Measurement system of 3-D position using a ZigBee S2C radio module based on a neural network Available to Purchase

The positioning system is closely related to wireless sensor networks that use wireless technology as a medium to deliver communications to receivers, such as Bluetooth, Wifi, and Zigbee. This study aims to design the 3-dimensional positioning system with the concept of Wireless Sensor Network (WSN) and uses ZigBee as a communication protocol. Radio signal waves on ZigBee devices are processed into Received Signal Strength Indicator (RSSI) values and then processed by the artificial neural network (ANN) method to estimate mobile node coordinates. RSSI is used to estimate the distance of the mobile node to each anchor node. Backpropagation on artificial neural network method in MATLAB can train the data for calculating the estimated position between the anchor node and the mobile node to generate a value in the form of coordinates. Then, the normalization, denormalization, activation, weight, and bias components obtained from the ANN training results are used in the Arduino ANN test program. The area for testing is 4x4x3 m³ with anchor nodes located at coordinates (1; 3; 2), (1,5; 2,5; 1,5), (2; 3; 1,5), (2,5; 2; 1) and (3; 1; 1). The average error values for tests with 3 anchors in a row are 8.3%, 2.8%, 4.6%, 4.6%, and 8.4%.