Phantomvox - Iot - Based Voice And Gesture Activated Emergency Alert System

Abstract

Emergency Response Systems In Modern Urban And Disaster Environments Continue To Rely On Conventional Alert Mechanisms — Physical Buttons Or Active Network Calls — That Are Inaccessible To Individuals In Distress Due To Physical Incapacitation, Environmental Noise, Limited Network Connectivity, Or Psychological Shock. Traditional SOS Systems Require Deliberate Manual Interaction, Fundamentally Reducing Their Effectiveness In Real-world Crisis Scenarios. This Paper Presents PhantomVox, A Voice And Gesture-activated SOS Web Application Designed To Autonomously Trigger Emergency Alerts Based Entirely On Passive User Input Signals. The System Operates As A Browser-native Progressive Web Application (PWA), Eliminating The Need For Proprietary Hardware, Dedicated Installation, Or Platform-specific Dependencies. PhantomVox Utilises The Web Speech API For Continuous Distress Keyword Monitoring, The Device Motion API For Accelerometer-based Fall Detection, And The Geolocation API For Real-time GPS Coordinate Capture. Upon Trigger Detection, Structured SOS Alerts Are Dispatched To Up To Three Pre-registered Emergency Contacts Via Email Or SMS. Experimental Validation Confirms An Average Alert Latency Below 8 Seconds, A False-positive Rate Below 2%, And Voice Keyword Detection Accuracy Exceeding 92% In Quiet Environments. Through Comparative Analysis Of Existing Personal Safety Systems — Life Alert, BSafe, Apple Watch Fall Detection, And Voice Assistant SOS Features — Five Persistent Research Gaps Are Identified And Addressed Through PhantomVox's Design.

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