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Tech explained: The AI of Things

Tech Explained

How AI is allowing objects to develop a more independent functionality

At Springwise, we have seen applications for both artificial intelligence and the Internet of Things growing at a tremendous rate. From using AI to create a digital economist to smart beehives, these two technologies are everywhere.

IoT innovations are now incorporating AI to become “smarter”. In fact, a number of major IoT developers are already offering integrated AI capabilities, such as machine learning analytics, in their products. So, what does this mean for the future of both AI and the IoT?

How IoT and AI work together: Research firm Gartner estimates that by 2022, more than 80 percent of enterprise IoT projects will feature an AI component. IoT devices collect huge amounts of data and AI allows these connected objects to go from data collectors to learning machines. It allows the creation of “connected intelligence” – devices that can adapt and respond to user conditions.

Traditional methods of analysing data and responding are too slow to process the huge amounts of real-time data coming from IoT devices. Using AI allows the rapid identification of patterns in data sets and the ability to run predictive analytics to find connections between data sets. Because AI can process data in real time, it also enables IoT devices to respond quickly to changing conditions and to make “decisions.”

AI of Things in action: Perhaps the ultimate example of AI-enabled IoT is the autonomous vehicle, which records and analyses hundreds of thousands of data points every minute to make decisions about driving. But AI-augmented IoT devices are also being used in hundreds of every day applications.

Smart home products like security cameras and thermostats employ AI to learn about how individuals live their lives and then respond. For example, a number of security cameras use AI to recognise people’s faces and let users know exactly what is going on in their house, including the ability to tell what people are saying and to learn users’ schedules to avoid false alarms.

Intelligent refrigerators like the LG InstaView ThinQ use internal cameras to keep track of what is in your fridge and AI to purchase groceries that are running low, and suggest recipes based on users’ likes and dislikes and what food is in their refrigerator.

AI is even being used in toys. Hello Barbie uses natural language processing, machine learning and AI-powered analytics to respond appropriately when a child talks to it. The doll records what is said to it and transmits this to the manufacturers’ servers, where an AI algorithm analyses the child’s speech and choses an appropriate response. The response is then transmitted back to Barbie, who speaks – all in under a second.

Industrial IoT is also benefitting from AI. Here, AI-powered IoT is used to improve operational efficiency by closely monitoring data on machine performance. Patterns in the data can be analysed using AI to predict when equipment needs maintenance or is about to fail.

Similar algorithms are also used to help factories and other types of networks run more efficiently by managing supply chains. In fact, machine learning is now integrated with most major industrial IoT platforms, such as Microsoft Azure IoTGE Predix and PTC ThingWorx.

What’s next: It may soon be difficult to find an IoT device that does not use AI in some way. Products will increasingly come to resemble services, where the information gathered by smart devices informs decision making. The merging of AI and IoT will eventually allow objects and devices to reach their full potential.