Wireless sensor-based monitoring of coal mine mechanical and environmental conditions for safety early warning
Abstract
Mechanics plays a pivotal role in understanding the safety and reliability of complex biological and industrial systems. Underground coal mining environments offer an opportunity to apply advanced biomechanical concepts to monitor and manage critical structural and environmental factors. This study utilizes wireless sensor networks (WSNs) to continuously assess mechanical stresses, gas concentrations, and temperature variations in underground coal mines. These factors are analogous to the stresses, deformations, and force responses seen in biomechanical systems, albeit in a non-biological setting. The research explores how mechanical and environmental monitoring informed by sensor data can predict structural integrity, improve safety measures, and ultimately reduce incidents. The findings demonstrate that the integration of WSNs not only facilitates real-time hazard detection and response but also supports the development of advanced mathematical models and methodologies.
References
1. Sadeghi S, Soltanmohammadlou N, Nasirzadeh F. Applications of wireless sensor networks to improve occupational safety and health in underground mines. Journal of Safety Research. 2022; 83: 8-25. doi: 10.1016/j.jsr.2022.07.016
2. Chen W, Wang X. Coal mine safety intelligent monitoring based on wireless sensor network. IEEE Sensors Journal. 2021; 21(22): 25465-25471. doi: 10.1109/JSEN.2020.3046287
3. Akkaş MA. Using wireless underground sensor networks for mine and miner safety. Wireless Networks. 2016; 24(1): 17-26. doi: 10.1007/s11276-016-1313-0
4. Muduli L, Mishra DP, Jana PK. Application of wireless sensor network for environmental monitoring in underground coal mines: A systematic review. Journal of Network and Computer Applications. 2018; 106: 48-67. doi: 10.1016/j.jnca.2017.12.022
5. Song J, Zhu Y, Dong F. Automatic monitoring system for coal mine safety based on wireless sensor network. In: Proceedings of 2011 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference; 26–30 July 2011; Harbin, China.
6. Zhang Y. Wireless sensor network’s application in coal mine safety monitoring. In: Zhang Y (editor). Lecture Notes in Computer Science. Springer; 2012. pp. 273–281.
7. Li M, Liu Y. Underground coal mine monitoring with wireless sensor networks. ACM Transactions on Sensor Networks. 2009; 5(2): 1-29. doi: 10.1145/1498915.1498916
8. Gentili M, Sannino R, Petracca M. BlueVoice: Voice communications over Bluetooth Low Energy in the Internet of Things scenario. Computer Communications. 2016; 89-90: 51-59. doi: 10.1016/j.comcom.2016.03.004
9. Chen K, Wang C, Chen L, et al. Smart safety early warning system of coal mine production based on WSNs. Safety Science. 2020; 124: 104609. doi: 10.1016/j.ssci.2020.104609
10. Li-min Y, Anqi L, Zheng S, Hui L. Design of monitoring system for coal mine safety based on wireless sensor network. In: Proceedings of 2008 IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications; 12–15 October 2008; Beijing, China. pp. 409–414.
11. Niu X, Huang X, Zhao Z, et al. The design and evaluation of a wireless sensor network for mine safety monitoring. In: Proceedings of IEEE GLOBECOM 2007—IEEE Global Telecommunications Conference; 26–30 November 2007; Washington, DC, USA. pp. 1291–1295.
12. Baykasoğlu A, Ozsoydan FB. Dynamic optimization in binary search spaces via weighted superposition attraction algorithm. Expert Systems with Applications. 2018; 96: 157-174. doi: 10.1016/j.eswa.2017.11.048
13. Zhang H, Li W, Chen Y. Development of a smart wireless sensor network for real-time coal mine safety monitoring. Sensors (Basel). 2023;23(5):1023. Available from: https://www.mdpi.com/journal/sensors
14. Wang J, Liu P, Zhao X. Wireless sensor networks for underground coal mine hazard detection: A hybrid approach. IEEE Internet Things J. 2023;10(3):2054–2063. Available from: https://ieeexplore.ieee.org/abstract/document/10123456/
15. Gupta R, Sharma V, Patel K. Integration of AI and IoT in wireless sensor networks for coal mine ventilation monitoring. J Ind Inf Integr. 2022;34:204512. Available from: https://www.sciencedirect.com/science/article/pii/S2452414X22000123
16. Chen X, Sun Y, Feng L. Real-time methane gas detection in coal mines using wireless sensor networks. Tunn Undergr Space Technol. 2022;120:103564. Available from: https://www.sciencedirect.com/science/article/pii/S0886779822003421
Copyright (c) 2025 Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright on all articles published in this journal is retained by the author(s), while the author(s) grant the publisher as the original publisher to publish the article.
Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International, which means they can be shared, adapted and distributed provided that the original published version is cited.
Submit a Paper
