The group standard T/CAPS 161—2026, Technical Requirements for Artificial Intelligence (AI) Smart Water Remote Monitoring Systems, jointly drafted by Shanghai Liancheng (Group) Co., Ltd. and eight other organizations, has recently been officially released.
As one of China’s early group standards focusing on the deep integration of artificial intelligence and remote monitoring for smart water management, the standard represents an important step in the development of technical guidance for AI-enabled water systems.
Its release provides a structured technical reference for applying AI to data acquisition, intelligent analysis, operational decision support, abnormal-condition detection and remote control across water infrastructure.
As next-generation information technologies become increasingly integrated with the water industry, smart water management has become an important pathway for improving operational efficiency, service quality and infrastructure management.
China has already released a range of national and industry standards for smart water applications, covering areas such as data acquisition, data transmission and platform construction. However, the rapid development of artificial intelligence is continuously expanding the potential applications of remote water monitoring.
Existing standard systems have provided limited technical guidance for AI algorithm models, intelligent analysis, adaptive optimization and autonomous operational decision support. The formulation of T/CAPS 161—2026 responds to this emerging need and provides technical support for the standardized application of AI in remote water monitoring systems.
The standard helps address a gap in technical guidance for AI-enabled water monitoring and establishes a clearer reference for system design, deployment, operation and maintenance.
T/CAPS 161—2026 establishes a systematic framework for applying artificial intelligence to smart water remote monitoring. Its technical requirements cover system architecture, multi-source data acquisition, AI model operation, intelligent scheduling, remote control, abnormal-condition detection and predictive maintenance.
The system architecture follows the complete process of data collection, transmission, processing, analysis and control. It is divided into five functional layers:
The standard defines hardware requirements for AI-based multi-source data acquisition and fusion. It covers intelligent sensing systems used to collect critical water-management parameters, including:
Remote monitoring systems should support the deployment, operation and inference of AI models. Where appropriate, AI models may be combined with mechanism-based models to enable hybrid modeling and coordinated decision-making.
AI algorithms may be configured with adaptive or updating capabilities according to operational requirements, allowing models to be optimized using newly collected data.
Based on pipeline-network or process models, operational data and forecasting results, optimization algorithms can generate scheduling recommendations. These capabilities provide technical support for more informed operating decisions and coordinated remote control.
By analyzing historical flow, pressure and leakage-monitoring data, AI systems can help identify potential pipeline leakage risks, locate possible leakage areas and support predictive maintenance. This shifts water-system management from reactive fault handling toward earlier detection and preventive intervention.
The release of T/CAPS 161—2026 is expected to support the standardized development and practical implementation of AI smart water remote monitoring systems in several important areas.
As an innovative technology enterprise in the smart water sector, Shanghai Liancheng (Group) Co., Ltd. has long been engaged in the digital transformation of water infrastructure.
Liancheng continues to integrate artificial intelligence, the Internet of Things, digital twins and other advanced technologies with practical water-management applications. Through full-process and multi-scenario AI smart water solutions, the company aims to support safer monitoring, more efficient operation and more intelligent lifecycle management for water utilities and infrastructure operators.