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ISPRS Int. J. Geo-Inf. 2017, 6(1), 31; doi:10.3390/ijgi6010031

Detection of Electronic Anklet Wearers’ Groupings throughout Telematics Monitoring

1
Electrical Engineering Department, Technology College, Universidade de Brasília, Brasilia DF 70910-900, Brazil
2
Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Computer Science and Engineering, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor José García Santesmases, 9, Ciudad Universitaria, Madrid 28040, Spain
3
Department of Convergence Security, Sungshin Women’s University, 249-1 Dongseon-dong 3-ga, Seoul 136-742, Korea
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Chi-Hua Chen, Kuen-Rong Lo and Wolfgang Kainz
Received: 8 October 2016 / Revised: 19 December 2016 / Accepted: 5 January 2017 / Published: 22 January 2017
(This article belongs to the Special Issue Applications of Internet of Things)
View Full-Text   |   Download PDF [1639 KB, uploaded 22 January 2017]   |  

Abstract

Ankle bracelets (anklets) imposed by law to track convicted individuals are being used in many countries as an alternative to overloaded prisons. There are many different systems for monitoring individuals wearing such devices, and these electronic anklet monitoring systems commonly detect violations of circulation areas permitted to holders. In spite of being able to monitor individual localization, such systems do not identify grouping activities of the monitored individuals, although this kind of event could represent a real risk of further offenses planned by those individuals. In order to address such a problem and to help monitoring systems to be able to have a proactive approach, this paper proposes sensor data fusion algorithms that are able to identify such groups based on data provided by anklet positioning devices. The results from the proposed algorithms can be applied to support risk assessment in the context of monitoring systems. The processing is performed using geographic points collected by a monitoring center, and as result, it produces a history of groups with their members, timestamps, locations and frequency of meetings. The proposed algorithms are validated in various serial and parallel computing scenarios, and the correspondent results are presented and discussed. The information produced by the proposed algorithms yields to a better characterization of the monitored individuals and can be adapted to support decision-making systems used by authorities that are responsible for planning decisions regarding actions affecting public security. View Full-Text
Keywords: anklet monitoring and tracking; detection algorithms; geoprocessing; Law Enforcement Telecommunications Systems (LETS); sensor data fusion anklet monitoring and tracking; detection algorithms; geoprocessing; Law Enforcement Telecommunications Systems (LETS); sensor data fusion
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lima Machado, P.; de Sousa, R.T.; de Oliveira Albuquerque, R.; García Villalba, L.J.; Kim, T.-H. Detection of Electronic Anklet Wearers’ Groupings throughout Telematics Monitoring. ISPRS Int. J. Geo-Inf. 2017, 6, 31.

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