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Search launched: Two buses with 22 persons missing in Maharashtra

Two buses with about 22 passengers were washed away early on Wednesday in flood waters after a bridge collapse on the Mumbai-Goa Highway

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Mumbai-Goa highway bridge collapse: Two buses with 22 persons missing. Image source: www.ibtimes.co.in
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Two buses with about 22 passengers were washed away early on Wednesday, August 3, in flood waters after a bridge collapse on the Mumbai-GoaHighway, an official said.

The state government, National Disaster Response Force, Indian Navy and Indian Coast Guard (ICG) launched a massive air and sea operation to trace the two MaharashtraState Road Transport Corporation buses and other five to six missing vehicles which were feared to have been washed away by the floods in the Arabian Sea in the coastal Konkan region.

Chief Minister Devendra Fadnavis, ministers and Raigad collector Sheetal Ugale were monitoring the situation, the official said.

Prime Minister Narendra Modi called Mr Fadnavis and offered help in the rescue operations.

The ICG deployed a Chetak and SeaKing helicopters to search the buses. An NDRF team was on the way from Pune while the police and naval divers have launched a sea search.

Of the two ill-fated buses, the Jaigad-Mumbaiservice was driven by S. S. Kamble and conducted by V. K. Desai while the Rajapur-Borivali (north Mumbai) service was driven by E. S. Munde and conducted by P. B. Shirke, all based with the Chiplun Bus Depot in Ratnagiri.

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The tragedy struck after heavy rains flooded the Savitri River which originates in Mahabaleshwar and flows through Ratnagiri-Raigad districts, leading to the collapse of a seven-decades-old British era bridge near Mahad around 1 a.m.

Image by thehindu.com
Image by thehindu.com

The buses with 11 passengers each went missing and there was no contact with either their drivers or the passengers, Raigad Collector Sheetal Ugale said.

Locals said that around five to six private vehicles were also missing and they were feared to be washed away in the floods.

“The bridge was built during the British era. After discussion with the National Highways Authority, we have shifted traffic to the new parallel bridge nearby. We are trying to confirm reports of other missing vehicles,” Ugale said.

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Rehabilitation Minister Chandrakant Patil said helicopters would be deployed and the help of defence forces was being taken to search the missing vehicles.

Incessant rains continue to lash the coastal Konkan, northern and western Maharashtra since past five days, with at least 10 persons losing their lives in rain-related incidents in the past 24 hours. (IANS)

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With the aid of Twitter and AI, researchers to develop flood warning system

In a study, published in the journal Computers & Geosciences, the researchers showed how AI can be used to extract data from Twitter and crowdsourced information from mobile phone apps to build up hyper-resolution monitoring of urban flooding.

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AI can play a key role in future flood warning and monitoring systems
AI can play a key role in future flood warning and monitoring systems

London, Dec 26: Researchers are combining Twitter, citizen science and artificial intelligence (AI) techniques to develop an early-warning system for flood-prone communities in urban areas.

In a study, published in the journal Computers & Geosciences, the researchers showed how AI can be used to extract data from Twitter and crowdsourced information from mobile phone apps to build up hyper-resolution monitoring of urban flooding.

“By combining social media, citizen science and artificial intelligence in urban flooding research, we hope to generate accurate predictions and provide warnings days in advance,” said Roger Wang from University of Dundee in Britain.

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

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

The research 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.

They found that social media and crowdsourcing can be used to complement datasets based on traditional remote sensing and witness reports.

Applying these methods in case studies, they found them to be genuinely informative and that AI can play a key role in future flood warning and monitoring systems.

“The present recording systems — remote satellite sensors, a local sensor network, witness statements and insurance reports — all have their disadvantages. Therefore, we were forced to think outside the box and one of the things that occurred to us was how Twitter users provide real-time commentary on floods,” 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,” Wang said.

The researchers applied computer vision techniques 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,” Wang said.

Twitter data was streamed over a one-month period in 2015, with the filtering keywords of “flood”, “inundation”, “dam”, “dike”, and “levee”. More than 7,500 tweets were analysed over this time.

“We have reached the point of 70 per cent accuracy and we are using the thousands of images available on MyCoast to further improve this,” Wang said.