The 12th International Conference on Water Resource and Environment (WRE 2026)

Abstract: This talk presents an integrated Water–Energy–AI Nexus framework for accelerating decarbonization and the transition toward a circular economy in the wastewater sector. The proposed framework explores how artificial intelligence (AI) can bridge water management and energy systems through three interconnected research topics: (1) AI-driven forecasting of wastewater influent characteristics to enable proactive and adaptive operation under dynamic influent conditions, (2) AI-driven autonomous operation of full-scale wastewater treatment plants (WWTPs) to enhance treatment performance while minimizing energy consumption, and (3) AI-assisted optimization of integrated biogasification systems to facilitate waste-to-energy conversion and resource recovery, including biogas and hydrogen production, through process design, organic waste supply-chain optimization, techno-economic assessment, and environmental evaluation. These studies demonstrate the potential of AI to integrate water and energy systems across multiple scales, ranging from process-level monitoring and autonomous control to system-level optimization and regional infrastructure planning. As the wastewater sector transitions from conventional pollutant removal toward integrated water and energy resource recovery, the Water–Energy–AI Nexus offers a promising pathway for transforming conventional WWTPs into intelligent, resource-efficient, and potentially energy-positive infrastructures, thereby contributing to decarbonization and a circular economy.