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An Interdisciplinary Web-based Framework for Data-driven Placement Analysis of CCTV Cameras
Blekinge Tekniska Högskola,Institutionen för datavetenskap.
Blekinge Tekniska Högskola,Institutionen för datavetenskap.
Blekinge Tekniska Högskola,Institutionen för datavetenskap.
Malmö University, Faculty of Health and Society (HS), Department of Criminology (KR).ORCID iD: 0000-0002-2145-113X
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2021 (English)In: Proceedings of the 2021 Swedish Workshop on Data Science (SweDS), IEEE, 2021, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes work in progress of an interdisciplinary research project that focuses on the placement and analysis of public close-circuit television (CCTV) cameras using data-driven analysis of crime data. A novel web-based prototype that acts as a framework for the camera placement analysis with regards to historical crime occurrence is presented. The web-based prototype enables various analyses involving public CCTV cameras e.g., to determine suitable locations for both stationary CCTV cameras as well as temporary cameras that are moved around after a few months to address crime seasonality. The framework also opens up for other analyses, e.g. automatically highlighting crimes that are carried out closed by at least one camera. The research also investigates to what extent it is possible to generate estimates on the amount of detail captured by a camera given the distance to the crime light conditions. The research project includes interdisciplinary competences from various areas such as criminology, computer and data science as well as the Swedish Police.

Place, publisher, year, edition, pages
IEEE, 2021. p. 1-6
Keywords [en]
CCTV camera placement, data-driven placement analysis, web-based prototype, intelligent models
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mau:diva-54491DOI: 10.1109/SweDS53855.2021.9637719ISI: 000833296400002Scopus ID: 2-s2.0-85123850535ISBN: 9781665418300 (print)OAI: oai:DiVA.org:mau-54491DiVA, id: diva2:1689291
Conference
9th Swedish Workshop on Data Science (SweDS), DEC 02-03, 2021, Linnaeus Univ, ELECTR NETWORK
Available from: 2022-08-22 Created: 2022-08-22 Last updated: 2024-02-05Bibliographically approved

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Gerell, Manne

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CiteExportLink to record
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  • apa
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Output format
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