Early Detection System for Gas Leakage and Fire in Smart Home Using IOT

Author:

B. Deepika ,S. Sivakami ,S. Sneha ,B. Sujitha

Abstract

Gas leakage is an important environmental, commercial and residential problem that threatens human health, safety and the environment. Traditional gas detection methods often lack the ability to track time and do not provide timely information, leading to accidents and damage. In this context, Internet of Things (IoT) technology has been found to provide a reliable solution for continuous monitoring and remote management of gas detection systems. This paper presents an IoT-based gas leak detection system to improve safety and reduce the risk of gas leakage. leak. The proposed system integrates gas sensors, microcontrollers, communication modules and cloud computing infrastructure to enable real-time monitoring, data analysis and remote monitoring. Gas detectors used in designated areas indicated the presence of hazardous gases, and data was collected directly from the 's central processing unit for analysis. The system provides rapid rescue and intervention by sending instant notifications via mobile applications in case of a gas leak. The main features of the proposed system are scalability, flexibility and interoperability, allowing integration with existing infrastructure and integration of different protocols. Additionally, the use of a cloud-based platform facilitates data storage, analysis and visualization, allowing partners to gain insight intogasleaks, processes and possible consequences

Publisher

Technoscience Academy

Reference10 articles.

1. S.S. Malik, V.K. Shukla, A. Mishra and S. Tiwari, “Design of low-cost IoT-based gas monitoring system,” 3rd International Conference on Sustainable Intelligent Systems (ICISS), 2020.

2. A. Kumar, A.P. Shukla, S. Kumari and R. Singh, "Emission Detection System for Smart Cities", International Conference on Communications and Signal Processing (ICCSP) 2019, 2019.

3. P. Sharma, S. Gupta, A. Kumar, na S. K. Bhandari, “Sensor Networks for Gas Detection and Monitoring,” 9th International Conference on Computers, Communications and Technology (ICCCNT) 2018, 2018.

4. M. S. Khan, M.I.Y. Essa, M.H. Alhussein en M. E. Al-Kuhaili, "Development of Sensing and Reporting Systems for IoT Applications", 2017 IEEE International Conference on Electrical/Informatics (EIT), 2017.

5. "Gas identificatie van LPG/CNG-system with GSM Modül” kapısı Alan M John, Bhavesh Purbia, Ankit Sharma, mevrouw A.S Udapurkar in International Journal of Advanced Research in Computers and Telecommunications, Cilt. 6, no. 5, May 2017.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Safe Haven: Smart Gas Leakage Detection and Response System;Convergence of Machine Learning and IoT for Enabling the Future of Intelligent Systems;2024

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