Enhancing IOT Systems with Machine Learning: A Framework for Intelligent Decision Making

Abstract

The convergence of the Internet of Things (IoT) with machine learning (ML) holds considerable promise for advancing green computing. By optimizing resource use, reducing energy consumption, and fostering sustainable practices, this integration has the potential to significantly contribute to environmental sustainability. This paper delves into how IoT and ML can work together in areas like energy management, predictive maintenance, HVAC optimization, smart agriculture, and waste management. It also examines the challenges in deploying these technologies, such as concerns around data privacy, scalability, resource constraints, and interoperability. Looking ahead, the paper highlights emerging trends like edge computing, federated learning, AI-driven sustainable solutions, and the development of smart cities, which offer exciting avenues for future research and development. Ultimately, the combination of IoT and ML is seen as a powerful tool to not only enhance operational efficiency but also to achieve broader sustainability goals.