A Mobile Approach Applied To Public Safety In Cities (International Journal of Engineering and Computer Science, 2014)
As the Population is increasing day by day natural and man-made disasters have become an important factor for public safety. The ultimate goal of defining crime and safety indexes is to provide users with safety advisory information. People are however not equally exposed and vulnerable to all crime types. Age, gender and an array of personal features, preferences and choices play a central role on the perception of an individual’s safety. In this paper we design, implement and deploy an application that retrieves and conveys to the user relevant information on the user’s surrounding. We propose to achieve this vision by introducing a framework for defining public safety. These information may not be readily accessible, we use the localization capabilities of a user’s mobile device to periodically record and locally store the trajectory traces with which future crime index may be predicted. Time series analysis is one of the forecasting techniques has been used in order to predict future safety values. The combination of space and time indexed crime datasets, with mobile technologies has been investigated to provide personalized and context aware safety recommendations for mobile network users. The trajectory trace of the user is used to define the chance of crime to occur around the user and generalize this approach to compute the chance of a crime to occur around groups of users.