ABSTRACT In recent decades, China's decentralized wastewater treatment systems have been widely adopted as a flexible solution to complement centralized infrastructure. However, these systems face challenges such as fragmented management, insufficient dynamic control, high operational costs, and a lack of specialized technical support. While SCADA and PLC systems are commonly used in individual facilities, digital and intelligent operation and maintenance models remain underutilized in decentralized contexts. This study proposes and evaluates an intelligent management platform designed to address these gaps. The platform features: (1) an edge-cloud collaborative IoT framework for real-time monitoring and data integration across distributed facilities; (2) adaptive algorithms for process optimization and predictive maintenance; and (3) a visual management platform enabling centralized yet fine-grained control of multiplant clusters. The platform has been implemented in a cluster of 15 decentralized plants in Sichuan, China. Results demonstrate a significant reduction in maintenance response time from 1 month to 1 day. The adaptive algorithm successfully detected 90% of simulated anomalies with a false positive rate below 5%. This research provides a replicable technical architecture and a validated implementation pathway for the intelligent, coordinated management of decentralized wastewater treatment systems.
Wen et al. (Tue,) studied this question.