In wireless sensor networks using soft computing techniques estimate of location

In Wıreless Sensor Networks Using Soft Computing Techniques Estimate of Location Requirements and developments of communication technologies are tending on wireless environment. So, methods of location on networks become a new field for researchers. Wireless Sensor Network is more different than other networks. The most significant specifications are; other wireless networks only have single side connection on data transferring/receiving but wireless sensor network has double side connection. Also wireless sensor network is claassified as Smart Network rather than other networks. Even these networks are capable of data tranferring/receiving and commenting. Early on wireless sensor network was used especially on military services. Additionally, because of decreasing fees on technological developments and sensors that was used for healthy, environment and habitat observing. Then, it is started to use for as Agriculture, Industry, Traffic, Education and it spreads almost all sectors. One of the Wireless Sensor Network's working area is location. Location estimation is inspected on two main subject. These subjects are outdoor and indoor. GPS is used on outdoor for location and it gives real results. However GPS systems don't give real results on indoor. So, real location on indoor is more important than outdoor. Also Range Based and Range Free Based methods will be used for indoor location. This thesis based on problem of finding location that unknown location sensor and it is made with using RSSI result. For solving this problem, worked on finding location with using Fuzzy Logic and Artificial Neural Networks. Our primary purpose is minimizing margin of error on mobile sensors in indoor when finding location (It is made with anchor sensors-their locations' are known). Two different applications are realized in this thesis. First of this applications is Fuzzy Logic Based Location with using RSSI and LQI results. The other one is location method the Artificial Neural Networks Based. Obtained results are compared with method of Centroid Localization. Key Words: Wireless Sensor Networks, Advantage of Wireless Sensor Network, Hardware of Sensor, Methods of Location on Wireless Sensor Network, Fuzzy Logic, Artificial Neural Network.