Enhancing Internet of Things Intelligence Using Machine Learning and Artificial Intelligence for Smart Decision-Making

The astonishing and dynamic development in the advancement of the Internet of Things (IoT) is understood as a connected way through which a multitude of industries is impacted by the collection, processing, and connectedly sharing of huge volumes of data over the Internet. It is, therefore, prudent to have heavy intelligent interventions for quick and autonomous decision-making of all that data today, among many reasons, and that is because its volume and complexity are increasing rapidly due to advancements in the IoT. The power of machine learning (ML) and artificial intelligence (AI) has incorporated such features into IoT for intelligent decision-making with minimal human intervention, as it provides extremely powerful tools with regard to real-time analysis, pattern recognition, anomaly detection, and other kinds of intelligent behavior with regard to decision-making. ML and AI are just one mode through which IoT progresses from simple automation to self-learning, flexible, and forward-looking systems. The global advancement of AI for IoT applications is reshaping development and productivity in various industries. In the case of home automation systems, AI manages energy usage and the surrounding atmosphere. In healthcare, one ML approach under development tracks early disease indicators and supervises patients. This paper outlines the fundamental research questions targeted toward the goal of developing scalable, efficient, and autonomous IoT systems, particularly for assessing the feasibility of integrating ML and AI into IoT-enabled smart intelligence systems.