Artificial Intelligence of Things 

In 1982, a modified Coke machine at Carnegie Mellon University became the first connected smart appliance, reporting its inventory and temperature back to Coca Cola, ushering in the world of connected technology. A.I. and IoT are a perfect example of two technologies that complement one another and should be tightly connected.

In the fast-growing world of IoT, which connects and shares data across a vast network of devices or ‘things,’ organizations win with analytics. For its ability to make rapid decisions and uncover deep insights as it ‘learns’ from massive volumes of IoT data, AI is an essential form of analytics for any organization that wants to expand the value of IoT.

Jared Newman


Today, we live in a world where there are more connected things than human beings. According to Business Insider Intelligence, there will be more than 55 billion IoT devices by 2025, up from about 9 billion in 2017. The rapidly expanding Internet of Things extends connectivity and data exchange across a vast network of portable devices, home appliances, vehicles, manufacturing equipment, and other things embedded with electronics, software, sensors, actuators, and connectivity. From consumer wearable devices to industrial machines and heavy machinery, these connected things can signal their environment, be remotely monitored and controlled—and increasingly, make decisions and take actions on their own.

This ecosystem of connected devices, people, and environments generate a torrent of complex data. For instance, today’s cars and trucks are like data centers on wheels, equipped with sensors that can monitor everything from tire pressure to engine performance, component health, radio volume, driver actions – even the presence of obstacles or rain on the windshield. Autonomous, self-driving vehicles may put out as much as 1GB of data per second.

However, being connected and exchanging masses of data is only the start to the IoT story.

A smart, connected device is made up of four layers:

  • Physical elements such as the mechanical and electrical parts.
  • Smart elements such as sensors, processors, storage, and software.
  • Connectivity elements such as ports, antennas, and protocols.
  • Onboard analytics, in some cases, to train and run AI models at the edge.

But by itself, connecting things does not promote learning. It paves the way, but that’s just the foundation. At the most basic level, the data generated from IoT devices are used to trigger simple alerts. For example, if a sensor detects an out-of-threshold condition, such as excessive heat or vibration, it triggers an alert and a technician checks it out. In a more sophisticated IoT system, you might have dozens of sensors monitoring many aspects of operation.


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