Accurate, efficient and sustainable water treatment dosing management

The traditional water treatment dosing process relies on manual experience and judgment, and there are the following problems：

Serious waste of medicine: Excessive dosing leads to increased costs, and drug residues affect water quality and safety.
Response lag: When manually monitoring fluctuations in water quality, the dosage cannot be adjusted in real time, which affects the treatment effect.
Data silos: The lack of in-depth analysis of historical data makes it difficult to optimize process parameters.
Regulatory pressure:Environmental protection standards are becoming stricter, and it is difficult for traditional methods to ensure stable and up-to-standard emissions.

	Core functional modules	Technical support
Data acquisition layer	-Multi-parameter water quality sensor (pH, turbidity, COD, TP, residual chlorine, etc.) –Flowmeter and drug stock monitoring –Equipment condition monitoring (dosing pump, agitator)	High-precision sensor array, edge computing gateway (real-time data preprocessing), 5G/LoRa wireless transmission
Intelligent analysis layer	-Feedforward prediction model (based on water inlet flow/water quality) -Feedback compensation model (based on effluent index) -Multi-objective optimization algorithm (balance medicine consumption/water quality/energy consumption)	Time series prediction, fuzzy PID control, multi-objective optimization algorithm, AI training platform
Control execution layer	–Precise control of digital metering pump –Multi-agent collaborative dosing strategy –Automatic switching under abnormal working conditions	PLC+SCADA system, Modbus/OPC UA protocol, redundant control design
Interaction management	-WEB/APP visual MONITORING (heat map of pharmaceutical consumption, analysis of water quality trends)	Low-code development platform, data visualization tool

Cloud-edge-end collaboration: Edge nodes realize real-time control at the millisecond level (such as response to sudden water quality fluctuations), and optimize long-term strategies in the cloud.
Multi-algorithm fusion: Feedforward prediction (coping with water inlet mutations) + feedback compensation (closed-loop correction) + enhanced learning (long-term adaptation), the error rate is reduced to ±2%.
Redundant safety design: Dual-system backup of key control loops, and the local edge model automatically takes over when communication is interrupted to ensure continuous and stable operation.

Precise dosing ability

Dynamic response speed：从水质变化检测到加药量调整完成，全链路延迟<30秒（传统人工需10-30分钟）。
Dosing accuracy: The control accuracy of the digital metering pump is ±1%, and the dosing error of the drug is ≤3% (the manual operation error is generally >15%).

Multi-dimensional cost optimization

Pharmacy savings: Through AI dynamic adjustment, typical scenarios save PAC by 25%-40% and carbon source by 30%-50%.
Reduced energy consumption: Optimize the start-stop strategy of the dosing pump, and reduce the energy consumption of the equipment by 15%-20%.

Intelligent management

Self-learning model: The AI algorithm parameters are automatically updated every quarter to adapt to seasonal changes in water quality (such as high turbidity in the rainy season and low temperature in winter, which affect the reaction rate).
Full link traceability: Automatically record pharmaceutical procurement, dosing, and effect data to meet compliance requirements.

Reliability and extensibility

Fault self-healing: Automatically identify pipeline blockage/pump failure, switch spare equipment and push maintenance work orders, and reduce downtime by 70%.
Rapid expansion: The modular design supports seamless access to new drug types (such as algae remover and heavy metal trapping agent) without the need to rebuild the system.

Core scenarios and solutions

scene	Pain points	Technical solution	Quantify benefits
Flocculation control in waterworks	Mutations in the turbidity of raw water cause uneven formation of alum flowers	–Real-time monitoring of flocculation size by laser online particle analyzer -Dynamically adjust the acceleration rate and stirring intensity of PAC injection	The turbidity of the effluent from the sedimentation tank is ≤0.5 NTU, which saves 30% of the medicine.%
Denitrification and phosphorus removal in sewage plants	The C/N/P ratio of the water inlet fluctuates, and the carbon source and the phosphorus remover are added in excess.	- Online spectrometer to monitor the concentration of NO3-N/PO4-P –Strengthen the learning algorithm to optimize the ratio of carbon source to phosphorus remover in real time	Carbon source consumption is reduced by 35%, and the TP compliance rate is >99.5%
Neutralization of toxicity of industrial wastewater	The sudden inflow of heavy metals/toxic substances leads to the collapse of the biochemical system	–Early warning of biological toxicity sensors – Automatically start emergency dosing (such as NaHS to neutralize heavy metals) and adjust the pH	超标排放风险降低90%，应急响应<5分钟

Extended scenarios and innovative applications

Pharmacy-aeration collaborative control: The dosing system is linked with the aeration equipment to optimize the efficiency of denitrification (such as reducing the demand for carbon sources in the denitrification stage).
Mobile AR operation and maintenance: Remotely identify the drug label and guide the dispensing operation through AR glasses to reduce the rate of human error.