According to United Nations Office for Disaster Risk Reduction, 79,732 people were killed by 321 natural disasters like floods and earthquakes in India between 2000 and 2019.Under its "Google Research" imprint, one of the world's largest tech companies is using machine learning to address one of the most prominent disasters in India and the world - riverine floods. According to Sella Nevo, a software engineer at Google who heads the Google Flood Forecasting Initiative, artificial intelligence can effectively help them send out flood warnings way before traditional methods.
India and China collectively account for the most loss of life and infrastructural damage due to natural disasters. According to United Nations Office for Disaster Risk Reduction, 79,732 people were killed by 321 natural disasters like floods and earthquakes in India between 2000 and 2019. In addition, 108 crore people were directly affected by disasters in terms of livelihood, displacement, and more.
Google is trying to change that. Under its "Google Research" imprint, one of the world's largest tech companies is using machine learning to address one of the most prominent disasters in India and the world - riverine floods. In the absence of mitigation measures and early warning systems, a lot of lives that can be saved are lost to natural disasters.
Using artificial intelligence, Google has developed an early warning system. According to Sella Nevo, a software engineer at Google who heads the Google Flood Forecasting Initiative, artificial intelligence can effectively help them send out flood warnings way before traditional methods.
Pilot programme in India
The pilot programme for this AI-based flood forecasting system was started in Bihar, India. Nevo highlighted how Google assists government with their goals. While the government assesses potential floods, it cannot predict areas that would be affected. By using satellite images, Google essentially creates a model of areas that are most likely to be hit by floods based on the river's trajectory. A prediction of the river's flood is created, based on which warnings are issued.
The company can help send out flood warnings to people two days in advance. With further research, Google hopes to improve the capabilities to five days in advance, giving a longer window of time for people to seek shelter.
So far, Google has sent out 100 million Android notifications to save lives of people in areas that could face flooding, Sella Nevo claimed. "Forecasting can prevent 30-50 per cent damage," he added.
What's the future of Google's flood forecasting?
By constantly improving AI by feeding it expansive data, Google's "top priority is getting these alerts to more people." So far, Nevo's team has helped 360 million people in India and Bangladesh.
The biggest roadblock is the lack of internet access in many regions. To overcome this challenge, Google is helping build a community-based alert system with help from local NGOs, Nevo said during the "Inventors @ Google" segment on November 11.
And no, you don't need to sign up for anything to be in tune with such warnings. The warning system is integrated into Google Maps and Google Search where just typing in the word "flood" followed by your location will give the right information.
How does AI help?
The AI employs two primary models to predict flooding. The "hydrologic model" helps scientists predict the water level in a river at any given time. "We have an error of 12 centimetres," Nevo added.
The "invasion model" translates the river into a map of sorts to identify areas that will be flooded. The error rate in this model stands at about 100 metres. While it may not tell you the exact place where flooding will occur, it can help save villages and neighbourhoods that are most likely to get hit by flooding. For now, the focus for Google and Nevo has shifted from improving accuracy to "providing it to more people."
For now, the predictive model only takes into account riverine flooding and not flash floods, which Nevo hopes to pursue "may be in the future." In response to a question by Indiatimes, Nevo highlighted how Google and his team are making the tool more accessible. First off, open sourcing of the code may "help others scale up." To this end, Nevo and team have "sent in hydraulics model for open source" which is currently under review.
Nevo also believes that "machine learning systems can adapt to changes in climate faster than classic hydrologic systems." With help from local disaster management agencies and the Central Water Commission, under the aegis of Indian government, Google hopes to save more lives in the future.
Sources:
Indiatimes.com
Provided by the IKCEST Disaster Risk Reduction Knowledge Service System
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