Challenging issues in visual sensor networks

A Survey of Image Compression Algorithms for Visual Sensor Networks

“…A few number of related review papers have been proposed in the literature [1][2][3][4][5]. An extensive survey of wireless multimedia sensor networks is provided in [1], where the state of the art in algorithms and protocols at the application, (2) we introduce some notions behind the compressive sensing, and its possible application to VSN, (3) we provide a brief overview of each compression method, the advantages and shortcomings of their application in VSN, a literature review of their application in VSN, as well as an open research issue for each compression method, (4) we conclude by some guidelines which concern the design of a compression method for VSN.…”

A routing mechanism based on the sensing relevancies of source nodes for time-critical applications in visual sensor networks

“…The size in bits of all protocol headers in each packet is defined as z, resulting in an effective payload area of (k -z) in each data packet. ( ) (1) We could extend the basic formulation in (1) adding the energy costs for transmissions and receptions of ACK messages and for the radio hardware switching among the transmitting, receiving and sleeping modes. Moreover, the average packet error rates and retransmissions could be accounted, as expressed in [18].…”

“…Group of relevance 2 available paths (p 1 < p 2 ) p 1 Maximum and high relevance packets p 2 Medium and low relevance packets 3 available paths (p 1 < p 2 < p 3 ) p 1 Maximum relevance packets p 2 High relevance packets p 3 Medium and low relevance packets 4 available paths (p 1 < p 2 < p 3 < p 4 ) p 1 Maximum relevance packets p 2 High relevance packets p 3 Medium relevance packets p 4 Low relevance packets 5 or more available paths (p 1 < p 2 < p 3 < p 4 < p (4 + i) ) p 1 Maximum relevance packets p 2 High relevance packets p 3 Medium relevance packets p 4 Low relevance packets p (4 + i) Backup paths…”

“…Visual sensor networks (VSNs) are composed of resourceconstrained self-organizing nodes where some or all of them are endowed with a low-power camera for a series of innovative multimedia sensing functions [1] [2]. Visual information retrieved from the monitored field in the form of video streaming, conventional snapshots, infrared or thermal images can significantly enhance a large set of monitoring applications, besides fostering the development of new ones [3] [4].…”

Energy Efficient Data Processing in Visual Sensor Network

“…In the following sections we present an overview of the ongoing research in several areas vital to visual sensor networks: Sensor localization and camera calibration in distributed camera sensor networks by A. Barton-Sweeney, D. Lymberopoulos, and A. Savvides, do not provide for fully automatic camera calibration methods, but instead they point out the difficulty of finding appropriate network configurations that can ease the calibration process [5]. Panoptes: scalable low-power video sensor networking technologies by E. Kaiser, M. Shea, W.-C. Feng, and L. Bavoil proposed the first video-based sensor network systems, and it includes video sensors built from COTS and software that supports different functions including capture, compression, filtering, video buffering and streaming [5]. Balancing computational and transmission power consumption in wireless image sensor networks by L. Ferrigno, S. Marano, V. Paciello, and A. Pietrosanto, aims at finding the most suitable compression method that provides the best compromise between energy consumption and the quality of the obtained image.…”