Stepwise Design of UAV Airborne System for Air Quality Monitoring and Video Surveillance

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Unmanned Aerial Vehicles (UAVs) play a vital role in data collection and surveillance within high-risk areas such as disaster sites or industrial zones with limited human access. This research centers on creating an RF-IoT-integrated ground control station aimed at enhancing UAV communication and surveillance in hazardous environments. Integrating Unmanned Aerial Vehicles (UAVs) into environmental monitoring and surveillance has transformed the collection of real-time air quality data and video footage. This paper introduces the design of a UAV-based airborne system for Air Quality Monitoring and Video Surveillance (UAV-AQMVS). The system integrates multi-sensor arrays for air quality assessment, high-resolution cameras for video surveillance, and an onboard computer for real-time data processing. It comprises three interconnected modular hardware subsystems: the UAV platform, the Air Quality Monitoring (AQM) unit, and the Video Surveillance System (VSS). The UAV, AQM unit, and VSS camera are onboard and linked via wired communication, while the Ground Control Station (GCS) and VSS receiver are connected through wired interfaces. Wireless communication between the UAV and GCS is facilitated by radio frequency (RF) technology. The UAV system includes a flight controller, electronic speed controllers, brushless DC motors, microcontrollers, RF devices, a gyroscope, a barometer, and additional sensors to support flight operations. The AQM unit integrates three MQ-135 gas sensors, a microcontroller, and a wired connection to the UAV. The VSS consists of a camera system and video transmitters wired to the UAV's RF transmitters. This paper highlights the design of a UAV-AQMVS system equipped with advanced capabilities for air quality monitoring and video surveillance. A robust flight control algorithm, operated remotely from the GCS, ensures precise navigation, obstacle avoidance, and energy efficiency. The system is designed with modularity, scalability, and adaptability to diverse environments. Simulation and field tests validate its effectiveness in collecting accurate air quality data and high-resolution video. It is a versatile tool for urban air quality monitoring, industrial emission tracking, and security surveillance. This study advances UAV-based research by offering a comprehensive framework for designing and implementing multifunctional airborne platforms.

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119-130

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February 2026

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© 2026 Trans Tech Publications Ltd. All Rights Reserved

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[1] N. Cheng et al., "AI for UAV-Assisted IoT Applications: A Comprehensive Review," 2023.

DOI: 10.1109/JIOT.2023.3268316

Google Scholar

[2] W. Jing et al., "Development and applications of the UAV remote sensing network based on the intelligent UAV base station," 2023.

DOI: 10.11834/jrs.20235014

Google Scholar

[3] Z. Xiao et al., "A Survey on Millimeter-Wave Beamforming Enabled UAV Communications and Networking," IEEE Communications Surveys and Tutorials, vol. 24, no. 1, 2022.

DOI: 10.1109/COMST.2021.3124512

Google Scholar

[4] O. Sami Oubbati, M. Atiquzzaman, T. Ahamed Ahanger, and A. Ibrahim, "Softwarization of UAV networks: A survey of applications and future trends," IEEE Access, vol. 8, 2020.

DOI: 10.1109/ACCESS.2020.2994494

Google Scholar

[5] H. Liu, Z. Chen, Z. Wang, and J. Li, "An Effective Precision Afforestation System for UAV," Sustainability (Switzerland), vol. 15, no. 3, 2023.

DOI: 10.3390/su15032212

Google Scholar

[6] M. M. Azari, G. Geraci, A. Garcia-Rodriguez, and S. Pollin, "UAV-to-UAV Communications in Cellular Networks," IEEE Trans Wirel Commun, vol. 19, no. 9, 2020.

DOI: 10.1109/TWC.2020.3000303

Google Scholar

[7] K. Y. Tsao, T. Girdler, and V. G. Vassilakis, "A survey of cyber security threats and solutions for UAV communications and flying ad-hoc networks," 2022.

DOI: 10.1016/j.adhoc.2022.102894

Google Scholar

[8] X. JIANG, M. SHENG, N. ZHAO, C. XING, W. LU, and X. WANG, "Green UAV communications for 6G: A survey," Chinese Journal of Aeronautics, vol. 35, no. 9, 2022.

DOI: 10.1016/j.cja.2021.04.025

Google Scholar

[9] C. Malang, P. Charoenkwan, and R. Wudhikarn, "Implementation and Critical Factors of Unmanned Aerial Vehicle (UAV) in Warehouse Management: A Systematic Literature Review," 2023.

DOI: 10.3390/drones7020080

Google Scholar

[10] M. H. Chaudhry, A. Ahmad, Q. Gulzar, M. S. Farid, H. Shahabi, and N. Al-Ansari, "Assessment of dsm based on radiometric transformation of uav data," Sensors, vol. 21, no. 5, 2021.

DOI: 10.3390/s21051649

Google Scholar

[11] G. Geraci et al., "What Will the Future of UAV Cellular Communications Be? A Flight from 5G to 6G," IEEE Communications Surveys and Tutorials, vol. 24, no. 3, 2022.

DOI: 10.1109/COMST.2022.3171135

Google Scholar

[12] L. P. Osco et al., "A review on deep learning in UAV remote sensing," 2021.

DOI: 10.1016/j.jag.2021.102456

Google Scholar

[13] A. Hemmati, M. Zarei, and A. Souri, "UAV-based Internet of Vehicles: A systematic literature review," 2023.

DOI: 10.1016/j.iswa.2023.200226

Google Scholar

[14] Y. Zhou, B. Rao, and W. Wang, "UAV swarm intelligence: Recent advances and future trends," IEEE Access, vol. 8, 2020.

DOI: 10.1109/ACCESS.2020.3028865

Google Scholar

[15] M. Campion, P. Ranganathan, and S. Faruque, "Uav swarm communication and control architectures: A review," J Unmanned Veh Syst, vol. 7, no. 2, 2019.

DOI: 10.1139/juvs-2018-0009

Google Scholar

[16] S. Guan, Z. Zhu, and G. Wang, "A Review on UAV-Based Remote Sensing Technologies for Construction and Civil Applications," 2022.

DOI: 10.3390/drones6050117

Google Scholar