Intelligent system to analyse distributed geophysical data for a network of test ranges with multiple landscapes
News of the Kabardin-Balkar scientific center of RAS, Tome 26 (2024) no. 6, pp. 129-138.

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The article presents a system for collecting and analysing distributed geophysical data from a sensor network of test ranges with multiple landscapes. The paper presents an architecture and features of a software for collecting data from sensors and for their intelligent analysis, taking into account the lack of stable access to the Internet on the territory of the test ranges. The article shows principles of intelligent system analysis of sensor data designed to use various approaches to create artificial intelligence systems. Moreover, the process of data exchanging with programs to model intelligent systems based on multi-agent neurocognitive architectures is described. In addition, the structure of a website and database of a service for collecting and processing data are presented.
Keywords: distributed sensor network, intelligent data processing, multi-agent systems, neurocognitive architectures, test ranges with multiple landscapes, data forecasting, wireless sensor networks, geophysical data
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M. A. Abazokov; K. Ch. Bzhikhatlov. Intelligent system to analyse distributed geophysical data for a network of test ranges with multiple landscapes. News of the Kabardin-Balkar scientific center of RAS, Tome 26 (2024) no. 6, pp. 129-138. http://geodesic.mathdoc.fr/item/IZKAB_2024_26_6_a9/

[1] N. A. Korgin, R. V. Meshcheryakov, “Concept of the project for the creation of a distributed network of testing grounds for testing scenarios for the use of heterogeneous groups of electric vehicles in difficult climatic and landscape conditions: current condition and development prospects”, XIV Russian Conference on Management Problems, 2024, 1247–1251 (In Russian) https://vspu2024.ipu.ru/node/17868

[2] A. M. Ksalov, K. Ch. Bzhikhatlov, I. A. Pshenokova, A. U. Zammoev, “Development of a transport subsystem for autonomous robots for plant protection system”, News of the Kabardino-Balkarian Scientific Center of RAS, 2022, no. 2 (106), 31–40 (In Russian) | DOI

[3] J. Tu, “Application of wireless sensor network model based on big data ecosystem in intelligent health monitoring system”, Journal of Function Spaces, 2022 (2022), 1–10 | DOI | MR

[4] Y. Zhang, W. Huang, “Design of intelligent diagnosis system for teaching quality based on wireless sensor network and data mining”, Eurasip Journal on Wireless Communications and Networking, 2021:1 (2021) | DOI

[5] F. LI, M. Valero, Y. Cheng et al., “Distributed sensor networks based shallow subsurface imaging and infrastructure monitoring”, IEEE Transactions on Signal and Information Processing over Networks, 6 (2020), 241–250 | DOI | MR

[6] X. Ge, Q. Han, X. Zhang et al., “Distributed event-triggered estimation over sensor networks: A survey”, IEEE Transactions on Cybernetics, 50:3 (2020), 1306–1320 | DOI

[7] C. Hou, Q. Zhao, T. Basar, “Optimization of web service-based data-collection system with smart sensor nodes for balance between network traffic and sensing accuracy”, IEEE Transactions on Automation Science and Engineering, 18:4 (2021), 2022–2034 | DOI

[8] C. Lin, G. Han, X. Qi et al., “Energy-optimal data collection for unmanned aerial vehicle aided industrial wireless sensor network-based agricultural monitoring system: A clustering compressed sampling approach”, IEEE Transactions on Industrial Informatics, 17:6 (2021), 4411–4420 | DOI

[9] G. K. Ijemaru, L. Ang, K. P. Seng, “Wireless power transfer and energy harvesting in distributed sensor networks: Survey, opportunities, and challenges”, International Journal of Distributed Sensor Networks, 18:3 (2022), 155014772110677 | DOI

[10] K. P. Seng, L. Ang, E. Ngharamike, “Artificial intelligence internet of things: A new paradigm of distributed sensor networks”, International Journal of Distributed Sensor Networks, 18:3 (2022), 155014772110628 | DOI

[11] Z. V. Nagoev, I. A. Pshenokova, O. V. Nagoeva, Z. A. Sundukov, “Learning algorithm for an intelligent decision making system based on multi-agent neurocognitive architectures”, Cognitive Systems Research, 66 (2021), 82–88 | DOI

[12] Z. V. Nagoev, K. Ch. Bzhikhatlov, I. A. Pshenokova, A. A. Unagasov, “Algorithms and software for simulation of intelligent systems of autonomous robots based on multi-agent neurocognitive architectures”, Interactive Collaborative Robotics. Lecture Notes in Computer Science, 14898 (2024), Springer, Cham | DOI