Author(s)

Xinyi Tang

School of Computer Science and Engineering/School of Software, Guangxi Normal University, Guilin, China.

In order to solve the problem of scientific monitoring of water quality, a trophic monitoring system for Li River water quality is developed to improve the decision-making of related environmental management departments. The system is based on embedded computing, deep learning and Internet of Things technology, combined with software and hardware design, to automatically obtain real-time water quality parameters with Raspberry Pi equipped with sensors and positioning modules. A camera is employed to capture the screen, and yolo-tiny image recognition is implemented in the Raspberry Pi. Lastly, the cloud storage is used for interaction to realize real-time monitoring of water quality, real-time positioning of the boat, real-time return of image recognition and visualization. The system is proven efficient and intelligent in facilitating water quality protection.

Raspberry Pi, Sensors, YOLO-Tiny Model, Cloud Development

Tang, X.Y. (2023) Design of Li River Water Quality Dynamic Monitoring System Based on Raspberry Pi and TinyML. Journal of Computer and Communications, 11, 121-133. doi: 10.4236/jcc.2023.118009.