IoT Research Project

Touch-based prediction model for user behavior with mobile sensor data

Project breakdown

• Android mobile application for sensor data collection : accelerometer, gyroscope, magnetometer,proximity
• Sensor data updated based on sensor reading changed (high frequency update) and can be uploaded to firebase with the same frequency
• The sensor data is then exported and cleansed into cvs file in the dataSouce folder
• The data training code was running in google collab and tested svm and random forest classifier
• The concept of digital twins were implemented during the data training and testing process as it acts as a learning feedback feeding a boolean value back to the training model

Results

svm confusion matrix with and without digial twin

vs