Smart Home Automation: Harnessing Machine Learning for Smart Living

Abstract

Machine learning (ML) plays a pivotal role in advancing smart home automation by enabling systems to adapt and respond intelligently to changing environments and user preferences. This paper explores how ML techniques are leveraged in smart home automation, focusing on their applications, benefits, and challenges. ML algorithms analyze data from various sensors and devices within the smart home ecosystem to learn patterns, make predictions, and optimize control strategies. Common ML applications include activity recognition, energy management, security enhancement, and personalized user assistance. By continuously learning from data, ML algorithms improve automation efficiency, enhance user experience, and contribute to the overall intelligence of smart home systems. However, challenges such as data privacy, scalability, and interpretability of ML models remain areas of ongoing research and development.