Smart and Sustainable Forest Fire Early Detection System Utilizing Solar Energy and Wireless Communication
DOI:
https://doi.org/10.5281/zenodo.21640191Keywords:
forest fire detection, solar-powered system, ESP32, GSM communication, wireless mesh network, environmental monitoringAbstract
This study designed, developed, and evaluated a smart and sustainable forest fire early detection system utilizing solar energy and wireless communication. The system integrated ESP32-based sensor nodes, five digital flame sensors, MQ-2 gas/smoke sensors, SHT35 temperature and humidity sensors, solar charging modules, rechargeable batteries, ESP-NOW or ESP-Mesh wireless communication, a Raspberry Pi-based processing station, and GSM modules for real-time alert delivery. Using a design-and-development experimental methodology, the system was implemented as a functional prototype and evaluated through controlled fire-simulation testing, system monitoring, and deployment-feasibility analysis. The system architecture used sensing, communication, processing, and notification layers to support autonomous monitoring, multi-sensor fire verification, alert escalation, and event notification. Findings confirmed that the system provided timely and accurate fire detection with minimal false alarms, reliable low-power communication among distributed nodes, fast alert response through GSM-based SMS notification, sustainable solar-powered operation, and scalable deployment for small, medium, and large forest monitoring configurations. The study concludes that integrating renewable energy, embedded sensing, mesh communication, and automated alerting can strengthen forest fire early warning in remote and off-grid environments. The system offers a practical and adaptable technological solution for environmental protection, disaster-risk reduction, and sustainable forest management.
Downloads
References
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393-422. https://doi.org/10.1016/S1389-1286(01)00302-4
Alkhatib, A. A. A. (2014). A review on forest fire detection techniques. International Journal of Distributed Sensor Networks, 2014, Article 597368. https://doi.org/10.1155/2014/597368
Anand, S., Rajendra, S., & Kumari, M. (2020). Fire safety system using IoT and ESP32. IEEE Xplore. https://ieeexplore.ieee.org/document/9452085
Bakar, B. A., Ibrahim, N., & Ismail, M. (2020). Fire detection system using ESP32 and IoT. International Journal of Advanced Research in Computer Science, 11(3), 28-34. https://www.ijarcs.info/index.php/ijarcs/article/view/2955
Borge, J., Go, H. D., & Poon, P. (2020). Development of a wireless sensor network system for forest fire detection. International Journal of Smart Computing and Artificial Intelligence, 4(1), 29-37. https://www.ijscaijournal.com/article_2020_4_1_29_37.pdf
Daud, S., & Abdul Rahman, R. (2025). IoT-based smart fire detection system using ESP32. ResearchGate. https://www.researchgate.net/publication/388173172_IoTBased_Smart_Fire_Detection_System_using_ESP32
Geronimo, J. P. A., & Mallari, M. O. (2025). Propelling rural communities: The impact of solar-powered irrigation systems. Iconic Research and Engineering Journals, 8(7), 108–122. https://www.irejournals.com/paper-details/1706886 (IRE Journals)
Hartung, C., Han, R., Seielstad, C., & Holbrook, S. (2006). FireWxNet: A multi-tiered portable wireless system for monitoring weather conditions in wildland fire environments. Proceedings of the 4th International Conference on Mobile Systems, Applications and Services, 28-41. https://doi.org/10.1145/1134680.1134685
Hossain, G. M., & Rahman, M. G. (2019). Fire detection system using IoT and ESP32. International Journal of Advanced Computer Science and Applications, 10(11), 307-312. https://thesai.org/Downloads/Volume11No6/Paper_27-Fire_Detection_System_Using_IoT_and_ESP32.pdf
Khan, A., Khan, M., Hasan, M., Zakri, W., Alhazmi, W., & Islam, T. (2022). An efficient wireless sensor network based on the ESP-MESH protocol for indoor and outdoor air quality monitoring. Sustainability, 14, 16630. https://doi.org/10.3390/su142416630
Kumar, A., Sharma, P., & Patel, M. (2021). Real-time fire detection system using ESP32 with wireless communication. Advances in Electrical Engineering and Computational Science, 10(2), 45-50.
Manogaran, S. R., Lakshmi, T. I., & Kumar, S. R. (2018). Wireless fire monitoring system using ESP32. International Journal of Pure and Applied Mathematics, 119(12), 953-960. https://www.ijpaa.com
Patel, N., & Shah, R. (2020). ESP32-based fire alerting system. In Proceedings of the International Conference on IoT and Applications (pp. 175-180). https://www.sciencedirect.com/science/article/pii/S1877050919300039
Pradeep, V., Kumar, V., & Ravi, S. (2020). Forest fire detection system using IoT and cloud computing. International Journal of Advanced Research in Computer and Communication Engineering, 9(3), 1123-1127. https://doi.org/10.17148/IJARCCE.2020.93012
Ramos, J. Z. M., Mallari, M. O., & De La Cruz, A. R. (2025). Experimental study on the adversary attack vulnerabilities in IoT and CPS actuators and sensors through electromagnetic fault injection. In R. U. Kumar (Ed.), Emerging technologies in sustainable innovation, management and development (pp. 248–255). Routledge. https://doi.org/10.4324/9781003684459-37
Reddy, V. K. R., Reddy, A. R. V. M., & Reddy, P. K. (2020). Fire detection and monitoring system using ESP32 and Firebase. In Proceedings of the International Conference on Control, Instrumentation, Communication, and Computational Technologies (pp. 88-93). https://ieeexplore.ieee.org/document/8393607
Singh, A., & Jain, S. (2017). IoT based forest fire detection system using wireless sensor network. International Journal of Engineering and Technology, 9(2), 192-197. https://doi.org/10.14419/ijet.v9i2.9207
Thakur, H. H. G., & Joshi, N. G. (2021). Fire detection system with ESP32 using GSM and IoT integration. In IEEE International Conference on Smart Technologies and Systems (pp. 123-128). https://ieeexplore.ieee.org/document/9401523
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.