Design and Implementation of a Dual-Mode IoT-Based Gas Leakage Detection and Alert System for Residential Safety in Resource-Constrained Environments

Abstract

The increasing frequency of gas-related accidents in residential, industrial, and institutional settings underscores the urgent need for reliable, real-time gas detection and alert systems. This study presents the design and implementation of an intelligent Gas Leakage Detection and Alert System that integrates Internet of Things (IoT) and embedded sensor technologies for continuous environmental monitoring. The proposed system detects the presence of hazardous gases such as liquefied petroleum gas (LPG), methane, and carbon monoxide using calibrated MQ-series sensors interfaced with a microcontroller unit. A Wi-Fi-enabled module transmits real-time data to a remote cloud server, enabling automated notifications via mobile and web platforms to alert users and emergency responders. The prototype includes both audible and visual alerts, with system thresholds optimized for sensitivity and minimal false positives. Experimental evaluation under controlled and field conditions demonstrated high accuracy in detecting gas concentrations above 200 ppm within less than 5 seconds of exposure, ensuring prompt response to potential hazards.
The proposed framework offers a cost-effective and scalable solution suitable for smart home integration, industrial safety, and public infrastructure management. Future improvements will focus on adaptive threshold algorithms, cloud-based analytics, and integration with smart city platforms to enhance predictive safety intelligence