Development of Autonomous Electric USV for Water Quality Detection

• Published in: Sensors (Basel, Switzerland) Vol. 25; no. 12; p. 3747
• Main Authors: Chen, Chiung-Hsing, Shang, Yi-Jie, Wu, Yi-Chen, Lin, Yu-Chen
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 15.06.2025; MDPI
• Subjects: Accuracy; automatic identification system; Control algorithms; Controllers; Data transmission; Electric properties; Electrical conductivity; Environmental protection; Heavy metals; Information management; Labor costs; Navigation systems; Pollution; precise positioning; Remote control; Rivers; Sensors; Spread spectrum; Sustainable development; Taiwan; unmanned surface vehicle; Water; Water pollution; Water quality; water quality detection; Taiwan; precise positioning; water quality detection; automatic identification system; unmanned surface vehicle
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s25123747

With the rise of industry, river pollution has become increasingly severe. Countries worldwide now face the challenge of effectively and promptly detecting river pollution. Traditional river detection methods rely on manual sampling and subsequent data analysis at various sampling sites, requiring significant time and labor costs. This article proposes using an electric unmanned surface vehicle (USV) to replace manual river and lake water quality detection, utilizing a 2.4 G high-power wireless data transmission system, an M9N GPS antenna, and an automatic identification system (AIS) to achieve remote and unmanned control. The USV is capable of autonomously navigating along pre-defined routes and conducting water quality measurements without human intervention. The water quality detection system includes sensors for pH, dissolved oxygen (DO), electrical conductivity (EC), and oxidation-reduction potential (ORP). This design uses a modular structure, it is easy to maintain, and it supports long-range wireless communication. These features help to reduce operational and maintenance costs in the long term. The data produced using this method effectively reflect the current state of river water quality and indicate whether pollution is present. Through practical testing, this article demonstrates that the USV can perform precise positioning while utilizing AIS to identify potential surrounding collision risks for the remote planning of water quality detection sailing routes. This autonomous approach enhances the efficiency of water sampling in rivers and lakes and significantly reduces labor requirements. At the same time, this contributes to the achievement of the United Nations Sustainable Development Goals (SDG 14), “Life Below Water”.