Development of AI Based Gesture and Voice Control Home Automation System
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Abstract
This study introduces the development and application of an AI-driven smart home system that combines voice and gesture controls to improve user convenience, accessibility, and energy conservation. The research aimed to create a system for managing home appliances through voice instructions and hand movements, assess the effectiveness of each control method, and evaluate their suitability for inclusive automation, especially for people with mobility challenges. The approach integrated hardware and software in a modular framework. High-quality microphones paired with natural language processing enabled voice recognition, while an ADXL335 accelerometer detected motion-based gestures. An Arduino UNO microcontroller served as the central hub, processing inputs and interfacing with appliances through a wireless relay module. Safety features and multi-input validation were incorporated to reduce errors from external factors like ambient noise or inconsistent gestures. Testing revealed that gesture control succeeded in 42 of 50 trials with an average response time of 1.89 seconds, while voice control achieved 44 successful trials with a quicker response time of 1.74 seconds. These findings demonstrate the potential for a reliable, inclusive, and efficient smart home automation solution.
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