Predicting burglaries and other incidents

K. Srinivasan, Technische Universiteit Eindhoven (TUE). Stan Ackermans Instituut. Software Technology (ST)

    Research output: ThesisEngD Thesis

    218 Downloads (Pure)

    Abstract

    Predicting Burglaries and Other Incidents (PBOI) is a project to estimate the possibilities of burglary at a given location at a specified time duration. Crime prediction using fixed-location observation points are being used by police. Prediction using location-independent methods, which use a variety of environmental and other additional sources (data), is currently being explored by researchers.
    PBOI is a pilot-project to study the feasibility of estimating burglaries using machine learning methods, which uses data from Interpolis/Achmea, Dutch police, TNO and a number of open data sources.
    PBOI uses open-source tools to import, analyze, generate a model (using data), and generate predictions. The model is generated using a machine learning algorithm. The algorithm is used to model systems from historic data, which can be mapped to non-parametric functions with independent variables.
    Based on the findings and a comparative study, the special algorithm performs better than others on the crime prediction domain. The predictions are populated on a map, which can help police and insurance professionals, to make informed decisions and to avoid burglaries and inform clients respectively.
    Original languageEnglish
    Awarding Institution
    Supervisors/Advisors
    • Vanschoren, Joaquin, Promotor
    • Nieuwkuijk, van, Sjak, Promotor, External person
    • Ringeling, Johan, External supervisor, External person
    Award date25 Sep 2015
    Place of PublicationEindhoven
    Publisher
    Print ISBNs978-90-444-1379-3
    Publication statusPublished - 25 Sep 2015

    Bibliographical note

    Eindverslag

    Fingerprint

    Dive into the research topics of 'Predicting burglaries and other incidents'. Together they form a unique fingerprint.

    Cite this