A Resilient Solution for Sewer Overflow Monitoring Across Cloud and Edge
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Demo Track. Pages 8522-8525.
https://doi.org/10.24963/ijcai.2026/994
Keywords
- AI: Planning and Scheduling
- AI: Humans and AI
- AI: Multidisciplinary Topics and Applications
- AI: AI Ethics, Trust, Fairnes
Abstract
Aging combined sewer systems in many historical cities are increasingly stressed by extreme rainfall events, which can trigger combined sewer overflows (CSO) with significant environmental and public health impacts. Forecasting the filling dynamics of overflow basins is critical for anticipating capacity exceedance and enabling timely preventive actions for CSO. We present a web-based demonstrator that integrates Deep Learning forecasting methods in both cloud and edge settings into an interactive monitoring dashboard for overflow monitoring, resilient to network outages.
@inproceedings{ijcai2026p994,
title = {A Resilient Solution for Sewer Overflow Monitoring Across Cloud and Edge},
author = {Singh, Vipin and Ling, Tianheng and Ghaly, Peter and Grimmeisen, Felix and Schiele, Gregor and Biessmann, Felix},
booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-26}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Diego Calvanese},
pages = {8522--8525},
year = {2026},
month = {8},
note = {Demo Track},
doi = {10.24963/ijcai.2026/994},
url = {https://doi.org/10.24963/ijcai.2026/994},
}
TY - CPAPER TI - A Resilient Solution for Sewer Overflow Monitoring Across Cloud and Edge AU - Singh, Vipin AU - Ling, Tianheng AU - Ghaly, Peter AU - Grimmeisen, Felix AU - Schiele, Gregor AU - Biessmann, Felix T2 - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2026 SP - 8522 EP - 8525 DO - 10.24963/ijcai.2026/994 UR - https://doi.org/10.24963/ijcai.2026/994 ER -Copied
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