These transformative technologies are fueling growth opportunities in a variety of industries, including healthcare, manufacturing and transportation. Both AI and IoT are the key to revolutionizing smart industries and delivering intelligence and connected systems that will move us into the next industrial revolution.
What is AIoT?
IoT devices use the internet to gather and exchange data and communicate with other devices. Physical objects have sensors, processing abilities, software and other technologies that facilitate communication over the internet or through other communications networks. Each day, IoT devices amass about 1 billion GB of data.
According to Transforma Insights, the number of IoT devices is expected to skyrocket from 7.6 billion in 2019 to 24.1 billion in 2030. The revenue potential from this growth amounts to $1.5 trillion. The data will grow alongside IoT adoption, however.
We’re already working with an unprecedented volume of data that needs to be gathered, processed and analyzed for use. As the volume grows, it’ll become increasingly difficult to realistically manage and analyze data for real-time insights – even with the help of IoT.
AI offers a solution. This self-learning technology can pair with IoT devices to gain data insights in real time, allowing businesses to maximize the power of their information. Combining AI and IoT is a key step in the widespread adoption of these technologies and harnessing their power.
Principles of AIoT
IoT relies on the following principles:
- Collecting data from devices and sensors
- Storing data is a scalable storage system like a data lake
- Processing and analyzing data for insights
- Using those insights to inform decisions
- Controlling devices according to established best practices
AI and IoT act as an interim for the controller and the device by making decisions based on the most accurate and recent data. Instead of taking the time to process data and present it to humans to make decisions, AI analyzes the data in real time and can apply the information to quick decisions without the need for a human decision-maker.
The capabilities of IoT are enhanced by intelligence, but they’re also capable of analyzing data in batches or in real time. AI can determine how to prioritize data effectively and make informed decisions on which information requires a rapid response and which data can be stored and analyzed for future decisions.
In the real world, AIoT could be a device with a camera and an image sensor that would analyze the entire data field to identify and transmit chosen images to the IoT system for analysis. With the capabilities of AI, the camera would only send the frames in which the target image was detected, reducing the volume and burden of data on the system.
In addition, AI is continuously learning and improving using deep-learning models and neural networks. These can identify critical issues and errors up to the minute, providing a rapid response prior to an accident or catastrophe. Otherwise, it’s up to humans to wait for the information and react to events, rather than taking a proactive approach.
4 benefits of AIoT
AIoT has incredible potential in multiple industries. Here are the major advantages of AIoT:
1. Operational efficiency
AIoT improves on traditional methods by allowing businesses to reach maximum operational efficiency. AIoT devices can generate and analyze data, gleaning patterns with machine-learning. The result is rapid insights to make real-time decisions and fix problems before they start. AIoT also improves automation to reduce the burden of repetitive tasks, freeing people to focus on mission-critical work.
2. Real-time monitoring
The real-time monitoring of systems with AIoT saves time and reduces business disruptions. AIoT devices continuously supervise the system to detect problems and anomalies, making decisions as needed without human intervention. Any delays while humans wait for information and process it can be reduced.
3. Reduced operational costs
AIoT devices and systems are key components in reducing overall costs and improving the efficiency of resources. Automated adjustments of parameters like temperature, light and maintenance tasks optimize equipment and processes to make the entire system more efficient and reduce wasted resources.
4. Risk management
Risk management is necessary in all industries. Intelligent systems can make informed assessments of risks and predict possible problems to take preventative actions based on historical information. Organizations are better equipped to stay ahead of any concerns and mitigate problems because they’re drawing on a wealth of industry and business data, rather than their own experience.
Key technologies that employ AIoT
AI and IoT together can create more efficient and scalable intelligent systems that solve business challenges. Here are the technologies that hold the most potential for AIoT capabilities.
Artificial intelligence allows devices to learn, reason, analyze and process information in a way that mimics the human mind. Over time, the system learns and becomes smarter, leading to better decisions that can be made without human input.
2. 5G Network
5G is the next generation of mobile networks that offers high-speed transmission with near-zero lag, eliminating the latency that often occurs with data transmissions. Having data travel faster allows for rapid real-time data processing.
3. Edge computing
Edge computing is a complement to the capabilities of cloud-based data centers and IoT devices. It processes data at the network edge, close to its collection point and end user, eliminating the delay that occurs when data must be transmitted to the data storage center and the congestion from network traffic that can limit efficiency.
4. Big data
Most of the benefits of AIoT tie back to the collection of data, which is only increasing in volume. All of these internet-connected sources are collecting more and more data, all of which can have potential value for businesses. But it’s useless without the ability to use it effectively, which is where AIoT shines.
Applications for AIoT
Wondering how AIoT can be useful in the real world? Here are some of the most promising applications for AIoT:
Medical wearable devices, such as smart watches, are revolutionizing the healthcare industry. These devices can monitor and track user performance, health parameters and preferences to improve exercise performance, diets and sleep patterns. While this may be used for entertainment for the average person, the healthcare industry can use wearables with physicians and patients to help them stay on top of their health.
Autonomous and semi-autonomous vehicles are self-driving vehicles that can navigate the roadway and drive from origin to destination without human input. Self-driving vehicles have numerous applications not just for consumers but for industries like shipping, public transportation, emergency response and more.
Several technologies need to be implemented and refined before vehicles can operate autonomously, however, including sensors and cameras that rely on both AI and IoT to collect environmental data from multiple sources and analyze it rapidly to make calculated decisions, just like a human driver would.
Smart cities are a possible solution to the growing population and congestion in urban centers, which has the potential to affect quality of life negatively. AIoT sensors and devices are necessary for real-time traffic analysis in smart city applications, which can improve traffic flow in crowded cities.
Smart traffic monitoring uses sensors to assess congestion levels and conduct crowd analysis to detect possible accidents – and report them if they occur – predict congested traffic areas, reroute vehicles to optimize routes, and respond to traffic violations.
Smart buildings are another element of smart cities that can improve quality of life and efficiency. IoT sensors are currently used in smart buildings to optimize energy usage for temperature control and lighting, all based on occupancy, to keep residents comfortable without driving costs up unnecessarily.
This technology is also used to enhance safety and security in the building, such as by improving the lighting in certain areas to deter crime or by filtering the air in busy areas to reduce airborne pathogens.
AIoT can enhance video surveillance systems by making them smarter and more efficient. Conventional systems require human operators to monitor video feeds to identify suspicious behavior. Operators may miss crucial events due to subjective viewpoints, poor reaction times, limited attention and drowsiness, reducing the efficacy of a surveillance system. AIoT uses machine learning to analyze the data as the events happen, detecting objects, identifying people and predicting events for fast decisions and interventions.
One of the most notable applications for AIoT is with the Industrial Internet of Things. Manufacturing has already been leveraging IoT devices for real-time monitoring and maintenance of industrial machinery and quality control, as well as automation. AIoT takes this capability a step further with predictive maintenance capabilities, more precise automation capabilities and better quality control.
What’s next for AIoT?
AI is a critical factor in the widespread adoption of IoT devices and their potential uses. As we move toward a smarter and more connected future, AIoT offers enhanced capabilities with devices that can identify, predict and react to events without human intervention.