Data Acquisition and Remote Monitoring of Geological parameters for Landslide Prediction using WSN
Main Article Content
Abstract
Aiming at the problems of a large amount of redundant information, low data accuracy and difficulty in system monitoring when wireless sensor network nodes collect data. An efficient technique of data collection and remote monitoring system based on wireless sensor network is proposed. The system uses WSN nodes to real-time collection of external environment parameters. A software design for Wireless Sensor Network formation, data fusion, data transmission and transferring data to the host computer, and use of WIFI/GSM as a means of transmission to build a remote monitoring platform. The test results show that the system can realize remote real-time monitoring of the external environment, geophysical parameters and the use of data fusion algorithms increases the transmission rate and data accuracy between nodes.
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How to Cite
Rao, D., Ahmed, M., Kumar, C., & Kumar, S. (2022). Data Acquisition and Remote Monitoring of Geological parameters for Landslide Prediction using WSN. SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology, 14(04), 1-5. https://doi.org/10.18090/samriddhi.v14i04.01
Section
Research Article
References
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2003, pp. 1443–47.
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[7] Deng, S.; Li, J.; Shen, L. Mobility-based clustering protocol for wireless sensor networks with mobile nodes. I. Eng. Technol. 2011, 1, 39–47.
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Solutions. (2023). International Journal of Engineering & Extended Technologies Research (IJEETR), 5(2), 6275-6281.
https://doi.org/10.15662/IJEETR.2023.0502004
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1189–1194.
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[11] Chang, C.Y.; Lin, C.Y.; Kuo, C.H. EBDC: An energy-balanced data collection mechanism using a mobile data collector in WSNs. Sensors 2012, 12, 5850–5871.
[12] Madan R, Lall S. Distributed algorithms for maximum lifetime routing in wireless sensor networks. IEEE Trans Wirel Commun. 2006;5(8):21852193.
[13] Ning, X., Sumit, R., Krishna, KC, et al. (2004) A Wireless Sensor Network for Structural Moni-toring. Proceedings of the ACM Conference on Embedded Networked Sensor Systems, New York, 56 -68.
[14] T. Wang et al., “Fog-based evaluation approach for trustworthy communication in sensor-cloud system,” IEEE Commun. Lett., vol. 21, no. 11, pp. 2532–2535, Nov. 2017.
[15] Cheng Rui, Li Jing, Lei Ming, et al. Design of wireless sensor network based on zigbee[J]. Application of Electronic Components, 2007, 24(3): 20-22.
[16] He Xuewen, Zheng Leping, Sun Han. Multi-sensor data fusion algorithm in wireless sensor network cluster[J]. Sensors and Microsystems, 2014, 33(1): 147-150.
[17] Wang Kang, Wang Feng. Research on Data Fusion Algorithm for Wireless Sensor Networks[J]. Television Technology, 2014. 38(1): 103106.
[18] Liu Hui, Zhao Lifen. Design of ZigBee RF transceiver module based on CC2530[J]. Journal of Yunnan Nationalities University, 2012, 21(16): 452-456.
[19] Jin Chun. Zigbee technology basis and case analysis[M]. Beijing: National Defense Industry Press, 2008.
[20] I.F. Akyildiz, W.Y. Lee, M.C. Vuran and S. Mohanty, “Next Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey”, Computer Networks, Vol.50, No. 13, pp. 21272159, 2006.