Geographical Information System Based Safe Path Recommender
Aman Jain1, Simran Sharma2, Hrishav Kumar3, Deepak Parashar4
1Aman Jain, Jaypee Institute of Information Technology, Noida Sector 62, Pursuing Final year of B. Tech in Computer Science and Engineering.
2Hrishav Kumar, Computer Science Student from Jaypee Institute of Information Technology (Graduating in 2020)
3Deepak Parashar, Computer Science Student from Jaypee Institute of Information Technology (Graduating in 2020).
4Simran Sharma, Jaypee Institute of Information Technology, Noida Sector 62, Pursuing 4th Year of B. Tech in Computer Science and Engineering
Manuscript received on 08 August 2019 | Revised Manuscript received on 15 August 2019 | Manuscript published on 30 August 2019 | PP: 3863-3868 | Volume-8 Issue-10, August 2019 | Retrieval Number: J98950881019/19©BEIESP | DOI: 10.35940/ijitee.J9895.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The threat to women safety, especially on road, has become a major concern these days and the problem is increasing dramatically. Women are unsafe not just in the night but also in the day, they fear getting assaulted not only in public transport but also while travelling in cars and two-wheelers. People are harassed on road in various ways like robberies, killings, etc., but women go through even bigger traumas. Cases like, rape in moving cars, sexual assault and robberies by forcefully stopping the vehicle, teasing women on two-wheelers, etc. have increased to an alarming level. This study is an initiative to safe-guard the self-esteem of our women and prevent them from any ugly experience, while on road. It aims to find and suggest the safest path for women and tells the level of crime of the locations in that path, while travelling from one place to another. The system determines the various paths from source to destination, as entered by the user on the map interface, by calculating the danger index. This index is found on the basis of the crime rate of the grouped locations. These locations are grouped by clustering them on the basis of the crime history of that location. The app as a result suggests the best three paths in different colours (Green, Red, Yellow).
Keywords: Crime Against Women; Safest Path; Maps; Location; Clustering of Locations.
Scope of the Article: Community Information Systems