AI, Machine Learning, and IoT: Driving Intelligent Interconnectivity

Abstract

The Internet of Things (IoT), artificial intelligence (AI), and machine learning have all contributed to more efficient interconnected systems, allowing for higher-level decision-making and work to be done in real-time. This study delves into the ways in which AI and ML improve real-time analytics and self-learning automation, enhance information processing, and promote intelligent networking in IoT systems. Research evaluates the efficacy of AI-ML integration for IoT functions based on industry-specific applications, using case studies of real-world IoT systems and analytically advanced AI-ML frameworks. These applications include healthcare, smart cities, and manufacturing. Organizations can respond 30–35% faster and be operationally more efficient 20–25% more with efficient, intelligent systems, according to the study. This suggests that there is room for improvement in responding to new threats. Privacy concerns and implementation obstacles are some of the limits of building these technologies that are discussed in the paper, along with some ways to improve upon them. The implementation of AI-ML enabled IoT systems revolutionizes efficiency and innovation in the digital age, as demonstrated by these suggestions.