Abstract
Abstract The potential of artificial intelligence (AI) in water management is widely recognised by research and practice communities alike, with an increasing number of applications showed tackling water supply, stormwater and wastewater management challenges. However, there is a critical knowledge gap in understanding the fundamental role of AI in the development of urban water infrastructure (UWI). This review aimed to provide an analysis of how AI could be aligned to support the future development of UWI systems. Four types of AI analytics – descriptive, diagnostic, predictive and prescriptive – are discussed and linked to the improvement in the performance of UWI systems from three categories: reliability, resilience and sustainability. It is envisioned that AI technology will play a pivotal role in UWI transitioning to the future through underpinning the five development pathways: decentralisation, circular economy, greening, decarbonisation and automation. The barriers in improving AI adoption in the real world are also highlighted from four dimensions: cyber-physical infrastructure, institutional governance, social-economic systems and technological development in wider society. Embedding AI in the development pathways and tackling the barriers can ensure that AI-empowered systems are deployed in an equitable and responsible way to improve the resilience and sustainability of future UWI systems.
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