Title :
Safety index: Using ubiquitous data for a safe transportation system
Author :
Singla, M. ; Khemani, Ankur ; Jain, Abhishek ; Sood, Aditya
Author_Institution :
Dept. of Comput. Sci. & Eng., ITM Univ., Gurgaon, India
Abstract :
When it comes to any type of crime it is just not a good picture to paint. Crime is a worldwide problem that directly or indirectly touches every one of us in multiple manners: as sufferers, in paying greater costs for merchandises and amenities, besides living with the concerns of fright and corruption. Moreover, location has a significant impact on crime. We propose a system to provide optimal travel route in Gurgaon, India (chosen as sample) along different modes of transport keeping in mind the distance and safety. We shall be using different learning algorithms to train the system based on available crime statistics (using research and surveys from government/non-government organizations).
Keywords :
geographic information systems; government; graph theory; learning (artificial intelligence); safety; traffic information systems; transportation; crime statistics; learning algorithms; nongovernment organization; optimal travel route; safe transportation system; safety index; ubiquitous data; Algorithm design and analysis; Indexes; Logistics; Optimization; Roads; Safety; Shortest path problem; machine learning; map and path-optimization; safety; transport system;
Conference_Titel :
Advance Computing Conference (IACC), 2014 IEEE International
Conference_Location :
Gurgaon
Print_ISBN :
978-1-4799-2571-1
DOI :
10.1109/IAdCC.2014.6779507
