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2019 | OriginalPaper | Chapter

Vision and Crowdsensing Technology for an Optimal Response in Physical-Security

Authors : Fernando Enríquez, Luis Miguel Soria, Juan Antonio Álvarez-García, Fernando Sancho Caparrini, Francisco Velasco, Oscar Deniz, Noelia Vallez

Published in: Computational Science – ICCS 2019

Publisher: Springer International Publishing

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Abstract

Law enforcement agencies and private security companies work to prevent, detect and counteract any threat with the resources they have, including alarms and video surveillance. Even so, there are still terrorist attacks or shootings in schools in which armed people move around a venue exercising violence and generating victims, showing the limitations of current systems. For example, they force security agents to monitor continuously all the images coming from the installed cameras, and potential victims nearby are not aware of the danger until someone triggers a general alarm, which also does not give them information on what to do to protect themselves. In this article we present a project that is being developed to apply the latest technologies in early threat detection and optimal response. The system is based on the automatic processing of video surveillance images to detect weapons and a mobile app that serves both for detection through the analysis of mobile device sensors, and to send users personalised and dynamic indications. The objective is to react in the shortest possible time and minimise the damage suffered.

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Metadata
Title
Vision and Crowdsensing Technology for an Optimal Response in Physical-Security
Authors
Fernando Enríquez
Luis Miguel Soria
Juan Antonio Álvarez-García
Fernando Sancho Caparrini
Francisco Velasco
Oscar Deniz
Noelia Vallez
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-22750-0_2

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