Signal 3: Minimizing Disaster Response time using Real-Time Analytics
Emergency services receive several thousands of calls during major disasters which makes it nearly impossible for them to respond to each service request. These calls can range from non-emergency situations like power outages to life and death matters like individuals trapped in fallen debris. In major cities like New York often people are not familiar with non-emergency helplines which further burdens the emergency helplines.
Real time analytics is the ideal approach to minimize response for emergency services. Smart sensors attached to power grids can alert authorities to power outages and give them a better real time understanding of power services during disasters. This will also eliminate the burden of these calls on emergency helplines and help disaster rescue efforts use their limited personnel more efficiently.
Another possible solution is the use of text messages instead of calls as emergency communications. This will reduce the need for call dispatchers manually speaking with citizens over phone. Real time texts along with social media data will provide invaluable information for real time analytics to find trends in highly affected areas. Each text can be analyzed by trained models to predict the level of emergency and type of service needed. This response can then be fed to another algorithm for route mapping of different services to maximize resource utilization and minimize average response time.
Source: https://datasmart.ash.harvard.edu/news/article/smart-grids-in-times-of-disaster-193
