Moment-based Feature Extraction in SAR Images for Ground Vehicle Recognition

Wireless sensor networks (WSNs) consist of a large number of sensor nodes. The sensors are tiny devices, which are easy to manufacture, low cost and very power efficient. The major objective of this thesis is to use WSNs in intelligent decision making based on the collected data. Intelligent decision making has important application especially in autonomous systems used in homeland security, health care improvement, wildlife monitoring, environmental surveillance, climate research and natural disaster – crises management. The main advantage and growing significance of intelligent decision making is the elimination of human factor which makes it reliable, conformable, adoptable and a major player in energy management of remotely located autonomous systems. The focus of this thesis is to design a system to make an intelligent decision based on the five levels of sensitivities introduced by Uysal et al [2]. In designing such a system, we will consider some parameters like power consumption, total cost and efficiency of the system in comparison to the PLCs developed by companies such as Siemens and Mitsubishi. For software implementation among the available techniques, we have chosen one that has a faster processing method in comparison to computational methods that are widely used in the processors. We introduce Fuzzy logic system, which is a very powerful method, commonly used in control systems, and can be easily simulated in MATLAB Toolbox. Keywords: Intelligent decision making, wireless sensor network, fuzzy logic, security system, PLC component