Design of an Amphibious Drone based on Monocular Vision for Lake Monitoring and Rescue

DOI

10.2991/978-94-6463-540-9_40How to use a DOI?

Keywords

Amphibious Drone; Monocular Vision; Environmental Monitoring; Pollutant Tracing; Freshwater Lakes

Abstract

The freshwater available for direct human use is extremely scarce compared to the total amount of water on Earth. Most of this freshwater is located in freshwater lakes. As human civilization progresses, the ecological destruction of freshwater lakes has become increasingly common. Drones have become ideal tools for lake monitoring due to their high mobility and wide coverage. However, these drones mostly do not directly contact the water, which introduces some limitations. To overcome these limitations and improve lake monitoring efficiency, this paper proposes an amphibious drone. This drone directly contacts the water body. It is equipped with monocular vision sensors and water quality sensors. The study validates the feasibility of the floating structure by comparing the displacement to the displacement mass ratio. The feasibility of the vision and water quality modules is verified through practical testing. The study combines the YOLO algorithm with optimized neural network algorithms and the inverse concentration gradient algorithm. The monocular vision sensor and water quality sensor achieve precise positioning and dynamic tracking of pollutants. This study validates the superiority of amphibious drones in monitoring freshwater lakes. It provides a new solution for future protection and monitoring of freshwater lakes.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Qiancheng Ma
AU  - Jundong Qi
PY  - 2024
DA  - 2024/10/16
TI  - Design of an Amphibious Drone based on Monocular Vision for Lake Monitoring and Rescue
BT  - Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
PB  - Atlantis Press
SP  - 403
EP  - 412
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-540-9_40
DO  - 10.2991/978-94-6463-540-9_40
ID  - Ma2024
ER  -