Artificial Intelligence unlocks the true potential of the Internet of Things by enabling networks and devices to learn from past decisions, predict future activity, and continuously improve performance and decision-making capabilities.
Over the past decade, the Internet of Things has been steadily adopted throughout the business world. Leveraging IoT devices and their data capabilities to build or optimize your business has ushered in a new era of business and consumer technology. Now, as advances in artificial intelligence and machine learning unlock the possibilities of IoT devices using the “Artificial Intelligence Internet of Things” (AIoT), the next wave is coming.
Consumers, businesses, economies and industries that adopt and invest in AIoT can harness its power and gain a competitive advantage. IoT collects data and AI analyzes it to simulate intelligent behavior and support the decision-making process with minimal human intervention.
The Internet of Things allows devices to communicate with each other and take action based on those insights. The performance of these devices depends on the data provided. To be useful for decision making, data needs to be collected, stored, processed and analyzed.
This creates challenges for organizations. As IoT applications increase, businesses are struggling to process data efficiently and use it for real-world decisions and insights.
This is due to two issues: cloud and data transmission. The cloud cannot scale to handle all data from IoT devices, and there is limited bandwidth to transfer data from IoT devices to the cloud. Regardless of the size and complexity of the communication network, the volume of data collected by IoT devices can cause delays and congestion.
Some IoT applications rely on fast, real-time decision-making, such as self-driving cars. To improve efficiency and safety, self-driving cars need to process data and make instant decisions (just like humans). They are not limited by latency, unreliable connections, and low bandwidth.
Self-driving cars aren’t the only IoT applications that rely on such rapid decision-making. Manufacturing is already integrating IoT devices, and in emergency situations, delays or delays can impact processes or limit capacity.
In terms of security, biometrics are often used to restrict or allow access to specific areas. Without fast data processing, there can be delays that impact speed and performance, not to mention risks in emergency situations. These applications require ultra-low latency and high security. Therefore, processing must be done at the edge. Transferring data to the cloud and back is not feasible.
Every day, IoT devices generate approximately 1 billion GB of data. By 2025, the global number of IoT devices is expected to reach 42 billion. As the network grows, so does the data.
As needs and expectations change, IoT is not enough. Data is growing, creating more challenges than opportunities. Barriers limit the insights and possibilities of all data, but smart devices can change this and allow organizations to unlock the true potential of their organizational data.
With artificial intelligence, IoT networks and devices can learn from past decisions, predict future activities, and continuously improve performance and decision-making capabilities. AI allows devices to "think on their own," interpret data and make real-time decisions without the delays and congestion caused by data transmission.
AIoT brings a wide range of benefits to organizations and provides powerful solutions for intelligent automation.
Some industries are limited by downtime, such as the offshore oil and gas industry. Unexpected equipment failure can lead to costly downtime. To avoid this, AIoT can predict equipment failures in advance and schedule maintenance before serious problems occur on the equipment.
Artificial intelligence processes the large amounts of data entering IoT devices and detects underlying patterns more effectively than humans. Artificial intelligence with machine learning can enhance this capability by predicting operating conditions and improving outcomes.
Natural language processing is constantly improving, making communication between devices and humans more effective. AIoT can enhance new or existing products and services by enabling better data processing and analysis.
Risk management is necessary to adapt to the rapidly changing market environment. Artificial intelligence with IoT can leverage data to predict risks and prioritize ideal responses, improving employee safety, mitigating cyber threats, and minimizing financial losses.
AIoT has revolutionized many industries, including manufacturing, automotive and retail. Below are some common applications of AIoT in different industries.
Manufacturers have been leveraging the Internet of Things for equipment monitoring. Going a step further, AIoT combines data insights from IoT devices with artificial intelligence capabilities to provide predictive analytics. With AIoT, manufacturers can proactively participate in warehouse inventory, maintenance, and production.
Robotics in manufacturing can significantly improve operations. Robots can be implanted with sensors for data transmission and artificial intelligence, so they can continuously learn from data, saving time during the manufacturing process and reducing costs.
Retail analytics takes data points from cameras and sensors to track customers’ movements and predict their behavior in a brick-and-mortar store, such as how long it takes to reach the checkout. This can be used to recommend staffing levels and improve cashier productivity, thereby increasing overall customer satisfaction.
Major retailers can use AIoT solutions to grow sales through customer insights. Data such as mobile-based user behavior and proximity detection provide valuable insights that can be used to deliver personalized marketing campaigns to customers as they shop, thereby increasing foot traffic to brick-and-mortar stores.
AIoT has a wide range of applications in the automotive industry, including repairs and recalls. AIoT can predict malfunctioning or defective parts and can combine data from recall, warranty and safety agencies to see which parts may need to be replaced and provide service checks to customers. Ultimately, the vehicle gains a better reputation for reliability and the manufacturer gains the trust and loyalty of its customers.
Self-driving cars are one of the most well-known and possibly the most exciting applications of AIoT. Through artificial intelligence and the intelligent Internet of Things, self-driving cars can predict the behavior of drivers and pedestrians in a variety of situations, making driving safer and more efficient.
One of the main goals of high-quality health care is to extend it to all communities. Regardless of the size and complexity of the healthcare system, physicians are facing increasing time and workload pressures and spending less time with their patients. Providing high-quality health care without administrative burden is a daunting challenge.
Healthcare organizations also generate large amounts of data and record vast amounts of patient information, including imaging and test results. This information is valuable and necessary to improve the quality of patient care, but only if healthcare facilities can quickly access it to inform diagnostic and treatment decisions.
Combining IoT with artificial intelligence has many benefits for these disorders, including improving diagnostic accuracy, enabling telemedicine and remote patient care, and reducing the administrative burden of tracking patient health in facilities. Perhaps most importantly, AIoT can process patient information to ensure that patients are effectively triaged, thereby identifying critically ill patients faster than humans.
Artificial intelligence and the Internet of Things are the perfect combination of capabilities. Artificial intelligence enhances the capabilities of the Internet of Things through intelligent decision-making, and the Internet of Things promotes the capabilities of artificial intelligence through data exchange. Ultimately, the combination of the two will pave the way for a new era of solutions and experiences that will transform business across numerous industries and create new opportunities together.
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