Hydro One used an electrical-outage prediction tool developed by International Business Machines Corp. IBM 0.22% that combines AI technology and the resources of IBM’s Weather Co. subsidiary. The tool helped predict the severity of the storm and the locations that would be hardest hit, so Hydro One knew where to position 1,400 front-line staff who were needed to restore power and to handle the nearly 130,000 customer calls that came in during the outage. IBM’s outage-prediction tool is also being used, with 70% accuracy, by other cities throughout North America to predict power outages as far in advance as 72 hours before storms are expected. “During severe weather events, every hour of advance notice counts and helps minimize the impacts,” says Mary Glackin, head of weather business solutions at IBM. Many companies and universities are developing AI tools to help cities better predict and prepare for weather events and natural disasters. When cities can predict more accurately the severity of weather, natural disasters and which areas will be affected most, they can better allocate resources to prepare for relief efforts such as restoring power or evacuating residents at risk. The AI tool gets its real-time information on the strength of the earthquake and its location from sensors and damage reports. Some roadblocks still exist before wide-scale adoption of AI tools to predict and prepare for weather events and natural disasters will occur, says Seth Cutler, an environment and water program manager at research firm Frost & Sullivan.
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