Artificial intelligence (AI) and the Internet of Things (IoT) are powerful partners that can unlock each other’s greatest potential. Over the past few years, there have been numerous successful applications that not only refine processes but also boost productivity and efficiency. Together, they are driving the transformation of entire industries, making them essential tools in the digital revolution.
According to recent reports, AI needs IoT to connect with the physical world, while IoT relies on AI to generate meaningful insights and intelligence. Only when these two technologies are combined can real, impactful changes be made. Looking ahead over the next 5 to 10 years, if we fully harness the potential of AI and IoT, it could lead to hundreds of millions—perhaps even trillions—of dollars in global economic output.
Just as the human body gathers information from the environment and sends it to the brain, AI acts like the brain, while IoT functions like the nervous system. By connecting IoT's vast network of sensors and cameras, massive amounts of environmental data can be collected, organized, analyzed, and transformed into actionable insights by AI. Therefore, researchers must not overlook these systems and data flows but should actively integrate IoT when designing AI solutions.
Moreover, the insights and decisions generated by AI need to be executed through IoT-enabled devices such as robots, drones, and industrial machines. Many real-world examples show that IoT applications incorporating AI capabilities are the fastest way for organizations to gain tangible benefits, including smart operations, predictive analytics, preventive maintenance, and remote control.
For instance, Fanuc of Japan has transitioned from being a product manufacturer to a service provider. Through IoT, it collects operational data from its equipment, uses AI to analyze this information, and provides customers with insights, remote monitoring, and predictive maintenance services. This helps reduce costs and increase equipment uptime.
Similarly, Renfe, a Spanish railway operator, offers high-speed trains traveling at 200 miles per hour, providing an attractive alternative to air travel. However, their real success lies in guaranteeing on-time arrivals. By using IoT to collect data from trains, tracks, and weather conditions, and then applying AI to predict and optimize schedules, Renfe managed to attract 60% of passengers who previously flew on this route.
Another example is Simultaneous Localization and Mapping (SLAM), a real-time machine learning algorithm. When embedded in drone technology, SLAM allows drones to navigate unknown environments, even in dark, signal-free, or GPS-unavailable areas, enabling safe flight.
Thus, combining SLAM (an AI technique) with drones (IoT devices) creates one of the most promising applications in safety, security, and surveillance. Drones equipped with this technology can enter disaster-stricken buildings or fire-damaged homes to locate injured individuals or trapped people.
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