How to use Machine Learning for IoT Analysis
Machine Learning and the Internet of Things (IoT) have been the buzzwords for the decade. These technologies find application in almost all industries, from enabling artificially intelligent powered digital assistants to the supply chain’s automation. They have revolutionized not only how we interact on social media but also how we pay the bills. Here is how to use Machine Learning for IoT Analysis.
Looking at the google trends analysis below, one can be sure that these technologies offer a lucrative career, so many people are interested in learning about them.
You already know what Machine Learning and IoT are.
Machine Learning is the process of getting computers to learn and act as humans & automatically improve with experience, without explicitly programming it. On the other contrary, the Internet of Things refers to a system of internet-connected objects that can communicate over wireless networks.
Now, it is exciting to note that the base of both these technologies is ‘Data.’ IoT devices generate a lot of data, which may seem useless to us, but this is where the role of Machine Learning comes into the picture.
How Can Machine Learning be Applied to IoT?
Talking about data analytics, Predictive and Prescriptive Analytics both utilize machine learning and find application in the world of IoT.
Predictive Analytics uses different statistical and Machine Learning Models to predict future outcomes based on past data.
For example, in smart lighting systems, the sensors can collect information about illuminance, movement of people and vehicles and public transport schedule, time of the day, year, etc. Based on the data received coupled with the historical data, the Machine Learning Algorithms can predict the appropriate lighting based on the conditions & this will enable the city administration to cut down their electricity costs.
Prescriptive Analytics uses a combination of business rules, computational modeling, and Machine Learning to roll out individual recommendations to a user for any pre-specified outcome.
SmartWatch using a wide range of sensors is an example of Prescriptive Analytics. The watch would record all your information and utilize machine learning models to roll out individual recommendations for you and alert you when it finds an abnormality in the reading.
Tesla Vehicles have always been in the news and even more so now. Probably it is a dream car for many of us. It is a pioneer in technology & they also have rolled out the concept of ‘Self Driving Mode’ on a pilot basis in some of their vehicles.
Have you ever imagined how these Self Driving Cars work? These vehicles have many sensors like lidars, radars, cameras, IoT devices that communicate with each other and send out the data in the form of images and numerical values to a dedicated server.
Based on the data received, various Deep...
