Internet of Things (IoT) and Machine Learning Primer: What You Need to Know

Written by Bart Nachimow

October 7, 2019

The Internet of Things (IoT) and machine learning (ML) are reshaping the world of computing. From corporate data to consumer devices, these phenomena have been the subjects of intense development. They’re not new, with the IoT having been recognized for around 20 years and the concept of machine learning existing since the late 1950s. However, today, they are advancing in their sophistication and coming together to realize innovations such as online recommendations, fraud detection and self-driving cars.

What Is the IoT?

The IoT is essentially an interconnected web of objects, linked to the Internet. A lot of the “things” in the IoT are industrial sensors like thermometers or weather reading devices. Other things are devices used every day, including cellphones, wearable fitness devices and headphones as well as refrigerators, washing machines, coffee makers and thermostats. Even cars and airplanes are becoming part of the IoT. It is uncertain how many billions of objects are now connected, but that number is growing rapidly. 

Data from all these devices are everywhere. While concerns of privacy and security do exist, the information has a broad range of uses. A coffee maker can be activated by an alarm clock, a wearable device can measure an employee’s productivity and industrial systems can measure energy use or air pollutant emissions. 

What Is Machine Learning?

The conventional view of machines is they do what they’re programmed to do. ML disrupts this notion, taking data analysis to a new level. A branch of artificial intelligence (AI), it automates analytical model building so that machine systems can learn from data they receive.

As a result, computers can theoretically learn to complete tasks they weren’t programmed for. Machine learning has invaluable applications in business. For example:

  • Financial services organizations can quickly identify data insights, act to prevent fraud or and help investors with trading.
  • Health care providers can analyze trends in patients’ health in real time to improve diagnosis and treatment.
  • Retail businesses can analyze consumer data for marketing campaigns and personalizing the shopping experience.

How Do the IoT and ML Work Together?

For artificial intelligence to work, systems need data. The analytical models used for machine learning require information from interconnected devices, much like the human brain requires input from the senses to analyze the environment and trigger a reaction. With vast amounts of information, ML systems can use big data to improve pattern recognition and modeling.

For example, combining the IoT and ML can help predict train arrival times, determine whether there are equipment problems and reveal when maintenance is needed. The same idea has been used to track elevator status and condition. It’s used by online services that make recommendations to consumers, such as Amazon and Netflix, as well.

In the near future, the marriage of IoT/ML will likely enable people to command their cars to take them to work. But even today, oil and gas companies are more efficiently predicting sensor failure and streamlining distribution, while government organizations are mining data more quickly to minimize identify theft and cut costs. 

The combination is already having an impact on every facet of our lives.

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