An information system for monitoring large wild animals in nature reserves based on spatial analysis and artificial intelligence methods

Olga Khristodulo, Anna Sokolova, M.S. Khairullin, E.V. Nakaryakov

Abstract


This article focuses on the development of an information system for monitoring wildlife in protected areas, based on the integration of artificial intelligence (AI) and spatial analysis methods. The system is designed to automate the collection, transmission, storage, and intelligent processing of large wild animal monitoring data in protected areas, with the goal of improving the completeness and consistency of information used in conservation decision-making. The authors examined a two-stage approach to organizing an information monitoring system: 1) object detection and classification using AI; 2) analytical processing of the obtained data using spatial analysis methods: constructing buffer zones and heat maps of large wild animal habitats. The study analyzed existing approaches used in this subject area, described a method for constructing a species' range (habitat) based on camera trap detections, and proposed an architecture for a large wild animal monitoring system based on microservices that integrates a sensor network, an automatic recognition module (on peripheral devices and/or a server), a spatial data warehouse, and a web interface.

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References


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