UCL Jill Dando Institute of Security and Crime Science


Smart Tagging and Proximity Detection for Crime Reduction

12 December 2019

Research summary
The electronic tagging of criminals to track their movement is already used with the aim of preventing crime. For example, electronic tags that use GPS monitoring are employed to ensure that offenders comply with Home Detention Curfews. However, GPS technology has limitations as it operates mainly in outdoor environments, which means that GPS signals can be lost in indoor environments, such as shopping malls or hospitals.

Near Feld Communications (NFC) and Bluetooth Low Energy (BLE) Beacons can be utilised as valuable alternatives to detect the presence of a criminal in a place. Furthermore, such technologies can be used for purposes other than tracking offenders. In the context of domestic abuse, such technology might be used as a panic alarm or to trigger the collection of evidence using connected smart devices, e.g. small NFC “dots” could be placed around the home so that when tapped by a phone (or wearable), they send an alert to trusted members of a victim’s network.  

These types of technologies are often used for contactless payments or other purposes in retail environments and they are increasing in ubiquity.  However, there has been little to no exploration of their potential utility in the context of crime reduction. Also important is the fact that these emerging technologies are supported by most smart phones, tablets, and they are highly affordable and portable in nature. The technologies are constantly evolving and being adopted in various contexts e.g. shopping malls, city council premises, and hospitals.

The project aims to explore the utility of these tagging and proximity detection technologies for crime prevention including identifying two case studies and potential users (i.e. applications), in which tagging and proximity detection could be utilised, and then developing and evaluating a prototype for each case study.

Lead investigator(s):
Dr Eiman Kanjo – Nottingham Trent University 

Research assistant(s):
Dario Ortega Anderez – Nottingham Trent University 

A COVID-19-Based Modified Epidemiological Model and Technological Approaches to Help Vulnerable Individuals Emerge from the Lockdown in the UK

For information about this project contact: Dr Eiman Kanjo