An Intelligent Surveillance Platform for Large Metropolitan Areas with Dense Sensor Deployment

Sensors

Jorge Fernández²  Lorena Calavia²  Carlos Baladrón²  Javier M. Aguiar²  Belén Carro²  Antonio Sánchez-Esguevillas²  Jesus A. Alonso-López¹ 

[1] Alvarion Spain SL, Parque Tecnológico de Boecillo, Edificio CEEI, 3.15, Valladolid 47151, Spain; E-Mail:;Dpto. TSyCeIT, ETSIT, Universidad de Valladolid, Paseo de Belén 15, Valladolid 47011, Spain; E-Mails:

关键词: smart visual sensors;    surveillance;    intelligent detection;    security;   

DOI  :  10.3390/s130607414

来源: mdpi

【 摘 要 】

This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform's control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coverage.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.