CROWDSAFE: crowd sourcing of crime incidents and safe routing on mobile devices

  • Authors:
  • Sumit Shah;Fenye Bao;Chang-Tien Lu;Ing-Ray Chen

  • Affiliations:
  • Virginia Tech;Virginia Tech;Virginia Tech;Virginia Tech

  • Venue:
  • Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
  • Year:
  • 2011

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Abstract

Crowd sourcing is based on a simple but powerful concept: Virtually anyone has the potential to plug in valuable information. The concept revolves around large groups of people or community handling tasks that have traditionally been associated with a specialist or small group of experts. With the advent of the smart devices, many mobile applications are already tapping into crowd sourcing to report community issues and traffic problems, but more can be done. While most of these applications work well for the average user, it neglects the information needs of particular user communities. We present CROWDSAFE, a novel convergence of Internet crowd sourcing and portable smart devices to enable real time, location based crime incident searching and reporting. It is targeted to users who are interested in crime information. The system leverages crowd sourced data to provide novel features such as a Safety Router and value added crime analytics. We demonstrate the system by using crime data in the metropolitan Washington DC area to show the effectiveness of our approach. Also highlighted is its ability to facilitate greater collaboration between citizens and civic authorities. Such collaboration shall foster greater innovation to turn crime data analysis into smarter and safe decisions for the public.