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Item type:Publication, Access status: with files , Digital-twin-based management of sewer systems: research strategy for the KaSyTwin project(Multidisciplinary Digital Publishing Institute (MDPI), 2025-01-22); ; ; ; Sewer infrastructure is vital for flood prevention, environmental protection, and public health. As part of sewer infrastructure, sewer systems are prone to degradation. Traditional maintenance methods for sewer systems are largely manual and reactive and rely on inconsistent data, leading to inefficient maintenance. The KaSyTwin research project addresses the urgent need for efficient and resilient sewer system management methods in Germany, aiming to develop a methodology for the semi-automated development and utilization of digital twins of sewer systems to enhance data availability and operational resilience. Using advanced multi-sensor robotic platforms equipped with scanning and imaging systems, i.e., laser scanners and cameras, as well as artificial intelligence (AI), the KaSyTwin research project focuses on generating digital twin-enabled representations of sewer systems in real time. As a project report, this work outlines the research framework and proposed methodologies in the KaSyTwin research project. Digital twins of sewer systems integrated with AI technologies are expected to facilitate proactive maintenance, resilience forecasting against extreme weather events, and real-time damage detection. Furthermore, the KaSyTwin research project aspires to advance the digital management of sewer systems, ensuring long-term functionality and public welfare via on-demand structural health monitoring and non-destructive testing.Publicationtype: Journal Article19 23 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Digital twins for sewer systems maintenance: a systematic literature review(Springer, 2025); ; Sewage systems are critical urban infrastructure elements, essential for flood prevention, environmental protection, and public health. As part of sewage system infrastructure, and similar to other infrastructure, sewer systems are deteriorating due to aging. Current maintenance measures for sewer systems predominantly rely on manual processes based on heterogeneous and inconsistent data. However, digital sewer models are expected to facilitate proactive maintenance strategies to mitigate damage and extend the lifespan of sewer systems. This paper investigates current state-of-the-art research concerning the implementation of digital twins in sewer system maintenance during the operating phase through a systematic literature review (SLR). The findings indicate that digital twins offer numerous advantages for proactive maintenance in sewer systems, specifically for sewer system assessment and damage prognosis. Nonetheless, in the current body of research, confusion between digital twins and simpler digital shadows and digital models is apparent. Furthermore, the implementation of digital twins for sewer system maintenance is associated with several challenges, including data-related, technological, and methodological challenges. Finally, the outcome of the SLR sheds light on potential research directions towards realizing digital twins based on building information modeling (BIM), e.g., BIM-based digital twins, for sewer system maintenance.Publicationtype: Conference Paper16