Over the last decade, IoT has been gaining ground in the business world. Businesses are built or optimized using IoT devices and their data capabilities, ushering in a new era of business and consumer technology. Now the next wave is with us, as advances in AI and machine learning reveal the capabilities of IoT devices using “artificial intelligence” or AIoT.

Consumers, businesses, economies and industries that adopt and invest in AIoT can harness its power and gain a competitive advantage. IoT collects data and AI analyzes it to simulate intelligent behavior and support decision-making processes with minimal human intervention.

Why IoT needs AI

IoT allows devices to communicate with each other and act on these insights. These devices are as good as the data they provide. To be useful for decision making, data must be collected, stored, processed and analyzed.

This poses a challenge for organizations. As IoT adoption grows, businesses struggle to process data efficiently and use it to make real-world decisions and insights.

This is due to two problems: cloud and data transport. The cloud cannot be scaled proportionally to process all data coming from IoT devices, and the transport of data from IoT devices to the cloud is limited in bandwidth. Regardless of the size and complexity of the communication network, the huge amount of data collected by IoT devices leads to delays and congestion.

Several IoT applications rely on fast real-time decision making, such as autonomous vehicles. To be efficient and safe, autonomous vehicles must process data and make immediate decisions (just like humans). They cannot be limited by latency, unreliable connectivity and low bandwidth.

Copyright © 2022 IDG Communications, Inc.


Previous articleIBM Introduces New Cloud and Artificial Intelligence Fan Experiences for Wimbledon 2022
Next articleSklearn linear regression (step-by-step explanation)