Real Time Route Adjustment of a UAV Based on Dust Measurement with an Onboard Sensor
DOI:
https://doi.org/10.47852/bonviewAAES42021702Keywords:
unmanned aerial vehicle, route planning, atmospheric measurement, aerial monitoringAbstract
This research is driven by a pressing requirement to improve the effectiveness and safety of unmanned aerial vehicle (UAV) operations, specifically in atmospheric particle sensing. Airborne particulates present a substantial health hazard, leading to an increasing demand for inventive solutions capable of autonomously guiding UAVs along optimal routes, steering clear of regions with heightened dust concentrations. This research aims to address this challenge by developing a sophisticated approach that integrates atmospheric particle sensors with UAV flight control systems. The approach outlined in this study relies on atmospheric sensors mounted on a UAV to measure dust levels in a specified region. The UAV, following a predetermined route over the area, detects dust pollution. It dynamically adjusts its route based on the observed dust levels, avoiding areas with high concentrations of dust. This adaptive route determination aims to identify safe paths, avoiding regions with elevated dust levels that may pose risks to human health. The flight strategy and area-scanning methodology tailored for this objective are established, enabling the UAV to execute the assigned task. The ultimate goal is to create a system that not only minimizes energy consumption but also prioritizes human health by autonomously redirecting the UAV away from potentially harmful dust levels. The real-time monitoring and telemetry data feedback mechanisms further contribute to the advancement of UAV technology for environmental sensing and risk mitigation. Additionally, the integration of the laser-based dust sensor, i.e., Gp2y10, with the ArduPilot autopilot flight computer ensures seamless coordination, with the UAV adjusting its flight path based on the sensor's output.
Received: 7 September 2023 | Revised: 24 November 2023 | Accepted: 8 January 2024
Conflicts of Interest
The authors declare that they have no conflicts of interest to this work.
Data Availability Statement
Data sharing is not applicable to this article as no new data were created or analyzed in this study.
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