AI and IoT: Together for a Better Future

Artificial intelligence (AI) and the Internet of Things (IoT) are among the hottest topics in recent times, gathering a lot of attention from technology enthusiasts. There is no doubt that these two trends are going to transform the online world in the same way smartphones revolutionized the first decade of the 21st century.

Introduction

IoT is a set of technologies which manage how physical devices transmit and receive information over the network with no human-to-human or human-to-computer involvement. AI is a field of computer science that builds computers that mimic humans in areas like decision-making, reasoning, speech recognition, learning, problem solving and translation.

Connecting the dots, IoT collects huge amounts of data from innumerable environments while AI uses data science to convert the gathered data into important information and uses analytics to the data for decision making. So, gathering data from various IoT devices and processing it with computers to make sense out of these vast data demands new ways of updating with AI. This excellent combination is expected to improve the existing technology ecosystem.

Here are a few instances of the value that AI brings to IoT applications:

IoT can scale

IoT is all about connected devices that share data between themselves. These IoT devices vary from mobile devices and high-end computers to low-end sensors. There are ecosystems of devices of all types but usually, the most general IoT ecosystems are made of low-end sensors.

By applying AI to the IoT ecosystem, we can draw the sense of data. AI fetches information from one device, then examines and summarizes it before conveying it to other devices. This decreases the flood of data to a manageable level and allows a greater number of IoT devices to be connected to the network. This is called scalability.

IoT becomes smart

In IoT applications, AI-powered machine learning is used to a restricted degree to react to unpredictable situations. When a device receives a sudden query or detects infrequent conditions, it needs knowing whether to reply autonomously or sound an alarm for human assistance. To take such a decision needs intelligent learning and decision-making competence. Google uses this method in the RankBrain algorithm, which applies deep learning to predict the meaning of an unanticipated query, then responds in real-time without any human intervention.

IoT boosts efficiency

With the assistance of predictive analytics, machine learning together with AI learns from the data to interpret trends and make forecasts about future events, like the likelihood of the failure of an equipment in a factory so that it can place an order for replacement parts just in time. This unlocks the real advantages of IoT in an assortment of manufacturing industries.

These are just a few promising applications of AI in IoT. Also, advanced IoT training from a reputed institution can help us learn how to create systems that learn from the data they process.