Intelligent IoT Enabled Gas Leakage Detection and Alert System with GSM-GPS Integration
DOI:
https://doi.org/10.15662/IJEETR.2026.0802212Keywords:
IoT, Gas Leakage Detection, GSM Module, GPS Tracking, Gas Sensor, Real-Time Monitoring, Emergency Alert SystemAbstract
Gas leakage in domestic, commercial, and industrial environments poses serious risks to human life and property. Early detection and rapid alert mechanisms are essential to prevent accidents such as fire explosions and asphyxiation.
This paper presents the design and implementation of an intelligent IoT-enabled gas leakage detection and alert system with GSM-GPS integration for real-time monitoring and emergency notification. The proposed system utilizes a gas sensor to continuously monitor the presence of hazardous gases and a flow sensor to detect abnormal gas flow conditions.
Sensor data is processed by a microcontroller unit, which compares the measured values with predefined safety thresholds. Upon detecting a gas leak, the system activates an audible buzzer alarm for immediate local warning and displays real-time status information on an LCD module. To ensure remote alerting, a GSM module is integrated to transmit instant warning messages to authorized users. The inclusion of a GPS module enables accurate location tracking of the leakage source, which is highly beneficial during emergency response and rescue operations.
A regulated power supply with a voltage regulator ensures stable and reliable system operation. The proposed system offers a cost-effective, reliable, and scalable solution for continuous gas monitoring and emergency alerting. It is suitable for applications in smart homes, industries, gas pipelines, and public safety systems. The modular design allows easy expansion to include cloud analytics and intelligent decision-making in future developments.
References
1. C. M. Anderson and R. P. LaBelle, “Update of comparative occurrence rates for offshore oil spills,” Spill Science & Technology Bulletin, vol. 6, no. 5–6, pp. 303–321, 2000.
2. D. Dunn, U.S. Energy Information Administration Monthly Energy Review, 2016.
3. C.-H. Chen, Y.-N. Sheen, and H.-Y. Wang, “Case analysis of catastrophic underground pipeline gas explosion in Taiwan,” Engineering Failure Analysis, vol. 65, pp. 39–47, 2016.
4. G. Tariq, S. Huaping, M. Haris, and K. Yusheng, “Energy consumption and economic growth: Evidence from four developing countries,” American Journal of Multidisciplinary Research, vol. 7, no. 1, 2018.
5. International Energy Agency, World Energy Outlook 2019, Paris, France, 2019.
6. C.Nagarajan and M.Madheswaran - ‘Stability Analysis of Series Parallel Resonant Converter with Fuzzy Logic Controller Using State Space Techniques’- Taylor &Francis, Electric Power Components and Systems, Vol.39 (8), pp.780-793, May 2011. DOI: 10.1080/15325008.2010.541746
7. C.Nagarajan and M.Madheswaran - ‘Experimental verification and stability state space analysis of CLL-T Series Parallel Resonant Converter’ - Journal of Electrical Engineering, Vol.63 (6), pp.365-372, Dec.2012. DOI: 10.2478/v10187-012-0054-2
8. C.Nagarajan and M.Madheswaran - ‘Performance Analysis of LCL-T Resonant Converter with Fuzzy/PID Using State Space Analysis’- Springer, Electrical Engineering, Vol.93 (3), pp.167-178, September 2011. DOI 10.1007/s00202-011-0203-9
9. S.Tamilselvi, R.Prakash, C.Nagarajan,“Solar System Integrated Smart Grid Utilizing Hybrid Coot-Genetic Algorithm Optimized ANN Controller” Iranian Journal Of Science And Technology-Transactions Of Electrical Engineering, DOI10.1007/s40998-025-00917-z,2025
10. S.Tamilselvi, R.Prakash, C.Nagarajan,“ Adaptive sliding mode control of multilevel grid-connected inverters using reinforcement learning for enhanced LVRT performance” Electric Power Systems Research 253 (2026) 112428, doi.org/10.1016/j.epsr.2025.112428
11. S.Thirunavukkarasu, C. Nagarajan, 2024, “Performance Investigation on OCF and SCF study in BLDC machine using FTANN Controller," Journal of Electrical Engineering And Technology, Volume 20, pages 2675–2688, (2025), doi.org/10.1007/s42835-024-02126-w
12. C. Nagarajan, M.Madheswaran and D.Ramasubramanian- ‘Development of DSP based Robust Control Method for General Resonant Converter Topologies using Transfer Function Model’- Acta Electrotechnica et Informatica Journal , Vol.13 (2), pp.18-31,April-June.2013, DOI: 10.2478/aeei-2013-0025.
13. C.Nagarajan and M.Madheswaran - ‘DSP Based Fuzzy Controller for Series Parallel Resonant converter’- Springer, Frontiers of Electrical and Electronic Engineering, Vol. 7(4), pp. 438-446, Dec.12. DOI 10.1007/s11460-012-0212-0.
14. C.Nagarajan and M.Madheswaran - ‘Experimental Study and steady state stability analysis of CLL-T Series Parallel Resonant Converter with Fuzzy controller using State Space Analysis’- Iranian Journal of Electrical & Electronic Engineering, Vol.8 (3), pp.259-267, September 2012.
15. C.Nagarajan and M.Madheswaran, “Analysis and Simulation of LCL Series Resonant Full Bridge Converter Using PWM Technique with Load Independent Operation” has been presented in ICTES’08, a IEEE / IET International Conference organized by M.G.R.University, Chennai.Vol.no.1, pp.190-195, Dec.2007
16. Suganthi Mullainathan, Ramesh Natarajan, “An SPSS and CNN modelling based quality assessment using ceramic materials and membrane filtration techniques”, Revista Materia (Rio J.) Vol. 30, 2025, DOI: https://doi.org/10.1590/1517-7076-RMAT-2024-0721
17. M Suganthi, N Ramesh, “Treatment of water using natural zeolite as membrane filter”, Journal of Environmental Protection and Ecology, Volume 23, Issue 2, pp: 520-530,2022
18. Mathew, A., & Alex, H. (2025). Federated Learning for Secure Genomic Research: Privacy-Preserving AI Solutions for Precision Medicine. Science and Technology: Developments and Applications Vol. 9, 36-43.
19. Jagadeesh, S., & Soundappan, R. S. (2014). Survey on knowledge discovery in speech emotion detection. International Journal of Innovative Research in Computer and Communication Engineering, 2(5), 4476–4481. Retrieved from https://ijircce.com/admin/main/storage/app/pdf/i7mLTWLAd6a4VqXoYxeMRM6m0zylGcBFKaMTHo5H.pdf
20. Soundappan, S. J. (2022). AI-Based Fault Detection and Isolation for Reliability in Modern Power Systems. International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(4), 7106-7110.
