Anita's Moonshot Codeathon


Winners announced


Thanks to all Participants!

Anita's Moonshot Codeathon



Project description

GoSafe is an application designed keeping in mind the safety of women. Women are underrepresented in almost all professional environments and we believe a major reason for that are safety concerns. In order to empower women, to help them become independent, unafraid and confident enough to take all decisions without having any second thoughts, we came to with our application, GoSafe.

  • It is an android application which provides safety information to the users. There are multiple ways in which the app takes care of this :We parse data from local newspapers using Natural Language Processing to obtain information about Theft, Harassment, Accidents, not well Illuminated Roads, CCTV Cameras, presence of Police. All six parameters are available in the form of markers in the app. A user can search any area and look for corresponding markers to analyze the safety.
  • We allow users to provide a feedback to us, which helps the safety data be up-to-date. We want users  to let us know better how safe they feel in different places. To review  any route / area, the  user can click on the map and submit a feedback. We believe that crowdsourcing this data is the best way to obtain correct information about the routes as newspapers might not cover all the information about certain incidents due to multiple reasons. The experience of one user can be helpful to multiple others.
  • The app provides a safety navigation system as well. Every time a user wants to go one from place to another, GoSafe shows the user two paths - the route suggested by Google Maps API which is the fastest route to reach the destination, and the safest route computed by our safety algorithm. The safety route is computed by calculating the safety index of all possible routes to reach the destination from a certain point and then returning the route with the highest safety index. All the negative marked areas (from the newspaper as well as the user feedback data) are given different negative weights, and the positive marked areas (data used from newspapers as well as users feedback) are given different positive weights according to their significance in deciding the safety.