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Open Access

Article

04 February 2026

Analysis of Sensor Locations in Drone Aided Environmental Monitoring System Using Computational Fluid Dynamics (CFD) Studies

Recent advancements in unmanned aerial vehicle (UAV) technology have enabled flexible, high-resolution monitoring of atmospheric CO2, particularly in complex or otherwise inaccessible environments. This study employs Computational Fluid Dynamics (CFD) to investigate the downwash flow field of a quadcopter UAV in hover condition with the objective of identifying low-disturbance regions suitable for accurate atmospheric sensor placement. A quadcopter model was simulated using the SST k-ω turbulence model. Simulations were performed at rotor speeds ranging from 1000 to 6000 rpm. Results show that the strongest downwash and turbulence occur directly beneath the rotors, while airflow above the central fuselage and regions laterally distant from the rotors remain significantly calmer. The findings strongly recommend placing gas sensors either above the drone body or sufficiently far horizontally from the rotor plane to minimize measurement errors caused by propeller-induced flow.

Keywords: UAV; Quadcopter; Computational fluid dynamics; Downwash; Sensor placement; Autodesk Fusion; ANSYS Fluent
Drones Auton. Veh.
2026,
3
(1), 10002; 
Open Access

Article

19 March 2024

Designing a Quadcopter for Fire and Temperature Detection with an Infrared Camera and PIR Sensor

In agriculture, medicine, and engineering, sudden fire outbreaks are prevalent. During such events, the ensuing fire spread is extensive and unpredictable, necessitating crucial data for effective response and control. To address this need, the current initiative focuses on utilizing an Unmanned Aerial Vehicle (UAV) with an Infrared (IR) sensor. This sensor detects and analyses temperature variations, accompanied by additional camera footage capturing thermal images to pinpoint the locations of the incidents precisely. The UAV’s programming is executed using Arduino-Nano and mission planner software, interfacing with the Pixhawk flight controller operating in a guided mode for autonomous navigation. The UAV configuration includes a radio module interfacing with Arduino-Nano, a flight controller, and remote-control functionality. The flight duration is approximately 10–15 min, contingent upon flight dynamics and environmental temperature. Throughout its airborne operation, the UAV transmits live telemetry and log feeds to the connected computer, displaying critical parameters such as altitude, temperature, battery status, vertical speed, and distance from the operator. The Pixhawk flight controller is specifically programmed to govern the UAV’s behavior, issuing warnings to the pilot in case of low voltage, prompting a timely landing to avert potential crashes. In case of in-flight instability or a crash, the mission planner can trace the UAV’s location, facilitating efficient recovery and minimizing costs and component availability losses. This integrated approach enhances situational awareness and mitigation strategies, offering a comprehensive solution for managing fire incidents in diverse fields.

Keywords: Drone; Quadcopter; Fire Detection; Pixhawk; ANSYS
Drones Auton. Veh.
2024,
1
(2), 10003; 
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