A smartphone and BLE beacons are being used to collect location co-ordinates(x,y) and RSSI values for the dataset. In addition, the accuracy of positioning is determined by using Neural Network algorithms and boosting models to train the dataset. Using performance metrics such as Euclidean distance, MAE and RMSE to compare results and select the best model.
Comparison experiment between Neural networks and Boosting Regression Models using performance metrics such as RMSE, MAE and Euclidean distance error. Though Neural networks performed well in RMSE and MAE with least error, but Ada boosting stands out with least error in Euclidean distance error..