Abstract:Aiming at the industry pain points of traditional water quality monitoring equipment, such as high cost, redundant power consumption, weak data collaboration capability and insufficient scalability, this paper designs and implements a low-power water quality monitoring and cloud collaboration system based on Phytium Pi CEK8903. The system uses the fully localized Phytium Pi development board as the core control unit, integrates TS-200 pH sensor, TS-300B turbidity sensor and DS18B20 temperature sensor to build a perception network, and realizes hardware-level low-power optimization through Dynamic Voltage and Frequency Scaling (DVFS) technology. Locally, the software simulates I2C to drive the OLED display module, and realizes cross-device data interaction between Phytium Pi and Arduino through UART protocol; the cloud builds a front-end and back-end separation service based on Flask+Socket.IO architecture, and realizes full-link data synchronization of "edge device-cloud platform-user terminal" with the help of HTTP/Socket.IO dual protocols. The system supports plug-and-play expansion of sensors and hierarchical fault tolerance mechanism. Users can obtain real-time core parameters such as pH value, turbidity and water temperature through Web terminal (PC/mobile terminal) or local OLED screen, and trigger multi-level early warning when parameters are abnormal. Verified by 72-hour laboratory calibration and field simulation tests: standby power consumption is as low as 0.48W (only 1/10 of traditional equipment), the relative error of pH measurement is ≤0.78%, the turbidity detection accuracy is ±30 NTU, the full-link data transmission delay is ≤1 second, and the data packet loss rate is <0.1%. The system breaks through the energy constraints and data island bottlenecks of long-term field monitoring, provides a low-cost and high-reliability nationalized solution for river water quality supervision, refined aquaculture management and industrial wastewater discharge monitoring, and has significant practical value and promotion prospects. Keywords: Phytium Pi CEK8903;Low Power Consumption;Water Quality Monitoring;Cloud Collaboration;Socket.IO; Dynamic Voltage and Frequency Scaling