
Research Article
Towards an IoT-Based Unmanned Surface Vehicle Design for Environment Monitoring in Mekong Delta
@INPROCEEDINGS{10.1007/978-3-031-58878-5_10, author={Cuong Pham-Quoc and Nguyen Cao Tri}, title={Towards an IoT-Based Unmanned Surface Vehicle Design for Environment Monitoring in Mekong Delta}, proceedings={Context-Aware Systems and Applications. 12th EAI International Conference, ICCASA 2023, Ho Chi Minh City, Vietnam, October 26-27, 2023, Proceedings}, proceedings_a={ICCASA}, year={2024}, month={8}, keywords={}, doi={10.1007/978-3-031-58878-5_10} }
- Cuong Pham-Quoc
Nguyen Cao Tri
Year: 2024
Towards an IoT-Based Unmanned Surface Vehicle Design for Environment Monitoring in Mekong Delta
ICCASA
Springer
DOI: 10.1007/978-3-031-58878-5_10
Abstract
Water quality is a major environmental issue and one of humanity’s major issues. For example, although the Mekong Delta has massive water resources from lakes, rivers, and aquifers, the area suffers from problems due to the reduced usable water supplies. Water pollution and salinization have become critical issues in most nations worldwide due to oil spills, plastic waste, sea-level increase, and human activities. Contamination of this nature can harm fish and other aquatic life habitats, agriculture, and, eventually, human health. This paper introduces our IoT-based Unmanned Surface Vehicle design for monitoring the Mekong Delta wetland environment. We explore the use of recent advances in open-source Global Positioning System (GPS)-guided drone technology to design and test a low-cost and transportable small unmanned surface vehicle (sUSV). The vehicle operates using Ardupilot open-source software and can be used by local scientists and marine managers to map and monitor marine environments in shallow areas with commensurate visibility. The USV is equipped with multiple sensors for measuring various water’s parameters at different positions. The experimental results show that the prototype version of our USV can work 573 m away from the base station while mean square error (MSE) of telemetry data from sensors compared to certified handheld devices is only 6.2%.