IoT Trends in 2021: Driving Innovation in Businesses

2021 is a challenging year for many industries, but the Internet of Things technology has already played an active role in shaping business and consumer trends. From healthcare and retail to automotive and manufacturing, every industry is getting smarter with technologies like IoT. Failing to stay competitive in this space can result in significant losses.

The global pandemic was a significant roadblock for IoT growth in 2020. Although a November 2019 forecast predicted that IoT spending would grow 14.9% in 2020, it could only grow 8.2%. Based on forecasting from the International Data Corporation, IoT will return in stride this year and achieve a growth rate of 11.3% from 2020 to 2024.

Recently, a shortage in semiconductors and other IoT components poses questions for IoT’s growth in 2021. Manufacturers will have to adapt quickly to maintain their momentum to remain competitive. Although this shortage won’t last for very long, it will affect projects in the short term.

CES (Consumer Electronics Show) took place online this year to demonstrate the latest innovations. Based on the technologies presented at the event, IoT appears to be far from dying. With millions of people in the United States finding themselves at home during the pandemic, smart home products are in higher demand. DIY smart home product shipments are up 9%, with 99 million units at a value of $15 billion (up 3%).

2021 is seeing IoT-connected devices climb to an astonishing 46 billion. Most of these devices have only one processor and a minimal amount of memory. IoT permeates our society.

Data collection with IoT devices has reached an unprecedented scale. Data science and Machine Learning unite to produce an array of opportunities for advanced IoT data analytics solutions. 

Big Data, AI, and IoT come together to collect already pre-structured data, set data pipelines, and build AI components on top of it all. The importance of this approach will remain relevant for years to come.

A report from Research and Markets forecasts that AI and IoT will surpass a value of $26 billion by 2025. They also demonstrate that AI improves IoT data’s efficiency by 25%, improving analytics by 42% for the industry. AI plays a role in both IoT center and edge networks. At the center of the system, AI can perform predictive analytics and alert users of anomalies.

Getting insights out of the data from IoT solutions is only the first step. AI’s role in IoT systems has much more potential that can be unlocked.

Imagine a factory that utilizes IoT-connected assembly lines to reduce the rate of manufacturing defects in the fabrication process by using AI visual inspection for quality control. As an example, with a much higher cost per mistake, consider a self-driving car. It not only safely brings passengers to their destination but uses that transit data to predict traffic patterns accurately. This data could then be used to build more efficient roads and infrastructure in the future.

Face and voice recognition are other essential elements to this used for biometric verification. AI-driven facial recognition is helpful in various areas, such as detecting whether or not guests are wearing face masks.

AI is becoming more empowered with decision-making as smart homes, smart cities, self-driving vehicles, and manufacturing tasks utilize the technology. However, human supervisors and data scientists are needed to help maintain the system and resolve non-trivial tasks. Explore more on how to build AI software.

The cloud and local servers are not the only places where computation can be performed. Using remote servers can result in transfer delays. Because of this, cloud computing is simply not an option for implementations that require real-time computations like self-driving cars.

Edge IoT is utilized in traffic cameras for pedestrian detection, adaptive traffic lights, vehicle prioritization, parking detection, and electronic tolling. Microsoft, IBM, and Amazon have also invested heavily in edge computing technologies. And there has been an increasing demand for smart IoT devices, fast data processing, and data security.

Amazon’s second-generation AWS IoT Greengrass service has entered use, empowering developers to use Lambda functions with edge devices. It allows developers to perform machine learning and compute tasks within IoT devices.

More IoT solutions will include onboard AI and push some computing from the cloud toward end-point devices. The three main reasons for this are reaction time, cost per cloud processing, and data privacy and security.

We are spoiled by Google’s insights on our search trends. Netflix and Spotify also understand our viewing and listening habits exceptionally well. However, even these predictors can make mistakes, resulting in irrelevant content being placed on our screens. This technology is ever-improving.

Smart home technologies are a sector where personalization is essential. Technology that manages daily home activities requires a highly personal experience to achieve the best customer satisfaction. At CES 2021, Samsung introduced Samsung Bot Handy and JetBot 90 AI+. Home assistance robots are possible thanks to AI and data analysis.

AI growth and edge computing are poised to help this area of the market grow tremendously. To bring Smart Home technologies to the next level, AI’s precision and decision-making need to improve. AI must make choices based on owner habits. Because of the personalization required, generalized data is not enough to train the neural network. Personal data is needed. However, this data can often be very private, and users are unwilling to share it.

The key to this problem may be edge computing, where the data is kept and processed locally on the users’ devices. It may be critical to improving customer perceptions of smart home technologies. A 2019 Statista report indicates that 46% of smart home users describe their experience as intrusive, while 36% describe their experience as fearful. Edge computing can help make customers feel safer while using smart home IoT technology. Check the AI technology trends article.

By 2025, there may well be more than 30 billion IoT Internet connections, amounting to about four devices per person. According to McKinsey, in the B2B sphere, total revenue for 5G IoT modules will increase from about 180 million USD to almost 10 billion USD by 2030.

In July 2020, the 3GPP standards body unveiled the latest set of specifications for 5G connectivity: version 16. This has important implications for 5G IoT, with mobile communication for embedded devices benefitting from the drastically reduced latency and reliability. Although 5G remains far from mainstream adoption, enterprises may consider undertaking this rather costly deployment endeavor with profitable business plans in hand.

Reduced latency will allow connected IoT devices to send and receive data at unprecedented speeds. This will allow for the analysis and management of data to function at a level not possible on older 4G networks.

The value of the technology depends on several factors: the cost of infrastructure, the cost of data transfer, and whether or not certain use cases actually need 5G speeds. Smart cities, transportation, and industrial IoT will be the first technologies to benefit from this technology.

Other network standards evolve like Wi-Fi 6, which allows for higher bandwidth, more simultaneous data streams, and a wider spectrum reaching into 6 GHz. Another technology to connect IoT is the Low-Power Wide-Area Network (LPWAN). Its extremely low power consumption and large effective range make LPWAN an ideal solution for small devices that need a high operating lifespan in remote locations. The LPWAN market size exceeded $2.5 billion in 2020 and is expected to grow at a CAGR of over 60% between 2021 and 2027.

In the low-range connectivity arena, Zigbee takes the lead. Its initiative to increase compatibility among smart home products through a royalty-free connectivity standard could bring real value to users and IoT product manufacturers by setting an industry standard for interoperability. To find more about the most widely used transport protocol – check the article.

According to PwC, Smart city development is poised for growth over the next seven years. By 2025, the market for this technology will reach $2.5 trillion. Senior Director for Business Development & Head of Smart Cities at Qualcomm mentioned that integrated ecosystems are better focused than standalone solutions. There’s also another challenge to overcome: new solutions typically have a legacy component that must be integrated.

Smart cities are second in line for 5G implementation after industrial IoT. This will allow for a stable network with enough bandwidth capacity. The connectivity diversity for smart city solutions is among the top issues for technology.

Data is the most intriguing element. Smart city data is mostly public and can be collected much more quickly than data required for smart home systems. Therefore, an opportunity is there for onboard AI in combination with IoT to prove successful. For example, the Roads and Transport Authority in Dubai utilized AI for crowd management at metro stations.

In the early stages, AI will create suggestions and insights out of the data. As the technology improves, more smart city decision-making will be delegated to AI. This has beneficial implications for traffic management, water, flood monitoring, and video surveillance.

As for video surveillance and streaming – there’s still a privacy issue. Explore how to blur elements in a real-time video stream using AI.

The most accelerated IoT vertical in 2020 was healthcare, no doubt due to the ongoing global pandemic. For years, implementing IoT projects in healthcare had proven cumbersome due to the industry’s highly regulated nature and general passive stance.

There is growing evidence that COVID-19 has led to a digital explosion in the healthcare sector, particularly in hospitals. The US Food and Drug Administration (FDA) in May 2020 issued multiple temporary policies to support digital tools during 2020. For the first time, Germany in October 2020 allowed doctors to prescribe access to digital health apps for specific diseases (e.g., an app that helps treat anxiety disorder).

Supply chain monitoring developer Controlant at the end of 2020 began providing monitoring support for Pfizer and the United States government for vaccine distribution. This is especially important due to the need for these vaccines in transit to be kept with careful temperature control. With AI monitoring technologies, Controlant was able to reduce spoilage and product loss.

One of the applications that surged during the pandemic is telehealth, where a doctor treats a patient via video conferencing. Doctors report that telehealth is often seen as just a first step toward digital diagnostics that lean on IoT devices that diagnose patients from afar. Several hospitals started experimenting with it in 2020. In December 2020, a video of a London surgeon went viral who performed remote surgery on a bandana in California using 5G.

IoT technologies will extend their presence and impact on the industry. It will happen along with other technology trends in Healthcare that bring value to patients, doctors, and management.

One sector that is seeing a great deal of progress is IoT applications in the automotive industries. Firmware over the air (FOTA) allows for wireless firmware updates on embedded systems. This provides a platform to allow for bug fixes easily and replace older versions of firmware. Road condition analysis is another application where IoT can shine in the automotive industry, especially in autonomous vehicles.

Telematics is also a serious topic in automotive IoT. Telematics transforms your vehicle into an IoT device. Emergency calls, GPS, and Bluetooth, are just some of the connections made possible through telematics. This is the first step in the process of achieving V2X (vehicle-to-everything) technology. This can enable features like over-the-air updates.

Vehicle-to-vehicle communication is important for the future of autonomous vehicles as well. If driverless cars can communicate with one another, they can better maintain a safe distance and share other important data.

Manufacturers are looking to remain competitive and explore industrial internet of things (IIoT) applications. Embedded edge networks are becoming utilized due to their ability to maintain greater efficiency while being powered by artificial intelligence. This is one of many industrial IoT use cases. In fact, the role of AI in this sector is expected to reach a value of up $16.7 billion by 2026.

Predictive maintenance is also another major benefit made possible with machine learning and IoT technology. With existing data, AI algorithms can identify when to implement preventative measures before a machine requires repairs.

Computer vision for visual inspection is also a critical technology that can reduce costs and improve efficiency. ML algorithms are more efficient at visual inspection when given the right training data and hardware than humans. Companies like BMW are already using this technology to ensure quality control for their automotive parts.

Advancements in the Internet of Things technology are propelling us farther than ever thought possible. Although global pandemics and component shortages may slow down progress in the short term, it is important to invest in these growing technologies in order to remain competitive in the long term. Without artificial intelligence, machine learning, embedded systems, and comprehensive IoT frameworks, businesses won’t keep up with an increasingly interconnected world. By taking advantage of these powerful technologies, companies can reap the benefits of smart features, functionality, and productivity from connected IoT ecosystems.

Written by Oleksii Tsymbal, Chief Innovation Officer at MobiDev

Photo by CHUTTERSNAP on Unsplash