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Heat loss monitoring of multi-story buildings using multi-agent approach
(2020) Simakova, I.
In this paper, the problem of developing a multi-agent method for detecting the places of heat energy leaks on the multi-story buildings using machine learning is solved. Efficient data processing of scanning areas for the heat energy leak monitoring was achieved using the multi-agent monitoring system (MAMS) that can perform calculations in the cloud conditionally. Features of the monitoring system with the integration of an analytical model for presenting a heat loss map with an account of multiple autonomous separated UAV’s for temperature measurements were contained. The MAMS reliability of the synchronization model between simultaneous localization and mapping method and generated heat loss map based on temperature measurements was confirmed. It has been experimentally proven that theoretical assumptions and accuracy for experimental usage during the multi-story building leaks analysis are sufficient.The recognition time of markers of the front of the building is in the range from 0 to 27 s. In this case, with the proposed model CNN, the CPU load during the execution of tasks did not exceed 26%.