SMQ Smart Water System

Traditional operation and maintenance models can no longer meet the urgent demands of modern power plants for refined management, low-carbon operation, and intelligent decision-making. Green and low-carbon development has become an irreversible trend in the industrial sector, while digital and smart technologies provide new breakthroughs to address these challenges. By building the SMQ Smart Water System platform, achieving digital and intelligent upgrades for water systems, and optimizing operations, enterprises can not only reduce costs and improve efficiency but also fulfill China's "Dual Carbon" strategy and drive the transformation of thermal power plants into green, intelligent energy hubs.  

The SMQ Smart Water System integrates cutting-edge technologies such as IoT, big data, artificial intelligence, and DeepSeek to break down data silos, optimize resource allocation, enhance water treatment efficiency, reduce energy consumption, and provide data support for future process improvements and water-salt balance management. This system serves as a replicable model for the green and low-carbon transformation of the thermal power industry.  

Key Advantages of SMQ  

● AI-Powered Intelligence  

  Leveraging DeepSeek's large model and machine learning, the system enables smart monitoring, predictive maintenance, and optimized decision-making, improving water treatment efficiency while reducing energy consumption and operational costs.  

● End-to-End Data Integration & Real-Time Sharing  

  A unified data platform consolidates monitoring points across the entire water system, enabling multi-source data fusion and real-time sharing to eliminate information silos and enhance management collaboration.  

● Precise Fault Prediction & Intelligent Diagnostics  

  AI algorithms analyze historical data to provide early warnings for equipment failures, root cause analysis, and solutions, minimizing unplanned downtime and extending asset lifespan.  

● Energy & Process Optimization  

  Dynamic adjustment of water treatment parameters based on big data analytics optimizes energy usage (e.g., pump scheduling, chemical dosing), achieving 10%-20% energy savings.  

● High Compatibility & Scalability  

  Seamless integration with existing DCS/SCADA systems, modular design for easy expansion (e.g., adding new water quality indicators or process units), and adaptability to water systems of varying scales.  

● Proven Reliability in Real-World Scenarios  

  Rigorous testing and optimization in complex power plant environments ensure stable operation, with parameters and control strategies calibrated using real-world data for high reliability.  

Applications & Value Proposition  

The SMQ Smart Water System, powered by AI, IoT, and big data, is widely applied in industrial water treatment (e.g., power generation, chemical, and food industries) for water quality optimization and energy efficiency. It enables end-to-end intelligent monitoring, optimization, and decision-making—from water intake to discharge—helping users improve water resource utilization, reduce operational costs, and ensure water safety, driving the evolution of water systems toward efficiency and sustainability.  

Core Value Delivered by SMQ:  

● Cost & Efficiency Gains: AI-optimized water treatment processes reduce chemical/energy consumption and O&M costs while boosting efficiency.  

● Risk Mitigation: Real-time monitoring + predictive alerts minimize unplanned downtime and safety incidents.  

● Resource Sustainability: Precision water balance management and wastewater reuse enhance resource efficiency, supporting green initiatives.  

● Data-Driven Decision-Making: A smart analytics platform provides actionable insights for faster, more informed responses.  

● Standardized Digital Upgrade: Modular design enables flexible adoption, accelerating the shift from traditional to smart water systems.  

This closed-loop value system covers economic, safety, and sustainability dimensions, making SMQ a key enabler for high-quality development in water management.