Gas Guardian: An IoT-Based Real-Time Leakage Detection and Mitigation System

Mon, 01 Jun 2026 00:00:00 +0000

An IoT-based Gas Leakage Detection System is developed to enhance safety by detecting hazardous gas leaks in real time. The system uses an MQ-6 gas sensor to monitor combustible gases such as LPG, propane, and methane with high sensitivity. When the gas concentration exceeds a predefined threshold, the system immediately activates safety mechanisms, including a buzzer alert and an exhaust fan, to reduce gas levels in the environment. The core controller, NodeMCU (ESP8266), enables wireless communication through Wi-Fi, allowing the system to connect with the Blynk mobile application for remote monitoring. It also displays warning messages on an LCD screen, ensuring both local and remote alerts. This dual-alert mechanism helps users take immediate action even when they are not physically present. The system is cost-effective, energy-efficient, and easy to install, making it suitable for residential, commercial, and small-scale industrial applications. By providing continuous monitoring, early detection, and rapid response, it significantly reduces the risk of fire accidents, explosions, and health hazards caused by gas leakage. Overall, the integration of sensor technology with IoT improves safety and helps protect human life and property effectively.

Enhancing Security in Digital Twin-Based Smart IoT Environments

Shikha Tiwari, Nisha Rathore, Vinay Kumar Singh — Tue, 30 Jun 2026 00:00:00 +0000

Digital Twin (DT) technology has emerged as a key enabler of smart Internet of Things (IoT) systems by providing real-time monitoring, predictive analytics, and intelligent decision-making capabilities. However, the integration of DT with IoT introduces significant security challenges due to distributed architectures, continuous data exchange, and heterogeneous devices. This paper presents a comprehensive study of security issues in DT-enabled IoT systems, including threat models across device, network, data, application, and DT layers. To address these challenges, a hybrid security framework integrating Artificial Intelligence (AI), Blockchain, and Edge Computing is proposed. The framework leverages AI-based intrusion detection for real-time anomaly identification, blockchain for secure and tamper-proof data validation, and edge computing for low-latency processing. Mathematical models are developed to evaluate threat detection, intrusion probability, and trust mechanisms. Experimental results demonstrate that the proposed hybrid approach achieves 96% detection accuracy, significantly reduces false alarms, and lowers latency compared to traditional methods. The study highlights the effectiveness of combining AI and blockchain in enhancing security resilience and real-time responsiveness. This work contributes toward developing a unified, scalable, and secure Digital Twin framework suitable for next-generation smart environments such as smart cities, healthcare IoT, and industrial systems.

Journal of IoT-based Distributed Sensor Networks (e-ISSN: 3048-9202)

Gas Guardian: An IoT-Based Real-Time Leakage Detection and Mitigation System

Enhancing Security in Digital Twin-Based Smart IoT Environments