Enhanced Intelligence Smart Home Control and Security System by using Deep Learning

Abstract

The rapid integration of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has changed conceptual models into practical systems in smart home systems, infacts the traditional rule-based security approaches remain limited in adaptability and threat detection. The purpose of this study is to search for the application of deep learning, specifically convolutional and recurrent Neural networks, to increase smart home control and security. This can be achieved by enabling real-time behavior analysis, anomaly detection, and autonomous decision-making; deep learning offers a scalable and context-aware solution. A persistent challenge lies in minimizing false notifications and alarms, which often result from non-threatening movements or environmental fluctuations.