Abstract: Smart home automation systems have gained significant popularity in recent years, enhancing comfort, safety, and energy efficiency in modern households. Traditional smart home systems often rely on mobile applications, voice assistants, or remote controls. However, these approaches can sometimes be inconvenient or inaccessible for certain users. In this project, we propose a gesture based smart home automation system using the Mediapipe library integrated with Raspberry Pi 3B+. A camera captures hand gestures, which are processed in real-time using Python and Mediapipe. Based on the recognized gestures, three electrical appliances are controlled via a 3- channel relay board connected to the Raspberry Pi.
Keywords: Feature fusion, Home automation, Deep learning, IOT, Gesture control.
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DOI:
10.17148/IJARCCE.2025.141234
[1] Prof. Mamtha M, Bhavan Kumar V, Dhanush E, Deekshitha K S, Harshitha K, "Smart Home Automation -Based Hand Gesture Recognition Using Feature Fusion and Neural Network," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.141234
