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Seeing Beyond Assumptions: Revolutionising Stormwater Management with Visual AI

In the world of stormwater management, assumptions have long dictated decisions. But what if we could move from assumptions to facts, revolutionising the way we manage time, effort, and money? This paper by Abi Croutear-Foy, Managing Director of AquaWatch, unveils a groundbreaking approach that integrates visual Artificial Intelligence (AI) with real-time water quality analysis, paving the way for precise monitoring and data-driven management strategies.


FROM ASSUMPTIONS TO FACTS, SHIFTING WATER QUALITY MANAGEMENT TO BETTER MANAGE TIME, EFFORT
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At the heart of this innovative methodology lies the fusion of visual AI with continuous physical water quality parameters. By harnessing the power of machine learning and large language models, stormwater systems can now be visually monitored in real-time, enabling insights into critical aspects such as trash rack management, underground pollutant traps, and sewer overflows.


The paper showcases compelling case studies that illustrate the transformative potential of this approach. From identifying and managing clogging events in real-time to assessing the effectiveness of underground pollutant traps, and mitigating pollution risks posed by combined sewer overflows, visual AI emerges as a game-changer in stormwater management.

The utilisation of existing data alongside visual AI and water quality sensors to model and predict system behaviors in real-time is also highlighted. This shift from intermittent grab samples to continuous data feeds empowers decision-makers with comprehensive insights, allowing for the development of tailored management strategies based on factual evidence.


The implications of this data-driven approach are profound. By optimising investment decisions through predictive modeling, resources can be directed towards the most impactful solutions.


Moreover, the real-time insights provided by visual AI enable more informed, effective, and sustainable management practices, ensuring the health and functionality of stormwater systems.

In a world where environmental challenges are increasingly complex, the shift from assumptions to facts is paramount. Visual AI, combined with real-time data, can now revolutionise stormwater management, ushering in a new era of precision, efficiency, and sustainability.

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