has just hit the most crucial tech industry with its liveliness, with many techniques joining hands to create an utterly new, more productive and highly efficient environment for stellar business growth. One can find a fair amount of the business ecosystem if one digs into logistics and other primary industries. It is easy to see that several factors and a market proposition drive the transformation. Complete ML: Automation + Optimization The two main lanes for machine learning that leverages artificial intelligence are implementation and the final goal. Automation is one of these. It automates the general task as well as those that are replicated in nature. This requires excellent precision and accuracy every time. Automation is being used to streamline stacks as well as automate global container transportation and stacking operations that are bulkier. This is done by computer-programmed stacking machines, fully aware of stacking endurance and precise positioning to eliminate the chance of an accident. A lot of transit data is needed to analyze time-material trade-offs when optimizing. These machines were created to create a sustainable system that reduces the overall cost of end-to-end services. This optimizes energy consumption for a complete put her back in a dockyard. It also increases power efficiency and utilization of assets. What's optimization by Machine Learning? Imagine an automatic crane capable of lifting bulk containers after they have been offloaded onto a port. It raises the piston of a hydraulic crane far too much in comparison to the different heights required every time. It also sits idle while other cranes continue to operate in an active-passive manner. Optimized automated cranes reduce power consumption and speed up the idol standing time. They operate with an increased height and no need to lift. It will also balance the load and reduce idle time by collaborating with other automated cranes. More intelligent and sensible Blockchain Enabled Database Imagine a clever Logistic Ecosystem fully controlled by multiple vehicles, automated grains and IoT-enabled gadgets for total tracking and management. An active database must support this system with no lag that allows you to track, approve, and read transactions. Blockchain-enabled database management systems can fulfil this high-end requirement for something more than the typical system. This will not leave any loopholes in the current scenario. Blockchain can control the high level of randomness induced at the database layer through automation, optimization, and analytics. End-to-end Robotics Robotics is an application of automation and has nothing to do with artificial intelligence unless otherwise stated. Please Note Every day, intelligent and miniature robots are being developed for the logistics industry to streamline operations. This is a critical need, given the rapid rise in e-commerce and the increasing demand for speed and efficiency due to online sales. The tech department is one of the most important and focused divisions in the ecommerce ecosystem. It is a multidisciplinary sector that manages fulfilment and transport from sellers and delivers the products flawlessly after adding value to customers. Virtual welcome: Augmented Reality Augmented reality has made it possible for the logistics industry to make considerable strides in creating a virtual world that is easy to manage and highly interactive. Augmented reality empowers many industries and highly automated businesses by allowing them to see their supervision and all the tracking system embedded in a virtual market. It simulates a real-world environment that can perform all services, such as layout, stalking and billing. There is also a fundamental change in the way the Logitech industry operates. Computer vision and augmented reality are joining forces to analyze the data from a camera-hosted operation system. This allows tracking of product movements within the warehouse, which can be used for faster delivery. Superlative IoT Development The IoT is making every effort to transform a small logistics sector into an innovative one. This transformation begins with the full utilization of GPS and tracking of all Internet-enabled devices. The logistics industry is flourishing despite the automation lag. Many high-end sensors can be used to determine temperature and humidity. These parameters are essential for intelligent decision-making and a reduction in the time and cost of long-term approaches. Logistics get Wearable 'gears.' Every layer and phase of the largest industries are being affected by wearable technology. It is reasonable to assume that wearable tech empowers humans to link a logistics network for easy tracking, up-to-date information, and real-time updates. This is usually impossible with geographical and temporal constraints. Wearable technology is emerging from the logistics line in the face of IoT-enabled scanning lenses, infrared scanners on helmets, real-time updates through smart watches, and Internet-based digital data terminals. Next level automation: Self-driven Vehicles Automation is an intelligent technology that draws a lot of attention around the globe. With some final movements, the most prominent tech industry is expanding its opportunities for improvement in its operations. The present-day talks are about automated grains and robots that can be optimized. Still, the world is stunned at how self-driven vehicles reduce human involvement in an integrated logistics system. Who would have thought that technology could eliminate human driving skills as quickly as driving a decade ago? Today, many large industries and warehouses are managed without human intervention: celebration vehicles, transport containers, articles and offloads. The king: Cloud Computing Intermingling technologies are responsible for long-running discussions and light dissemination of the logistics industry's amazing sights. Take, for example, an automated warehouse management system. The objects are transported by cell prevent vehicles. All of this is supported with IoT devices, complete integration of sensors and many data flows between devices. But who would be responsible for keeping all this information interconnected with one backbone and for accounting? Although technology integration is possible, integrating them all takes a lot of effort. Although centralization is essential, cloud computing provides a more general level of control. It holds all the computer-based systems in place, documents them, and manages the data. They work alone to create an independent system within an integrated logistics industry network. This layer will be cloud computed and act beneath the entire system. The Last Word The world will agree that the cliche logistics network has transformed into a sophisticated, intelligent, highly integrated logistic system. It includes both humans and devices. Technology is constantly evolving. Call turn off technology businesses to transform current status. It is still a matter of great speculation as to how these technologies will intertwine and mature over time to stabilize the logistics sector. Innovators are constantly striving to make the industry more efficient and automated. It will take time to see how much they have accomplished in a system. Otherwise, this could be overkill.

How Technology Has changed the Logistics Industry

Digitalization is a blessing to the supply chain industry. It’s significantly improved the operational efficiencies of the supply chain. But digitalization has a downturn—it’s opened supply chain enterprises to more scrutiny from malicious actors. For example, weekly attacks on the in 2021. In the US, . Also, suffered cyber attacks in the last decade. transportation and logistics (T&L) industry increased by 186% supply chain attacks increased by 42% over 72% of supply chain enterprises Why do cybercriminals target supply chains? One explanation is the network. The supply chain is a network of manufacturers, suppliers, and retailers. Therefore, an attack on the supply chain is considered “high impact” because of the sensitivity of the data involved. The higher the impact of breaches, the better for cybercriminals. An attack on the supply chain is considered “high impact” because of the sensitivity of the data involved. The higher the impact of breaches, the better for cybercriminals. Another reason is supply chains are easy targets. Supply chain enterprises, on average, care less about security measures. In 2020, a a lack of digital culture and training is the biggest threat facing the T&L sector. Without adequate security policies, technological systems are like a house without a fence; they’re easy to infiltrate. PwC study revealed Without adequate security policies, technological systems are like a house without a fence; they’re easy to infiltrate. A third reason is ransomware groups. Ransomware groups—also called —provide malicious code to amateur and professional hackers to infiltrate systems. In the last few years, RaaS gangs have grown, and they increasingly target the supply chain. Check the image below for prominent attacks RaaS gangs orchestrated on the supply chain. Ransomware-as-a-service (RaaS) What weaknesses do malicious actors target in the supply chain? : Digital systems require passwords to manage accessibility. But weak or compromised passwords plague the logistics industry. According to NordPass, the to protect their digital systems. Instead, the employees use easy passwords such as “password”, “company name”, “company name 123”, etc. Login credentials employees of T&L don't use unique passwords Besides, the infamous attacks on US-based supply chains—JBS (a meat processing firm) and Colonial Pipeline—buttresses the poor accessibility security in the supply chain industry. For Colonial Pipeline, an employee's compromised password of the Virtual Private Network (VPN) was the entry point of attack. The JBS intrusion is a similar story: attackers gained unsolicited access through the unguarded credentials of JBS workers that were available on the dark web. Computer programs—such as remote desktop protocols (RDPs), VPNs, and firewalls—require protection. Leaving software, especially open-source software programs, unguarded is terrible for security. Open-source programs typically contain known vulnerabilities malicious actors can explore. Software blunders: In 2021, Intel 421—a cybercrime intelligence company—examined the in Asia, the US, and the UK. According to the report, cybercriminals gained unwanted access mainly through unprotected RDPs, VPNs, and private networks. BlueVoyant’s 2022 cybersecurity report also corroborates Intel 421 findings. software vulnerabilities of logistics companies According to , 90% of the top 20 logistics companies used open RDPs. Additionally, 10 of the top 20 used “software with high severity vulnerabilities” on their servers. Software blunders like these only have one end—security violation. BluveVoyant Phishing is an age-long tactic threat actors use to con sensitive information from people. Phishing scams are often spread through emails and text messages. Email security is still an issue in the logistics industry—90% of the top 20 . Therefore, it’s unsurprising that target the logistics industry. Unsecure emails equal more phishing: logistics companies lack email and phishing security 3.6% of global phishing scams Phishing is an age-long tactic threat actors use to con sensitive information from people What’s the way forward for the supply chain industry? Cybersecurity awareness is ongoing education about the latest security practices. But many logistics companies are complacent with cybersecurity education—at least can’t manage cyber attacks. Increase cybersecurity awareness: 55% of logistics employees Ignorance and gullibility fuel breaches; therefore, cybersecurity education is the first step to cyber protection. To begin with, implement basic security measures such as multi-factor authentication (MFA), phishing and email security, and third-party assessment policies. 2. Password breaches are still high—weak passwords caused in 2021. MFAs provide an extra layer of security to protect your accessibility credentials. Microsoft reports that . That’s how effective MFAs are! For instance, the Colonial Pipeline breach was partly successful because the exposed VPN account lacked MFA. With an MFA, there’s a high chance Colonial Pipeline would avert the intrusion. MFAs + Zero Trust = formidable security: 21% of ransomware attacks MFAs block 99.9% of cyber breaches For formidable security, add zero-trust security to the mix. Zero-trust infrastructure works on a “never trust, always verify” policy. It verifies every entity, internal or external, before granting access to a system. Zeo-trust security is an advanced policy that manages every network traffic. Software programs always require updates (or “patches”) to fix bugs and vulnerabilities. Once available, always patch your systems. Patch your software: : “how” and “who” respond to risks, vulnerabilities, and violations can make or mar your security system. IR defines the personnel and tools for different cyber scenarios. Crucially, it describes how to identify weaknesses that affect systems. Cyber attacks are inevitable; implement incident response (IR) Backups, an archive of your data, hastens data recovery should you experience data violation. The standard backup policy is to save three copies (one primary and two backup copies) of your data on two different media with one offsite copy. Have backups:

Logistics Security: 5 ways to protect the Supply Chain Against Cybersecurity Attacks

The digital supply chain has become a more strategic and integral part of operational activities in many industries, including logistics, retail, agriculture, automotive and more. Read on to learn why you should consider making supply chain 4.0 a reality for your business. The traditional supply chain can be outlined as a linear model that is useful in a predictable and consistent environment. However, the uncertain times we are currently experiencing requires the adoption of a new supply chain model that allows organizations to be more responsive and agile to survive and lead the market. Supply chain 4.0 is the application of the Intelligence of Things, big data combined with , data science, digital connectivity and many other smart technologies brought by the fourth industrial revolution. custom logistics software development Innovative technologies reorganize the traditional model, change how information flows within the chain, and help to achieve greater business success through automation and digitalization. Global organizations like Adidas, Maersk Line, Volvo, Port of Hamburg and Decathlon already use IoT in their supply chain operations to get valuable insights into things like inventory, logistics and warehousing. Source: supplychainbeyond Key benefits of supply chain 4.0 Digital transformation of the supply chain can bring a company a plethora of benefits from better end-to-end visibility and improved decision-making to higher operational effectiveness and minimization of expenditure. Here’s more about the top advantages of the digital supply chain: . With the digital supply chain, data exchange between an organization, multiple suppliers and customers becomes more effective. Real-time asset tracking powered by IoT, cloud-based dashboards and other tech solutions make it possible to establish an item's precise location. Organizations can see all updates added to the digital ecosystem, leading to ordering accuracy, traceability and efficiency. Espouse end-to-end transparency . Predictive analytics has the potential to reduce forecasting errors by 10% to 20%. Fuelled by AI and machine learning, predictive analytics evaluates historical information about demand, current market trends, weather conditions and other data to provide statistics-based demand forecasts and optimize inventory. Predictions can be carried on a monthly, weekly or even daily basis depending on the product, helping to prevent out-of-stock situations and ensuring on-time delivery. Moreover, performing real-time analysis of a constantly changing market allows organizations to adapt to prevailing trends and stay flexible. More accurate forecast approach . According to the , digital supply chain management offers a 25% faster response to market demand changes. Process management, supply and demand planning, cash flow and other underlying supply chain processes can be managed within one digital ecosystem. Custom warehouse management systems that use IoT and data analytics can optimize the warehouse space by providing insights into shipping and picking. Immutable records offered by blockchain technology and smart contracts allow supply chain optimization, guarantee secure and automated transactions, and increase the visibility of purchases and transactions in supply chains. Enhanced supply chain management Boston Consulting Group . In the US, poor customer service lead to an average loss annually. The end-to-end visibility guaranteed by the digital supply chain increases the knowledge of employees in customer-facing positions. Customers can receive an immediate response about product availability and detailed information about the order, improving the overall experience and bottom-line growth. Improved customer experience $62 billion Source: McKinsey Supply chain 4.0 use cases throughout industries The disruption in today’s business environment makes digital supply chain adoption a necessity rather than an option. And while many organizations are just considering the benefits, some have already implemented a digital supply chain and proven its capabilities. Here are a few applications of supply chain 4.0: 1. Manufacturing Digital technologies can help to mitigate the disruptions caused by the pandemic and boost operational efficiency and continuity. For instance, wearables like augmented-reality glasses can help employees receive or render remote assistance, leading to reduced maintenance time. Machine vision algorithms can conduct an automatic quality inspection by analyzing images for specific results. It is unlikely that 3D printing will substitute the traditional manufacturing process. However, it can be applied as a cost-effective solution for producing personalized items. Dr. Scholl, a manufacturer of foot care products, to create custom orthotics. uses 3D printing 2. Logistics Smart logistics powered by connectivity, advanced analytics and automation solutions encompass route optimization and vehicle scheduling. Moreover, COVID-19 has increased the need to deploy fully autonomous vehicles to deliver goods and minimize physical interactions. The introduction of fully automated vehicles depends on deep learning algorithms, and the technology is not yet available. Even though most vehicles still have to be controlled by human drivers, they are starting to adopt self-driving features. In 2019, an autonomous truck with a safety driver on board made a trip from California to Pennsylvania in three days. Such a trip would usually take nearly nine days. Unmanned aerial vehicles can also be used to optimize the delivery process and maintain social distancing. For example, Amazon developed a delivery system to distribute packages by drones in 30 minutes or less. Another example of no-contact delivery is self-driving robots. At the beginning of 2021, Starship Technologies’ delivery robots have already completed around a million autonomous deliveries. 3. Retail With the rise of e-commerce, optimizing operational costs with technology solutions is also growing. Digital supply chains powered by intelligent, data-based processes provide retailers with enhanced transparency, including raw material acquisition, production and last-mile delivery. By adopting intelligent, data-driven processes, retail businesses can not only effectively manage inventory and meet consumer expectations, but they can also synchronize information-sharing across the whole supply chain. As such, retailers are now adopting a 360-degree view of their entire supply chain—from raw material acquisition to production to last-mile delivery. Zara, a fast-fashion retailer that also manufactures its clothing, uses RFID tags to produce more fast-selling clothes and avoid out-of-stock situations. Walmart has invested $14 billion to improve its supply chain, leveraging automation solutions in distribution centers. Final thoughts More than 80% of organizations are preparing to leverage the digital ecosystem in the next few years. Many partners with third-party software vendors to build up smart development teams skilled to drive digital transformation forward. Digitization is a win-win solution for all supply chain stakeholders. The adoption of cutting-edge technologies allows companies to stay responsive to the changing business environment, deliver excellent customer experience and stay ahead of competitors. Are you looking for ways to capture the full potential of the digital supply chain in your organization? We will be happy to discuss your questions. ! Get in touch with us

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