Geofencing on the Real-Time GPS Tracking System and Improving GPS Accuracy with Moving Average, Kalman Filter and Logistic Regression Analysis

People throughout history have wondered their position on the world. This led to the development of Global Navigation Satellite Systems (GNSS). The most widely used is the GPS (Global Positioning System) technology. Signals emitted from GPS satellites. Calculates your own location by detecting GPS receivers on earth. The GPS data obtained in this study was sent to a remote server via GSM and GPRS and turned into a real-time tracking system. The location of the GPS device can be monitored instantly by observing the application map screen from devices such as computer and phone. This monitored location has a certain delay considering the factors such as the arrival time of the GPS data to the device and the time the device connects to the internet. The system operates with a delay of 4 - 5 seconds. In addition, the Geofence field is used to alert the device when it moves away from a specified location. As the Geofence area, a predetermined polygon on the map can be used or the polygon area drawn during the application can be used as Geofence. On the application screen, an audible warning is given when leaving the Geofence area. GPS does not always show the exact correct position; it has a certain margin of error. Many factors affect this margin of error. This causes the application to give false alarms and operate with the wrong location. In order to reduce this error, the error rate was tried to be reduced by using Kalman filter, logistic regression analysis and moving average filter. Normally the error margin of up to 15 meters is considerably reduced by these filters.