100
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

Automating Evidence Collection at the Crime Scene Using RFID Technology for CBRN Events

, &
Pages 3-11 | Received 12 Mar 2012, Accepted 05 Jul 2012, Published online: 12 Sep 2012
 

Abstract

In forensic management, radio frequency identification (RFID) technology has a potential to improve the chain of evidence, automate the control of exhibits moving out from a hot zone, help locate exhibits in the property control unit (PCU), and reduce human errors and the amount of paperwork due to duplicate data entry. The goal of this paper is to experimentally investigate the efficacy of RFID technology for evidence gathering in a hot zone and for controlling entry to and exit from the hot zone of first responders and exhibits. We performed three evaluation exercises where forensic technicians had a chance to experiment and evaluate the technology as it applied to their duties. Long-range passive RFID technology in the ultra high frequency (UHF) range was used. Based on our observations and the interviews with the forensic technicians who participated in the exercises, we conclude that the technology is suitable for tagging the exhibits and that it has a good potential for controlling the exit point of exhibits and first responders.

Acknowledgments

This work was supported by DRDC Centre for Security Science CBRN Research & Technology Initiative project CRTI 06-0317TD PROBE — Crime Scene Support Tool for Police, Hazmat & EMS, and Toronto Police Services (TPS) Forensic Identification Services (FIS), as well as the RCMP Integrated Forensic Identification Services (IFIS).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access
  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart
* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.