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world , including the city of Jakarta , Indonesia . AI , machine learning and realtime data streaming have led to major improvements in disaster awareness , particularly important as the city has 13 major rivers and 40 % of its area is below sea level , leading to a long history of flooding . Climate change has had a major impact on these rivers , causing flooding to worsen in recent years .
“ Using SAS Analytics for IoT , Jakarta ’ s city government has created a dataand AI-powered flood control system similar to Istanbul ’ s approach to traffic congestion ,” Mann explains . “ Jakarta has aggregated data from sensors and weather forecasting across the city into intelligent models , which can predict water levels around high-risk areas . City officials can send push notifications to residents ’ phones , close floodgates and prepare the city as much as six hours in advance of emergency flooding . Jakarta ’ s smart models not only prevent potential damage to the city but protect the lives of citizens living in flood-prone zones .”
Cary , North Carolina , is another example of how analytics has helped a government regain control of a city after the population has tripled in size over the last 25 years . Cary , therefore , saw an influx of residents , which led to a boom in new housing , shopping centres and businesses . Mann explains that now , the town has a team dedicated to using “ cutting-edge technology ” to benefit the community , including IoT analytics to safeguard against flooding events .
Many more communities can emulate Istanbul , Jakarta and Cary by using data and analytics to drive better and faster decisions that support sustainability and smart-city goals . sustainabilitymag . com 121