Gesture-Driven Laptop Control with AI-Powered Background Noise Analysis

With the era of unencumbered human-computer interaction, hands-free control systems are becoming increasingly relevant. This study is performed on a gesture-based control system that would also be coupled with AI-based background noise analysis for adaptive volume control. Our commands like media control and brightness control. Also, The possibility of having an AI-powered noise analysis module, which analyzes background noise levels in real time and dynamically rescales the system volume for an optimal user experience. Gesture detection is achieved based on the MediaPipe framework with precise hand tracking, The system volume control logic utilizes the PyCaw library for direct control of system audio. The noise analysis module has real-time audio processing and ideal thresholding, making intelligent changes to the volume. This two-input scheme increases access, enhance user ease of use, and allow more natural interaction with computing equipment. Our method resolves issues about static gesture-to-gesture mapping, unreliable recognition in different contexts, and interactive volume control, presenting a resilient and effective option for human-computer interaction.