Artificial intelligence (AI) and the Internet of Things (IoT) can show each other's greatest benefits. In the past few years, there have been hundreds of well-developed application examples, not only to gradually improve the program, but to improve productivity and efficiency. Changing the potential of the entire industry is the best partner to drive Digital TransformaTIon.
According to reports, AI must connect with the physical world through IoT, while IoT requires AI to provide viable intelligence and insights. Only by combining AI and IoT can we make real changes and achieve substantial results. Looking forward to the next 5 to 10 years, if you can fully realize the extraordinary benefits of AI and IoT, it will create hundreds of millions to tens of trillion dollars in global output.
Just as the human body perceives the world around it and transmits information to the human brain, it compares AI to the human brain, and IoT is the human body. Linking IoT's myriad sensors and cameras, collecting huge amounts of environmental data, organized, analyzed and transformed into actionable insights by AI. Therefore, researchers should not take these sources and data circulation systems for granted, but must consider and integrate IoT when designing an AI system.
In addition, the actionable insights and decisions provided by AI must also be implemented by IoT through terminal devices such as robots, drones and industrial machines. Many application examples have proven that IoT applications that typically incorporate AI functionality are the fastest way for organizations to benefit, such as networked operations, predictive analytics, preventive maintenance, and remote control operations.
For example, Fanuc of Japan is transforming from a product manufacturer to a service provider, collecting information on the operation of its equipment through IoT, using AI analysis to generate insights and recommendations for business and operations, and providing remote monitoring and predictive maintenance services. Reduce customer costs and improve equipment uptime (UpTIme).
The train of the Spanish railway operator Renfe, with a speed of 200 miles per hour, offers passengers an attractive commute option, but to compete directly with the airline, the real point of success is to provide on-time arrival guarantee.
Renfe first used the IoT to collect data from trains, rails and external weather sources through the IoT route, using AI to predict and optimize, to achieve on-time arrival guarantee, so it was able to win 60% on this route. Passengers who originally boarded the plane.
Synchronous Positioning and Map Creation (SLAM) is a real-time machine learning algorithm that, if built into a drone device, can help them understand the unknown environment, even in dark, full-impedance, Internet-free and GPS-free environments. Safe flight.
Therefore, SLAM (AI) combined with unmanned aerial vehicles (IoT devices) can become one of the most important applications in the field of safety, security and surveillance, such as allowing drones to fly into houses damaged by fire or natural disasters to find injuries or suffer Sleepy person.
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