Use Cases

Beginners Guide to Artificial Intelligence of Things (AIoT) in 2022

This blog explains Artificial Intelligence of Things (AIoT) Trends, an overview of the applications of AIoT in 2022, and the benefits of combining AI with IoT.
Halime Yilmaz
4 Minutes

Artificial Intelligence of Things (AIoT) Trends and Use Cases

The rapid development of AI and IoT has prompted a new wave of interest in AIoT. The combination of artificial intelligence (AI) with the Internet of Things is known as "Artificial Intelligence of Things," or AIoT for short. How exactly can these two technological advancements complement one another to help businesses accomplish their goals? 

In this blog, we will provide an overview of the applications of the Artificial Intelligence of Things (AIoT) in 2022 and the benefits of combining AI with IoT.

Let’s discover the fundamentals of the artificial intelligence of things together with this comprehensive guide.

What is Artificial Intelligence of Things (AIoT)?

The term "Artificial Intelligence of Things" (AIoT) refers to the integration of IoT connections with AI-derived data-driven knowledge. This cutting-edge innovation is based on the incorporation of AI into the existing Internet of Things infrastructure.

The Artificial Intelligence of Things (AIoT) is a framework for optimizing IoT processes, facilitating better communication between humans and machines, and boosting data management and analytics capabilities.

The Internet of Things (IoT) and artificial intelligence (AI) work together to enable the use of the data generated by dispersed nodes via the application of AI methods such as machine learning and deep learning. Thus, machine learning skills are relocated to be closer to the data itself. The increased scalability, robustness, and efficiency made possible by this approach is known as Edge AI or Edge Intelligence.

In other words, IoT and AI are two different technologies that have a big impact on businesses by making them smarter and more connected. IoT is the main body, and AI is the brain, making decisions that control how the body works.

To understand why AI and IoT need to work together, we must first look at what is meant by the "internet of things."

What is the Internet of Things (IoT)?

The phrase "Internet of Things" (IoT) refers to the collective network of linked devices as well as the technology that enables the communication between devices and the cloud, as well as between the devices themselves. This communication can also take place between the devices themselves. Since the invention of cheap computer chips and high-bandwidth communications, billions of devices are now connected to the internet. This means that everyday items like toothbrushes, vacuum cleaners, cars, and machines can use sensors to collect data and respond intelligently to users.

For example, you have a smartwatch on your arm. This smartwatch has sensors that detect the distance you go, the steps you take, and how your heart beats while doing these activities. This data collected here is analyzed by a client (computer, mobile phone, etc.) and helps us organize our lives. The communication between these two devices is the most basic feature that makes up the internet of things.

Edge Computing IoT 

In recent years, the concept of "edge computing" has become very popular. It is a key part of many future technologies, like the Internet of Things (IoT) and artificial intelligence. Edge computing is the main thing that makes the AIoT work because it moves data processing from the edge of the network.

Edge Computing supports efficient, scalable, resilient, on-device data processing for low-latency use cases. Machine Learning and Deep Learning were once constrained to the cloud because of the high computing resources needed to handle ML jobs.

Emerging AIoT applications may be effectively supported at the network edge by using edge intelligence. Edge computing is critical for clever IoT applications' quick processing and minimal latency.

The Benefits of Combining AI with IoT

How do artificial intelligence and the internet of things operate together? Is it not a little strange to see two distinct technologies working in conjunction with one another rather than in competition with one another? The Internet of Things (IoT) and artificial intelligence (AI), on the other hand, are two distinct technical developments that are each independently transforming sectors all over the globe in their way. On the other hand, the advantages of combining them become much more significant.

The main reason why AI skills are used in this situation is for real-time analysis of data acquired by IoT systems. Thus, AI systems include IoT connection and data transfer competence into machine learning models.

When AI is combined with IoT, the latter expands beyond its original information-gathering and delivery purposes. In addition, IoT gadgets have a greater capacity to understand and assess the retrieved data.

Businesses, sectors, and economies are all susceptible to radical changes brought on by IoT and AI. The combination of AI knowledge with the Internet of Things enables the creation of autonomous decision-making devices.

  • Increases Productivity in The Workplace

Through the use of AIoT, businesses can maximize their efficiency in all areas of operation. Through the use of machine learning techniques, AIoT-enabled devices can create data, analyze it, and spot trends. Because of this, it can rapidly give operational insights, identify and resolve issues, and further automate labor-intensive procedures. Companies can improve their service while cutting costs by using AI to do monotonous jobs.

The use of cameras for quality control in industrial automation is one such example of the automation of vision-based quality inspection. Many programs attempt to monitor and guarantee compliance with rules and regulations.

  • Easy Real-Time Monitoring

Monitoring of systems in real-time may help in the reduction of costly business disruptions while also saving time. It requires regular monitoring by the system to identify any problems and then either make predictions or choose actions based on those findings. In addition, there is no need for any kind of human interaction, which leads to speedier and more objective findings.

  • Risk Management

It's crucial for businesses of all sizes and in all fields to have a solid risk management plan in place. Distributed, intelligent systems can foresee potential dangers and even mitigate them. Analysis of water levels, employee safety, or public crowds is just a few examples.

Organizations may anticipate and respond to future threats with more agility with the aid of AIoT technologies. Insurers have just recently begun to employ such software to oversee the risks associated with machinery and whole plants.

  • Reduces Costs

Intelligent AIoT devices and systems can save expenses. Intelligent systems improve resource efficiency.

In smart factories, AIoT devices are used for preventative maintenance and equipment analysis. Here, sensors and cameras monitor machine components to minimize failure and business disruption.

AIoT Applications in 2022

The AI of things allows AI adoption across sectors to tackle actual business challenges more efficiently than before. AI and IoT may enhance efficiency and save expenses.


In the IoT (Industrial Internet of Things), AIoT technologies are widely used. Such smart systems are employed in the manufacturing industry to monitor machines in real-time and identify faulty components. There has been a shift away from using traditional machine vision systems for quality control and toward using deep learning applications instead. Real-time footage from low-cost cameras is analyzed using AI models to train deep neural networks to identify faulty components as they occur.

Tracking Traffic

There has been a great increase in the use of sensors and devices based on the artificial intelligence internet of things (AIoT) for real-time traffic monitoring. Smart drones are one kind of AI system that may be used to analyze crowds and traffic conditions. AIoT systems that rely on computer vision can detect and report all sorts of transportation-related incidents, from accidents and traffic offenses to stalled cars and more.

Video Surveillance

Video surveillance for safety reasons is greatly improved by the use of AI and IoT. Human operators are needed to keep an eye on many video streams in conventional Video Management Systems (VMS).

This indicates that the video's success is contingent on factors like uneven focus, skewed evaluation, and slow responses. By using machine learning algorithms, the AIoT can conduct real-time analysis of video streams, identify objects, and detect people and events with absolute precision.

For instance, Cameralyze has developed an AI-based Human Detection solution that can accurately and quickly detect people in an image, video, or live. Cameralyze's Person Detection system uses artificial intelligence to recognize people with certain characteristics, such as those who wear glasses, have tattoos, or are on a restricted list. 

As a result of Cameralyze's intuitive interface, it has found widespread use in a wide variety of public settings, including but not limited to transit hubs, airports, entertainment venues, retail outlets, tourist attractions, banks, and corporate buildings.

Last Words

AIoT combines the strength and efficiency of both AI and IoT, which makes it suited for tackling particular challenges using intelligent systems that are deployed across several locations. As we mentioned above, it is becoming more common for businesses across a variety of sectors, including manufacturing, healthcare, security, finance, and insurance, to use AIoT-driven solutions. There is a good chance that technological progress will continue in the future. It seems all conditions are now favorable for this.

Cameralyze helps businesses of all sizes to develop AIoT for computer vision. Cameralyze is the top no-code computer vision platform for building, deploying, and scaling AIoT applications. It combines no-code design with automated, enterprise-grade infrastructure and is employed by prominent companies all over the globe.

The first platform for no-code AI-based computer vision, Cameralyze, allows anybody to easily create and deploy processes and apps for vision-based AI.

Anyone with a basic understanding of technology can build an application from scratch according to their requirements using the drag-and-drop feature of the Cameralyze platform.

By launching the application you created in AI Studio with a single click on your Edge Devices, you can use vision systems without storing or transferring image or video data and without the need for any further operations or technical expertise!

Become a part of the future by taking advantage of the solutions provided by Cameralyze. Start a free trial now!

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