Title: Extended results from the measurement and analysis of safety in a large city

Authors: Rami Ibrahim; M. Omair Shafiq

Addresses: School of Information Technology, Carleton University, Ottawa, Ontario, Canada ' School of Information Technology, Carleton University, Ottawa, Ontario, Canada

Abstract: This paper presents an extended version of our measurement and analysis of data from the city of Los Angeles (Ibrahim and Shafiq, 2017). More specifically, we analysed datasets about crimes that took place in Los Angeles. This dataset was prepared by the Los Angeles Police Department (LAPD) and is also updated on a regular basis. This dataset contains approximately 1.5 million records, where each record represents a crime incident in the city. We analysed multiple features of the dataset including different activities of crimes (i.e., number of crimes) in terms of year, month, weekdays, time of the day, area, victim sex, victim age, victim descent, suspect activities and crime seriousness index. In addition to it, we also analysed the reporting period of a crime incident by calculating the average reporting days (i.e., number of days the victim took to report a crime incident) in terms of multiple factors. Our analysis uncovers the unique characteristics and insights of safety measures and crime prevention in the city. This extended version of paper contains some new results and discussions. This includes new graphs for number of crimes based on suspect activities and crime seriousness index, a new graph for crimes distribution based on crime seriousness index, and average reporting period based on crime seriousness index. We introduced a section that provides discussion on potential implications of our analytical results.

Keywords: data analysis; smart city; crime statistics; dataset; extended version of original paper.

DOI: 10.1504/IJBDI.2019.10019310

International Journal of Big Data Intelligence, 2019 Vol.6 No.2, pp.86 - 101

Received: 16 Mar 2018
Accepted: 22 Jun 2018

Published online: 09 Apr 2019 *

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