3 research outputs found
Scheduling for Multi-Camera Surveillance in LTE Networks
Wireless surveillance in cellular networks has become increasingly important,
while commercial LTE surveillance cameras are also available nowadays.
Nevertheless, most scheduling algorithms in the literature are throughput,
fairness, or profit-based approaches, which are not suitable for wireless
surveillance. In this paper, therefore, we explore the resource allocation
problem for a multi-camera surveillance system in 3GPP Long Term Evolution
(LTE) uplink (UL) networks. We minimize the number of allocated resource blocks
(RBs) while guaranteeing the coverage requirement for surveillance systems in
LTE UL networks. Specifically, we formulate the Camera Set Resource Allocation
Problem (CSRAP) and prove that the problem is NP-Hard. We then propose an
Integer Linear Programming formulation for general cases to find the optimal
solution. Moreover, we present a baseline algorithm and devise an approximation
algorithm to solve the problem. Simulation results based on a real surveillance
map and synthetic datasets manifest that the number of allocated RBs can be
effectively reduced compared to the existing approach for LTE networks.Comment: 9 pages, 10 figure
An intelligent surveillance platform for large metropolitan areas with dense sensor deployment
Producción CientíficaThis 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 coveraMinisterio de Industria, Turismo y Comercio and the Fondo de Desarrollo Regional (FEDER) and the Israeli Chief Scientist Research Grant 43660 inside the European Eureka Celtic project HuSIMS (TSI-020400-2010-102)
Sistema de vídeo vigilancia semántico basado en movimiento. Aplicación a la seguridad y control de tráfico
Se realiza el diseño y la arquitectura de un sistema de videovigilancia semántico orientado al control de tráfico. A partir de los datos provenientes de una red de sensores visuales inteligentes y basándose en el conocimiento definido en una ontología, el sistema automáticamente detecta e identifica las alarmas ocurridas en la escena. Este trabajo se ha desarrollado dentro del proyecto Europeo Celtic HuSIMS.Teoría de la Señal y Comunicaciones e Ingenieria TelemáticaMáster en Investigación en Tecnologías de la Información y las Comunicacione