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AI-trained CCTV systems are emerging as a vital tool for flood prevention by detecting blockages in urban waterways. Researchers at the University of Bath developed a software called 'AI on The River' that integrates with existing CCTV to provide early warnings of potential flooding. This proactive approach aims to identify debris and waste obstructing culverts, which are crucial for managing water flow in urban areas.
The machine learning model has shown impressive accuracy, identifying blockages with nearly 90% precision. This technology not only streamlines monitoring efforts but also enhances safety for response teams by allowing them to act before flooding occurs. The potential for global application, especially in flood-prone regions with limited resources, highlights the importance of innovative AI solutions in addressing climate change challenges.
• AI systems can proactively detect blockages to prevent urban flooding.
• Machine learning achieves nearly 90% accuracy in identifying culvert obstructions.
The article discusses how machine learning is used to train CCTV systems to identify blockages in waterways.
'AI on The River' is highlighted as a key software developed for early flood warning.
The proactive nature of the AI system allows for early detection of potential flooding risks.
The University of Bath is responsible for developing the AI technology discussed in the article.
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