Wireless line sensor network for distributed visual surveillance

Abstract

Wireless sensor networks (WSNs) play a crucial role in visual surveillance for automatic object detection, such as real-time traffic monitoring, vehicle parking control, intrusion detection, and so on. These online surveillance applications require efficient computation and distribution of complex image data over the wireless camera network with high reliability and detection rate in real time. Traditionally, such applications make use of camera modules capturing a flow of two dimensional images through time. The resulting huge amount of image data impose severe requirements on the resource constrained WSN nodes which need to store, process and deliver the image data or results within a certain deadline. In this paper we present a WSN framework based on line sensor architecture capable of capturing a continuous stream of temporal one dimensional image (line image). The associated one dimensional image processing algorithms are able to achieve significantly faster processing results with much less storage and bandwidth requirement while conserving the node energy. Moreover, the different operating modes offered by the proposed WSN framework provide the end user with different tradeoff in terms of node computation versus communication bandwidth efficiency. Our framework is illustrated through a testbed using IEEE 802.15.4 communication stack and a real-time operating system along with one dimensional image processing. The proposed line sensor based WSN architecture can also be a desirable solution to broader multimedia based WSN systems.

BandEst: Measurement-Based Available Bandwidth Estimation and Flow Admission Control Algorithm for Ad Hoc IEEE 802.15.4-Based Wireless Multimedia Networks

“…Beyond four flows there are strong chances that the networks will become congested; hence all the schemes will reject new flows). The throughput of each connection is randomly distributed in the range [2,22] kbps. Nodes randomly select a frame size between 80 and 127 bytes.…”

Traffic related observations by line sensing techniques

“…The line sensor [3] extracts a line from the two dimensional image retrieved by the camera module. This is equivalent to focusing a sampling line (L) in the field of view (P).…”

Energy optimization in wireless sensor networks using a hybrid K-means PSO clustering algorithm

“…WSNs have found many applications in industry, science, health care, transportation, civil infrastructure, and security. They were used in diverse applications including habitat and environmental monitoring [1], visual surveillance for automatic object detection such as real-time traffic monitoring and vehicle parking control [2], intrusion detection [3], and noise pollution monitoring [4]. WSNs suffer many challenges.…”