Design and experimental investigation of a gas analysis device integrated into an unmanned aerial vehicle (UAV) for the early detection of chemical, biological, radiological, nuclear (CBRN) agents
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Abstract (EN)
In this thesis study, a portable gas analysis system integrated into a rotary-wing Unmanned Aerial Vehicle (UAV) was designed, developed, and experimentally investigated for the early detection of Chemical, Biological, Radiological, and Nuclear (CBRN) agents. As an alternative to existing stationary detection systems with limited coverage and inflexible structures, a mobile system capable of real-time and wide-area scanning was targeted. In the developed system, multiple gas sensors were used simultaneously to ensure the precise and concurrent detection of different gas types. In the experimental studies, tests were carried out using 50 different sample types containing various gas components such as ethanol, acetone, toluene, carbon monoxide, hydrogen, and ammonia. For each sample, an average of 200 tests were conducted, and 2000 data points were collected in each test, resulting in approximately 20 million data points in total. This dataset was processed using various machine learning algorithms (Random Forest, KNN, SVM), and the resulting model was trained to identify new sample types with an accuracy rate of 95%. In addition, separate accuracy analyses were performed for each gas type, and the system's performance was evaluated in detail. The developed gas analysis system not only detects gases in various environments but also determines the type, concentration, and dispersion direction of the gas. With this capability, the system offers a mobile, fast, and reliable solution for critical scenarios such as fires, industrial leaks, war zones, and civil defense applications. The UAV-based gas analysis system developed within the scope of this thesis provides early warning against CBRN threats and stands out as a portable, expandable platform with high accuracy, carrying significant potential for future defense and security applications.
Author
Yunus Emre Yeşilkaya
Institution
How to Cite
Yunus Emre Yeşilkaya (Master Thesis). Design and experimental investigation of a gas analysis device integrated into an unmanned aerial vehicle (UAV) for the early detection of chemical, biological, radiological, nuclear (CBRN) agents, 2025, Fırat University.
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