Claim Missing Document
Check
Articles

Found 1 Documents
Search

Automating Hazardous Gas Mitigation in Enclosed Areas Using Smart Contracts and Sensors Michael Surya Gunawan; Ridwan Kurniaji; Abdul Hamid Aribathi; Untung Rahardja; Lokae Fern
Blockchain Frontier Technology Vol. 6 No. 2 (2027): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i2.1200

Abstract

Hazardous gas exposure in confined work environments, including mines, tunnels, and petrochemical facilities, threatens workers because conventional monitoring can experience communication attenuation, sensor faults, delayed response, and false alarms. Recent studies have advanced IoT gas sensing, LoRa communication, machine-learning-based fault detection, and spatiotemporal prediction, while blockchain and smart contracts have been explored for data integrity and rule-based automation. However, these capabilities remain fragmented. Existing systems rarely integrate reliable wireless sensing, sensor-fault validation, AI-based gas prediction, trusted safety verification, automated mitigation, and auditable event recording within one framework. This study aims to develop and experimentally evaluate a smart-contract enabled Networked Intelligent Gas Sensor System (N-IGSS) for real-time hazardous-gas monitoring and mitigation. The system combines portable MOX gas sensors, LoRa 868 MHz communication, hybrid HMM-ANN fault detection, and Spatial-Temporal Attention Network (STAN) analysis with a proposed blockchain and smart-contract mechanism for safety-event verification, authorization, and traceability. The framework extends conventional IoT monitoring by connecting validated sensor observations and AI outputs with predefined smart-contract safety rules and automated actuators, including ventilation, alarms, and gas valves. Experimental results show LoRa communication up to 590 meter, low false-positive HMM-ANN fault detection, and strong STAN performance for gas prediction and localization. The system supports notification and automated mitigation, providing foundation for safer, more responsive, and traceable occupational safety management.