HYBRID LOCALIZATION TECHNIQUE FOR INDOOR CHILD TRACKING USING WIRELESS SENSOR NETWORK

Child kidnapping causes a lot of concerns among People.
Wireless Sensor Network (WSN) could be used for child tracking as a kidnapping tool.
Localization is the main issue in tracking applications. There are many localization techniques available for WSN. Each technique Was designed a specific purpose
and environment. Accuracy is the most important parameter of any localization technique. However, the other parameters cannot be neglected. Improving accuracy
leads to decreasing the performance of the other parameters. localization techniques use complex mathematical formulas to improve the accuracy. This leads to
high complexity of the algorithm. Keeping complexity of the algorithm low is also important. It is define how 1ong it takes the technique to locate the tarset The problem
addrased in this thesis is increasing the accuracy without increasing the complexity of the Localization technique. The objectives of this thesis are a) to propose a hybrid
localization kdnique that has higher localization accuracy and lower algorithm complexcity fbr its real-time execution, and b) to analyze the localition accuracy and
algorithm complexity of hybrid technique of K-Nearest Neighbors (KNN) and Fuzzy
Logic Indoor localization System (FLIPS), FuzzY-KNN, through experiment, and
compare it to other localization techniques for WSN from the literature study.