Concentration map reconstruction for gas source location using nano quadcopters: Metal oxide semiconductor sensor implementation and indoor experiments validation. (31st May 2023)

• Record Type: Journal Article
• Authors: Bouras, Abdelwahhab; Gutierrez-Galvez, Agustin; Burgués, Javier; Bouzid, Yasser; Pardo, Antonio; Guiatni, Mohamed; Marco, Santiago
• Is Part Of: Measurement. Volume 213(2023)
• Publication Date: 2023-05-31
• Subjects: Nano-quadcopter -- Metal oxide semiconductor sensor -- Coverage path planning (CPP) -- Gas distribution map (GDM) -- Gas source localization (GSL); Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2023.112638
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: In this paper, we present a mobile gas monitoring system based on Nano-drones to map indoors gas distributions and to locate the gas source. The system combines a gas sensing unit of reduced size, weight, and consumption with a commercial Nano-drone. The sensing unit is outfitted with a metal oxide gas sensor for the detection of Volatile Organic Compounds (VOC). Several experiments were conducted in this study. A first set of experiments were devoted to characterizing the effect of the rotors on the sensor signals, commonly known as downwash. The experiments were designed to determine the speed and response intensity of the gas sensor placing the gas source at different heights above and below the drone. We repeated the experiments with the drone's rotors turned on and turned off to compare the results. A more comprehensive set of experiments was conducted to test the monitoring system in gas distribution maps generation and source localization problems. Several scenarios were designed and tested with different drone trajectories, drone speeds, including one or two drones. Our results support the ideas that a good coverage of the area of interest combined with a moderate drone speed improves the accuracy of the gas concentration map as well as the accuracy of the estimation of the source location. Highlights: We developed a nano-drone based gas sensing system to locate chemical sources. To find the highest odor concentration locus, we reconstructed a GasDistribution Map. The system is tested in an odor source localization problem with a single VOC source.