An efficient fuzzy fusion-based framework for surveillance applications in Wireless Multimedia Sensor Networks

Abstract

, 86 pages Previous advances in Information Technologies and especially in Micro Electro-Mechanical Systems, have made the production and deployment of tiny, battery-powered nodes communicating over wireless links possible. Networks comprised of such nodes with sensing capability are called Wireless Sensor Networks. The early deployment aim was to use these nodes only in a passive way for indoor applications. These kinds of early nodes had the ability to sense scalar data such as temperature, humidity, pressure and location of surrounding objects. However, recently available sensor nodes have higher computation capability, higher storage space and better power solutions with respect to their predecessors. With these developments in addition to scalar data delivery, multimedia content has become the core focus. A wireless sensor network with multimedia capabilities is called Wireless Multimedia Sensor Network. There has always been a trade-off between accuracy and energy-efficiency in these new generation networks because of their resource-constrained nature. In this thesis we introduce a new approach to address this trade-off in Wireless Multimedia Sensor Networks. Although a number of previous studies have focused on various special topics in Wireless Multimedia Sensor Networks in detail, to the best of our knowledge, none presents a fuzzy multi-modal data fusion system, which is lightweight and provides a high accuracy ratio. Especially, a multi-modal data fuv sion system targeting surveillance applications make it inevitable to work within a multi-level hierarchical framework. In this thesis, our primary focus is on accuracy and efficiency by utilizing our framework. Along with the fuzzy fusion framework, a new fuzzy clustering algorithm, namely Multi-Objective Fuzzy Clustering Algorithm (MOFCA), is introduced and evaluated in detail as well.

Two novel protocols for optimizing energy consumption in heterogeneous wireless sensor networks using fuzzy logic for monitoring, diagnosis and target tracking

“…Consequently, a considerate amount of energy is wasted and the network lifetime ends prematurely. In this paper we used fuzzy logic approach which have recently used in [12,20] to handle uncertainties in cluster head radius estimation. In this fuzzy approach the CH election occurs by considering three fuzzy descriptors namely distance to BS, residual energy of each node and the density of the node with the aim of estimating the competition radius for tentative CHs.…”

“…In case the selected number is less than threshold of the tentative cluster head, that node will change its status into the tentative cluster head. Then, using three parameters, namely distance to the base station, density and remaining energy, these tentative cluster heads will measure and create their competition radius according to the fuzzy rules [12,20]. Given the fact that tentative cluster heads make use of the above-mentioned three parameters for measuring competition radius, it is obvious that the value of competition radius will change as these input parameters vary throughout the execution of the protocol; otherwise, the energies of the sensors will deplete quickly.…”

“…In case the communication channel of the receiver is free, data will be transmitted. For more details about fuzzy approach and its tables please refer to [12,20].…”

Reliable Multi-Object Tracking Model Using Deep Learning and Energy Efficient Wireless Multimedia Sensor Networks

“…Habitation and ecological monitoring denote a kind of WMSN applications which is advantageous to scientific communities and societies [7]. This technology enables the research people and biologists to thoroughly analyze the target region [45] by giving the local measurements, sampling, and in-depth information, which are usually hard and high cost to get.…”