Smart water source monitoring system

Project Introduction

system structure

Perception layer:
Sensor network: Deploy water quality sensors (pH, dissolved oxygen, turbidity, permanganate index, etc.), flow meters, video surveillance, meteorological stations and other equipment to achieve real-time data collection.
移动监测终端：无人机、无人船搭载多参数检测仪，覆盖复杂地形区域（如库区死角）。

Low Power Wide Area Network (LPWAN): Using LoRa and NB-IoT technologies to transmit data, reducing energy consumption and costs (a single base station covers a radius of 10 kilometers).
低功耗广域网（LPWAN）：采用LoRa、NB-IoT技术传输数据，降低能耗与成本（单基站覆盖半径达10公里）。
5G边缘计算：在监测节点就近处理数据（如视频AI识别非法排污行为），减少云端负载。

Data center platform: Integrate water quality, water quantity, pollution sources, meteorology, geographical information and other data to build a unified database.
数据中台：集成水质、水量、污染源、气象、地理信息等数据，构建统一数据库。
AI算法引擎：开发水质预测、污染溯源、风险预警等模型，支持决策分析。

Visualized cockpit: GIS maps dynamically display water quality thermal map, pollution diffusion simulation, and equipment operating status.
可视化驾驶舱：GIS地图动态展示水质热力图、污染扩散模拟、设备运行状态。
业务系统：包括监测预警、应急指挥、污染源管理、生态评估等模块。

system function

Intelligent monitoring and early warning
Dynamically display key indicators (such as ammonia nitrogen and total phosphorus concentrations) and over-standard alarms (red/orange/yellow three-level warning).
自动生成日报/周报，对比历史数据与国家标准。
基于水动力模型（如EFDC、MIKE）预测污染物迁移路径，划定应急响应范围。

AI traceability system: Combined with pollutant fingerprint database (such as heavy metal signature spectrum) and hydrological and meteorological data, lock the location of pollution sources (error of 50 meters).
AI溯源系统：结合污染物指纹库（如重金属特征谱）、水文气象数据，锁定污染源位置（误差≤50米）。
技术路径：随机森林算法分析污染物流向，叠加企业排污台账数据匹配嫌疑源。
应急预案库：联动应急资源（活性炭投放设备、拦截坝位置）一键调度。

Dynamic management and control of pollution sources
Electronic ledger management: Record the discharge permits of enterprises in the protected area, the operating status of pollution control facilities, and law enforcement records (such as online monitoring data of wastewater treatment equipment of a chemical plant). Combined with satellite remote sensing to monitor corporate land use changes and warn of illegal expansion risks.

Intelligent inspection system: UAVs automatically patrol route planning, AI identifies garbage dumping, illegal fishing and other behaviors, and generates law enforcement clues.

Ecological health assessment
Ecological index model: Build a comprehensive evaluation system based on biodiversity (benthos, fish populations), vegetation coverage (NDVI index), and water quality indicators.
输出形式：生成生态健康“五色图”（红-黄-绿-蓝-紫代表退化至优良等级）。
修复效果跟踪：对比修复前后数据，量化项目成效。

project value

Monitor water quality, assist in water quality improvement, locate pollution sources, improve water quality control efficiency, etc. Real-time monitoring ensures water source safety and promotes scientific management and governance of water quality.

Real-time data from monitoring systems helps assess ecosystem health and biodiversity. Based on the monitoring results, decision makers can take corresponding measures to protect and restore affected ecosystems and create a clean and healthy water environment.