Data collection system with signal optimal-routine for the mining and environmental monitoring in Vietnam

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Authors:


Pham Thanh Loan, orcid.org/0000-0002-8933-5258, Hanoi University of Mining and Geology, Hanoi, the Socialist Republic of Vietnam

Le Xuan Thanh*, orcid.org/0000-0001-5052-4484, Hanoi University of Mining and Geology, Hanoi, the Socialist Republic of Vietnam, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


повний текст / full article



Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2023, (1): 149 - 153

https://doi.org/10.33271/nvngu/2023-1/149



Abstract:



Purpose.
To develop a data acquisition which is optimized for suitable purposes in monitoring/warning or decision-making assistance in the field of geography accident in mining activities or agroforestry.


Methodology.
In activities related to mining, agroforestry and environmental monitoring, many climate factors must be taken into account including humidity, soil moisture or level of rainfall. Those data play a key role in pre-warning or assisting in decision-making for operators who are responsible for risk warning. In this paper, we present an optimized data acquisition system which is reasonable in cost, simple and easy in installation. The system includes a sensor station (SS) and a central station to collect data from specified monitoring points. The latter one is used to gather data from SS through a new and optimized Lora WAN communication system. When sending gathered data to a cloud sever, an assistant system based on 3G module is established to warn of abnormal scenarios of the mining procedure or environmental parameters. The system is experimented, tested and implemented in the North Mountain area (Northwest) of Vietnam.


Findings.
A development of an acquisition system with optimized-data for alarming/warning and monitoring in the field of geography accident, mining activities and environment. The system could get sensing signal in both direct way and indirect way despite of bad weather.


Originality.
An improved Dijkstra algorithm is implemented to optimize and simulate the routing paths of a network. The optimization could show the best way for getting signal from sensor station indirectly to other ones, then to the central station.


Practical value.
A simple, reasonable-cost and easy-installation system is formed for monitoring, risk warning in the field of geography, mining, and climate.



Keywords:
 data acquisition, monitoring, LoRa WAN, risk warning, mining, optimization

References.


1. Tao, Z., Zhang, H., Zhu, C., Hao, Z., Zhang, X., & Hu, X. (2019). Design and operation of App-based intelligent landslide monitoring system: the case of Three Gorges Reservoir Region. Geomatics, Natural Hazards and Risk, 10(1), 1209-1226. https://doi.org/10.1080/19475705.2019.1568312.

2. Huang, F., Luo, X., & Liu, W. (2017). Stability analysis of hydrodynamic pressure landslides with different permeability coefficients affected by reservoir water level fluctuations and rainstorms. Water, 9(7), 450. https://doi.org/10.3390/w9070450.

3. Ngọc, T. (2020). Thiên tai cực đoan, dị thường, Nhân dân điện tử. Retrieved from https://nhandan.com.vn/tin-tuc-xa-hoi/thien-tai-cuc-doan-di-thuong-628407/.

4. Calvello, M. (2017). Early warning strategies to cope with landslide risk. Rivista Italiana Di Geotecnica, 2(17). https://doi.org/10.19199/2017.2.0557-1405.063.

5. Murugesh, P. T. S., Sivakumar, V., Kumar, B., Biju, C., & Rana­de, P. (2015). GIS and Sensor Based Monitoring and Prediction of Landslides with Landslide Monitoring and Prediction System (LMPS) for Indian Scenario. IOSR Journal of Applied Geology and Geophysics, 3(3), 13-16. https://doi.org/10.9790/0990-03311316.

6. Sarah, S., Dilip, M., & Aravindh, R. R. (2016). Disaster Alert andNotification System Via Android Mobile Phone by Using Google Map. International Research Journal of Engineering and Technology, 3(4), 2709-2713.

7. Sukhwani, V., & Shaw, R. (2020). Operationalizing crowdsourcing through mobile applications for disaster management in India. Progress in Disaster Science, (5), 100052. https://doi.org/10.1016/j.pdisas.2019.100052.

8. Sikder, M. F., Halder, S., Hasan, T., Uddin, M. J., & Baowaly, M. K. (2017). Smart disaster notification system. International Conference on Advances in Electrical Engineering, 658-663. https://doi.org/10.1109/ICAEE.2017.8255438.

9. Kadam, A., Mate, L., Chiddarwar, C., Bhoite, A., Momin, S., & Shelar, A. (2018). Natural Disaster Monitoring and Alert System using IOT for Earthquake, Fire and Landslides. International Journal of Innovative Science and Research Technology, 3(3), 763-767.

10. Zambrano, A. M., Calderón, X., Jaramillo, S., Zambrano, O. M., Esteve, M., & Palau, C. (2017). Community early warning systems. Wireless Public Safety Networks, 39-66. https://doi.org/10.1016/B978-1-78548-053-9.50003-2.

11. Piciullo, L., Calvello, M., & Cepeda, J. M. (2018). Territorial early warning systems for rainfall-induced landslides. Earth-Science Reviews, (179), 228-247. https://doi.org/10.1016/j.earscirev.2018.02.013.

12. Ibrahim, D. M. (2019). Internet of Things technology based on LoRaWAN revolution. Information and Communication Systems, 234-237. https://doi.org/10.1109/IACS.2019.8809176.

13. Zhou, Q., Zheng, K., Hou, L., Xing, J., & Xu, R. (2019). Design and implementation of open LoRa for IoT. IEEE Access, (7), 100649-100657. https://doi.org/10.1109/ACCESS.2019.2930243.

14. Leon, E., Alberoni, C., Wister, M., & Hernández-Nolasco, J. A. (2018). Flood early warning system by Twitter using LoRa. Multidisciplinary Digital Publishing Institute Proceedings, 2(19), 1213. https://doi.org/10.3390/proceedings2191213.

15. Gamperl, M., Singer, J., & Thuro, K. (2021). Internet of things geosensor network for cost-effective landslide early warning systems. Sensors, 21(8), 2609. https://doi.org/10.5194/egusphere-egu21-8447.

16. Van Khoa, V., & Takayama, S. (2018). Wireless sensor network in landslide monitoring system with remote data management. Measurement, (118), 214-229. https://doi.org/10.1016/j.measurement.2018.01.002.

17. Gian Quoc, A., Nguyen Dinh, C., Tran Duc, N., Tran Duc, T., & Kumbesan, S. (2018). Wireless technology for monitoring site-specific landslide in Vietnam. International Journal of Electrical and Computer Engineering, 8(6), 4448-4455. https://doi.org/10.11591/ijece.v8i6.pp4448-4455.

18. Azzam, R., Fernandez-Steeger, T., Arnhardt, C., Klapperich, H., & Shou, K. J. (2011). Monitoring of landslides and infrastructures with wireless sensor networks in an earthquake environment. International Society of Soil Mechanics and Geotechnical Engineering, 1-13.

19. Varandas, L., Faria, J., Gaspar, P. D., & Aguiar, M. L. (2020). Low-cost IoT remote sensor mesh for large-scale orchard monitorization. Journal of Sensor and Actuator Networks, 9(3), 44. https://doi.org/10.3390/jsan9030044.

20. LoRa (2018). Retrieved from https://lora.readthedocs.io/en/latest/#range-vs-power.

21. GSM/GPRS Communication chanels for warning systems (n.d.). Retrieved from http://www.electronic-sirens.com/gsmgprs-communications-channels-warning-systems/.

 

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ISSN (print) 2071-2227,
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Journal was registered by Ministry of Justice of Ukraine.
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