Development of Autonomous Electric USV for Water Quality Detection

Area of Science:

• Environmental Science
• Robotics
• Sensor Technology

Background:

• Industrialization has intensified river pollution, necessitating advanced detection methods.
• Traditional water quality monitoring is labor-intensive, costly, and time-consuming.
• Existing methods struggle with prompt and effective river pollution detection.

Purpose of the Study:

• To develop and demonstrate an autonomous unmanned surface vehicle (USV) for remote water quality detection.
• To replace manual sampling with an efficient, cost-effective, and unmanned solution.
• To enhance the accuracy and timeliness of river and lake pollution monitoring.

Main Methods:

• An electric USV equipped with GPS, AIS, and wireless data transmission was utilized.
• The USV autonomously navigated pre-defined routes for water quality measurements.
• Integrated sensors measured pH, dissolved oxygen (DO), electrical conductivity (EC), and oxidation-reduction potential (ORP).

Main Results:

• The USV demonstrated precise positioning and autonomous navigation capabilities.
• Real-time water quality data effectively indicated pollution levels.
• The system successfully identified collision risks using AIS for safe route planning.

Conclusions:

• The autonomous USV offers a significant improvement over traditional methods for water quality monitoring.
• This technology reduces operational costs and labor requirements in environmental monitoring.
• The developed system contributes to achieving UN Sustainable Development Goal 14 (Life Below Water).