Essay On Hurricanes And The Internet Of Things And Big Data Save Lives

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Hurricanes And The Internet of Things And Big Data Saves Lives Over the last couple of weeks I have been in Houston working with a Search and Rescue (SAR) team helping to find, recover, and relocate individuals affected by Hurricane Harvey. I traveled with a team from Harbinger Technologies Group (HTG) that was comprised of special operations veterans, law enforcement, EMT/Firefighters, communications, etc. We were broken into two units - water and land rescue. Having been in several natural disasters over the past 20-years, it is amazing how the evolution of technology, especially the Internet of Things (IoT), has matured and is saving lives. Although the severity of the disasters might increase, I believe the loss of life has been…show more content…
Through social media, my team and I also connected with volunteers and families affected by the storm via Facebook, Twitter, and Snapchat asking us to check on relatives and family members, pets, and property affected by the flooding. No rescue or wellness check was too big or too small. Leveraging Big Data to predict, prepare, and prevent Even before Harvey hit landfall, organizations like NASA, NOAA, municipalities and other agencies were using sensor data, surveillance, and satellite imagery to predict not just where the storm was likely to impact, but also coordinating with first responders and law enforcement to identify staging locations, evacuation routes, likely flooding areas, etc.. Data collected from sensors and meters located throughout the region were mined and machine learning algorithms applied to predict patterns and outcomes based on past, present, and future behaviors. For example, using clustering algorithms helped to determine the probability of where flooding would occur and devising a set of recommendations for evacuation routes, resource staging, and the identification of locations for shelters along these routes. As more data is collected the more insight these agencies had to compare against other operations like regression algorithms to forecast future behavior based on past incidents such as previous hurricanes or flood tracking. This gives officials more detailed

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