Dr Roger Wang (pictured above) and colleagues from the School of Science and Engineering have combined Twitter, citizen science and cutting-edge artificial intelligence (AI) techniques to develop an early-warning system for flood-prone communities.
The researchers showed how AI can be used to extract data from Twitter and crowd-sourced information from mobile phone apps to build up hyper-resolution monitoring of urban flooding. They believe this is the first time that Computer Vision has been applied to flooding issues.
Applying these methods in case studies, they found these methods to be genuinely informative and that AI can play a key role in future flood warning and monitoring systems.
Dr Wang said, “Sea levels have been rising at an average rate of 3.4mm a year over the past decade. The extremes of today will become the average of the future so coastal cities and countries must take action to protect their land.
“A tweet can be very informative in terms of flooding data. Key words were our first filter, then we used natural language processing to find out more about severity, location and other information. Computer vision techniques were applied to the data collected from MyCoast, a crowdsourcing app, to automatically identify scenes of flooding from the images that users post.
“We found these big data-based flood monitoring approaches can definitely complement the existing means of data collection and demonstrate great promise for improving monitoring and warnings in future.”