Social media utilised to help flood-prone communities

Researchers at Dundee University are utilising social media in a bid to develop a sophisticated early-warning system for flood-prone communities.

Academics have shown how artificial intelligence (AI) can be used to extract data from Twitter – as well as crowdsourced information from mobile phone apps – to build up hyper-resolution monitoring of urban flooding.

Those behind the project, Dr Roger Wang and his colleagues from the university’s School of Science and Engineering, believe this is the first time computer vision has been applied to flooding issues.

Urban flooding is difficult to monitor due to complexities in data collection and processing.

This prevents detailed risk analysis, flooding control and validation of numerical models.

The team set about trying to solve this problem by exploring how the latest AI technology can be used to mine social media and apps for the data that users provide.

Dr Wang said: “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.” Dundee Stars players visited Tayside Children’s Hospital at Ninewells to hand out teddies gathered at last week’s “teddytoss”. Ice hockey fans throw teddies on to the rink each year at Christmas. The December 15 game saw a record number of teddies hit the ice following Justin Fox’s early goal.