Year: 2025
Type: conference-paper
Abstract: The article discusses the principles of development and application of an integrated system for monitoring and preventing forest fires using unmanned aerial vehicles (UAVs), ground autonomous systems (UGVs), and stationary sensor networks (SNs).The proposed system architecture provides for the prompt collection, processing, and analysis of environmental data using modern neural network algorithms and clustering methods.Suggested integrated approach combines the mobility of unmanned (UAV-UGV) platforms with continuous parameters monitoring using SNs.The integrated UAV-UGV-SN-based system allows for timely detection of threats, forecasting the spread of fires and coordinating measures to eliminate them.The results of the study demonstrate an increase in the efficiency of emergency response and a reduction in economic and environmental losses.
Authors: Dmytro Korniienko, Vyacheslav Kharchenko
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W7084108683