Development of the method for increasing the accuracy of localization of wireless sensor networks
DOI:
https://doi.org/10.30837/2522-9818.2025.1.180Keywords:
localization, wireless sensor networks; signal power tuning; localization accuracy; multi-step optimization; IoT; location prediction; energy efficiency.Abstract
The subject of the study in the article is methods for increasing the localization accuracy in wireless sensor networks in open environments. Particular attention is paid to methods for adjusting the signal transmission power to determine the communication ranges between reference and unknown nodes, as well as methods for optimizing localization through multi-step narrowing of the search area of possible node locations. The purpose of the work is to develop an effective method that increases the localization accuracy of wireless sensor network nodes by adjusting the signal transmission power to gradually narrow the search area, using multi-round measurement to improve localization results, and statistical analysis to predict the location of nodes. The following tasks are solved in the article: 1) development of a method for adaptively adjusting the signal power; 2) development of an algorithm for multi-round narrowing the search area; 3) use of statistical methods for predicting node positions. Methods used in the study: adaptive signal power adjustment method; algorithm for multi-round narrowing the search area; statistical analysis for predicting the location of a node. Results. A method is proposed that allows to significantly increase the localization accuracy in wireless sensor networks. As a result of experiments, it was shown that, compared to traditional methods, the new approach reduces positioning errors by 30–40%, which is a significant achievement for networks operating in open environments. In some cases, the method allows to accurately determine the location of a node already at a late stage of measurements. This allows to reduce energy consumption, since the number of necessary measurements and checks is significantly reduced. The developed approach demonstrates its effectiveness even in cases where signals are subject to significant interference, thanks to adaptive adjustment of the signal transmission power. Conclusions. The use of the method increases the localization accuracy in wireless sensor networks, which is important for IoT applications. This reduces energy consumption due to the lower need for measurements. Further research may focus on adaptation to more complex conditions, such as urban environments or indoor spaces.
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Khan, R., Pathan, A. (2018), "The state-of-the-art wireless body area sensor networks: A survey". International Journal of Distributed Sensor Networks, 14 р. DOI: 10.1177/1550147718768994
Guerrero-Ibáñez, J., Zeadally, S., Contreras-Castillo, J. (2018), "Sensor technologies for intelligent transportation systems", Sensors. № 18 (4), 1212 р. DOI: 10.3390/s18041212
Hilmani, A., Maizate, A., Hassouni, L. (2018), "Designing and Managing a Smart Parking System Using Wireless Sensor Networks", Journal of Sensor and Actuator Networks. 24 р. DOI: 10.3390/jsan7020024
Alkhatib, A., Hnaif, A., Kanan, T. (2019), "Proposed simple system for Road Traffic Counting". International Journal of Sensors, Wireless Communications and Control. № 9(2), P. 269–277. DOI: 10.2174/2210327908666181107110441
Nguyen, L. N., Vy, T., D., Shin, Y. (2019), "An efficient hybrid RSS-AoA localization for 3D wireless sensor networks", Sensors. № 19 (9), 2121 р. DOI: 10.3390/s19092121
Pita, R., Utrilla, R., Rodriguez-Zurrunero, R., Araujo, A. (2019), "Experimental evaluation of an RSSI-Based localization algorithm on IoT end-devices", Sensors. № 19(18), 3931 р. DOI: 10.3390/s19183931
Tomic, S.; Beko, M.; Dinis, R.; Bernardo, L. (2018), "On target localization using combined RSS and AoA measurements", Sensors. №18, 1266 р. DOI: 10.3390/s18041266
Alkhatib, A., Alia, M., Hnaif, A., Yousef, S. (2018), "A novel method for localizing a randomly distributed wireless sensor network". International Journal of System Assurance Engineering and Management. Springer № 9 (2), P. 354–361. DOI: 10.1007/s13198-017-0670-0
Xiaoyang, L. and Chao, L. (2018), "Wireless sensor network dynamic mathematical modeling and node localization", Wireless Communications and Mobile Computing. 141 р. DOI: 10.1155/2018/1082398
Cama-Pinto, A., Piñeres-Espitia, G., Caicedo-Ortiz, J., Ramírez-Cerpa, E., Betancur-Agudelo, L., Gómez-Mula, F. (2018), "Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules", International Journal of Distributed, P. 1–9. DOI: 10.1177/1550147717722691
Sandeli, M., Kitouni, I. (2021), "An Efficient Localization Approach in Wireless Sensor Networks Using Chicken Swarm Optimization". International Conference on Information Systems and Advanced Technologies (ICISA), P. 1–6. DOI: 10.1109/ICISAT54145.2021.9678446
Avareddy, S., Biradar, R. V. (2021), "Comparative Analysis of Localization Techniques and Security Mechanisms in WSN". IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC), P. 1–4. DOI: 10.1109/ICMNWC52512.2021.9688549
Padhy, S., Dash, S., Malla, P. P., Routray, S., Qi, Y. (2021), "An energy efficient node localization algorithm for wireless sensor network", IEEE 2nd International Conference on Applied Electromagnetics, Signal Processing, & Communication (AESPC), P. 1–5. DOI: 10.1109/AESPC52704.2021.9708459
Khobragade, P., Ghutke, P., Kalbande, V. P., Purohit, N. (2022), "Advancement in internet of things (IoT) based solar collector for thermal energy storage system devices: a review", 2nd International Conference on Power Electronics & IoT Applications in Renewable Energy and its Control (PARC), P. 1–5. DOI: 10.1109/PARC52418.2022.9726651
Lachouri, A., Ardjouni, A. (2022), "Aeroelastic stability of combined plunge-pitch mode shapes in a linear compressor cascade". Advances in the Theory of Nonlinear Analysis and Its Applications. № 6 (1), P. 101–117. DOI: 10.3390/ijtpp7010007
Panwar, A., Morwal, R., Kumar, S. (2022), "Fixed points of ρ-nonexpansive mappings using MP iterative process". Advances in the Theory of Nonlinear Analysis and Its Applications. № 6 (2), P. 229–245. DOI: 10.31197/atnaa.980093
Bhattacharya, S., Pandey, M. (2024), "Deploying an energy efficient, secure and high-speed sidechain-based TinyML model for soil quality monitoring and management in agriculture". Expert Systems with Applications, Volume 242. 122735 р. DOI: 10.1016/j.eswa.2023.122735
Shivadekar, S., Kataria, B., Limkar, S., S. Wagh, K., Lavate, S., Mulla, R. A. (2023), "Design of an efficient multimodal engine for preemption and post-treatment recommendations for skin diseases via a deep learning-based hybrid bioinspired process". Soft Computing, P. 1–19. DOI: 10.1007/s00500-023-08709-5
Boutebba, H., Lakhal, H., Slimani, K., Belhadi, T. (2023), "The nontrivial solutions for nonlinear fractional Schrödinger-Poisson system involving new fractional operator". Advances in the Theory of Nonlinear Analysis and Its Applications. № 7 (1), P. 121–132. DOI: 10.31197/atnaa.1141136
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