An in-depth guide to Artificial Intelligence of Things (AIoT)?
The Internet of Things, or IoT, refers to a network of interconnected devices and machines that can ensure data transfer without human intervention. Over the past decade, IoT has brought about major changes in the way people approach business operations and personal tasks in their daily lives. At the same time, AI has emerged as a powerful force for change in the technological realm.
Accordingly, discussions on artificial intelligence of things (AIoT) are becoming more active. The convergence of artificial intelligence and the Internet of Things leads to the birth of AIoT. But it’s also important to remember that people are likely wondering how AI and IoT can complement each other. Let’s learn more about AIoT’s working mechanisms and its benefits and applications in the real world.
Combining two powerful technologies with AIoT
The best way to understand the importance of artificial intelligence of objects is to unpack the definition of objects. You can find better explanations for questions like “What is artificial intelligence of things?” Identifying the strengths of AI and IoT as core components, artificial intelligence (AI) is an important discipline in computer science that focuses on developing smart systems that can simulate human intelligence.
AI enables machines to perform tasks such as understanding, perception, and reasoning like humans. The Internet of Things, or IoT, refers to a network of connected devices or things that enable real-time data collection and transmission through sensors or software.
Artificial Intelligence of Things allows you to combine the power of AI and IoT. As a result, AIoT can help create new systems that can leverage AI capabilities to process data collected and generated by IoT systems. The power of AIoT applications lies in combining machine learning models, connectivity, and data transfer capabilities with the IoT. When you integrate AI into an IoT system, the system no longer works solely on collecting and transmitting data. IoT systems can leverage the power of AI to deeply understand and analyze the data they collect and generate.
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Working mechanism of artificial intelligence of things
The next important aspect of the guide to artificial intelligence of things is an overview of the mechanisms of operation. Most examples of artificial intelligence in things demonstrate that AIoT devices work by embedding AI in infrastructure components. Infrastructure components such as chipsets and programs are connected to each other through IoT networks.
AIoT systems also leverage APIs to ensure seamless operation and communication between hardware, platform components, and software. When IoT devices operate, they collect data and AI analyzes the data to extract valuable insights. AIoT in Action also highlights two common approaches for setting up AIoT systems. Below is an overview of two major implementations of AIoT systems:
The first AIoT example to consider to understand the workings of AI of Things is cloud-based AIoT. Cloud-based IoT involves collecting and processing data from IoT devices through cloud computing platforms. Connecting IoT devices to the cloud is important as it serves as an ideal place to store, process, and access data for a variety of applications and services.
The four important layers of a cloud-based AIoT system include device layer, connection layer, user communication layer, and cloud layer. The device layer allows you to find different types of hardware, such as beacons, automotive, sensors, embedded devices, and tags. Things for cloud-based AIoT The infrastructure for artificial intelligence in AIoT also includes a connectivity layer with field and cloud gateways. It plays an important role in connecting cloud storage to controllers, intelligent devices, and sensors.
The cloud layer also plays an important role in powering cloud-based AIoT as it ensures data processing through components such as AI engines, data visualization, API data access, data storage, and analysis. On the other hand, the user communication layer primarily includes mobile applications and web portals.
Another popular implementation of AIoT systems that has garnered attention from technology experts is edge-based AIoT. Search for answers to “What is Artificial Intelligence of Things?” Additionally, special features will point the way toward edge-based AIoT. This type of AIoT implementation facilitates IoT data processing within the edge or proximity of IoT devices. Edge-based AIoT systems therefore require lower bandwidth for data transmission, avoiding potential delays in data analysis.
Edge-based AIoT systems include three main layers: collection terminal layer, connection layer, and edge layer. Each layer of edge-based AIoT applications offers unique capabilities. For example, the collection terminal layer includes all hardware devices such as automobiles, sensors, embedded devices, tags, and mobility devices. Hardware devices in this layer are connected to the gateway via existing power lines.
Above this, the connectivity layer includes field gateways that connect to the collection terminal layer via existing power lines. Finally, the edge layer of an edge-based AIoT system provides capabilities for effective data storage, processing, and insight generation.
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What are the benefits of combining AI and IoT?
If we take a closer look at AI of Things examples, we can see that AIoT systems allow us to take full advantage of the best features of AI and IoT. It is important to understand the different ways artificial intelligence and IoT can work together. Although AI and IoT are separate technologies, some may have doubts about the possibility of them working together. AI and IoT have made significant technological advancements and have served as valuable tools for technological development in a variety of industries.
The combination of AI and IoT ensures that IoT devices can expand their utility beyond data collection and delivery. IoT devices will develop capabilities to better understand and evaluate data. Businesses, economies, and industries around the world must take note of the benefits of AIoT.
Improved operational efficiency
AIoT can help businesses achieve better operational efficiency. The combination of AI and IoT generates operational insights at a faster rate, helping you detect and resolve problems faster. As a result, AIoT systems can also play an important role in improving the operational efficiency of industrial automation operations. For example, AIoT applications involving cameras can help with quality control in industrial automation. AIoT also ensures effective tracking and compliance with specific regulations and guidelines.
Reduce operating costs
AIoT devices can also have a significant impact on reducing operational costs. Smart systems with the power of AI and IoT can ensure efficient use of resources. For example, smart building applications can help adjust temperature and lighting controls based on occupancy.
Therefore, AIoT systems can play an important role in fundamentally improving machine analysis and preventive maintenance. Sensors and cameras can monitor mechanical parts and identify the ideal time to introduce improvements or implement maintenance schedules.
Companies across a variety of industries struggle with risk management issues. Intelligent distributed systems based on AIoT can predict future risks while suggesting preventive measures for the future. The best AIoT practice for risk management points to crowd analytics in public spaces.
AIoT systems can also support comprehensive analysis of water levels and employee safety analysis according to desired goals. Using AIoT, organizations can stay one step ahead in preparing for and managing future potential risks. For example, insurance companies have been leveraging AIoT applications to collect data from machines and elements to effectively manage insurance risks.
Flexible real-time monitoring
AIoT also makes it easier for businesses to monitor their systems in real time, saving time and helping prevent business downtime. Consistently monitoring different systems through AIoT makes it easier to detect anomalies and make predictions or decisions about them.
Most importantly, artificial intelligence of things (AIoT) can achieve consistent, real-time monitoring without human intervention. As a result, you get faster results. One notable advantage of real-time monitoring using AIoT systems is the use of cameras for remote detection of leaks.
What are the main applications of AIoT?
Artificial intelligence of things could mark the beginning of a new revolution in technology. This is the answer to “What is artificial intelligence of things?” There will be interest in using cognitive power in consumer electronics. However, we can also find broader applications for AIoT that have the potential to create a seamless technological environment. Below are some of the most prominent applications of AIoT that can provide a new definition of the capabilities of AI and IoT.
Starting from smart cities to smart homes and offices, AIoT could have a huge impact on the world we see in the future. Representative examples of artificial intelligence in things point out how sensors can collect data to improve quality of life operational efficiency and ensure cost-effective improvements. Smart retailers can use AIoT to recognize shoppers’ faces with cameras and determine whether shoppers have scanned items at self-checkout before leaving the store.
Cameras are one of the widely used IoT devices, so it is important to understand that AIoT use cases are incomplete without video surveillance. Video surveillance with AIoT applications leverages the power of AI and IoT for smarter video surveillance and security. AIoT uses machine learning algorithms to automatically detect objects and recognize people by analyzing data from camera video feeds in real time.
Another notable area where artificial intelligence of things could have a huge impact on technology is manufacturing. AIoT systems can augment the Industrial Internet of Things (IIoT) to improve real-time monitoring of machines and effectively detect defective parts.
You may encounter traditional machine vision systems that provide quality control and fall behind in terms of efficiency. However, AIoT can solve these problems by providing the power of deep neural networks. As a result, AIoT systems can use deep neural networks to detect defective parts in real time through comprehensive analysis of live video feeds.
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final words
An overview of AIoT, Artificial Intelligence of Things, shows why it deserves to be one of the top trends in the technological sphere. Artificial Intelligence and Internet of Things are two of the most powerful technologies that have had a distinct impact on various industries. At the same time, it is important to consider the possibility of combining AI and IoT to create AIoT.
With the power of AI, IoT systems will be able to process and analyze data collected and generated by IoT devices. Interestingly, the success of various AIoT cases demonstrated in the real world proves that AIoT has a bright future. Improve your knowledge of AIoT today with a deeper understanding of AI and IoT fundamentals.
