title: The role of predictive policing in predicting spatio-temporal crime mapping
metadata.name: dc.contributor.author
metadata.value: Abdulkareem, Fahil Abdulbasit A.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2024-04-01T16:34:24Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2024-04-01T16:34:24Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2024-03
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Abdulkareem, Fahil Abdulbasit A. 2023. “The role of predictive policing in predicting spatio-temporal crime mapping”. Vestnik of Saint Petersburg University. Law 4: 192–205. https://doi.org/10.21638/spbu14.2024.112
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/spbu14.2024.112
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/45213
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: Since the modern criminology critically reviews the contribution of socio-environmental
  factors to the crime mapping in terms of their spatio-temporal distribution, a statistical/
  machine learning technique namely called the risk terrain modelling (RTM) is currently being
  used as a software solution to diagnose the socio-environmental conditions that lead to
  crime in a specific area’s geography (Study Area), through geospatial and temporal analyses
  of crimes by linking them to hotspots and analysing them into big data (criminal data), and
  as a result, appears the new predicting patterns of risks in geographical area under survey
  (Survey Area) in future, all that for a sake of a rapid and effective response by the Predictive
  Police, firstly, for setting the priorities for the deployment of precautionary resources to prevent
  crime and reduce potential risks in the event of a crime, and secondly, what is required
  to be done upon arrival as a precautionary step to control the crime with a minimum disadvantage
  to the police forces. The Risk Terrain Modelling represents a systematic investment
  for more than a decade in the field of criminal investigation, it is have been founded by
  Leslie W. Kennedy and Joel M. Caplan at Rutgers University, and it currently testes in over
  than 45 countries around the world.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Law;Volume 15; Issue 1
metadata.lang: -
metadata.name: dc.subject
metadata.value: predictive policing
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: near-repeat phenomenon
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: crime prediction
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: risk terrain modelling
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: artificial intelligence
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: machine learning
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: agent-based modelling
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: The role of predictive policing in predicting spatio-temporal crime mapping
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 192-205.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/45213/1/192-205.pdf
resources.format: Adobe PDF
resources.size: 653,87 kB