NDLI: Predicting per capita violent crimes in urban areas: an artificial intelligence approach

Content Provider	Springer Nature Link
Author	Castelli, Mauro Sormani, Raul Trujillo, Leonardo Popovič, Aleš
Copyright Year	2015
Abstract	A major challenge facing all law-enforcement organizations is to accurately and efficiently analyze the growing volumes of crime data in order to extract useful knowledge for decision makers. This is an increasingly important task, considering the fast growth of urban populations in most countries. In particular, to reconcile urban growth with the need for security, a fundamental goal is to optimize the allocation of law enforcement resources. Moreover, optimal allocation can only be achieved if we can predict the incidence of crime within different urban areas. To answer this call, in this paper we propose an artificial intelligence system for predicting per capita violent crimes in urban areas starting from socio-economic data, law-enforcement data and other crime-related data obtained from different sources. The proposed framework blends a recently developed version of genetic programming that uses the concept of semantics during the search process with a local search method. To analyze the appropriateness of the proposed computational method for crime prediction, different urban areas of the United States have been considered. Experimental results confirm the suitability of the proposed method for addressing the problem at hand. In particular, the proposed method produces a lower error with respect to the existing state-of-the art techniques and it is particularly suitable for analyzing large amounts of data. This is an extremely important feature in a world that is currently moving towards the development of smart cities.
Starting Page	29
Ending Page	36
Page Count	8
File Format	PDF
ISSN	18685137
Journal	Journal of Ambient Intelligence and Humanized Computing
Volume Number	8
Issue Number	1
e-ISSN	18685145
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-12-11
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Evolutionary Computation Crime Prediction Urban Security Semantics Local Search Computational Intelligence Artificial Intelligence (incl. Robotics) Robotics and Automation User Interfaces and Human Computer Interaction
Content Type	Text
Resource Type	Article
Subject	Computer Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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