Vehicle Recognition Via Sensor Data From Smart Devices

Abstract

This study explored the activity of moving vehicle and public transportation, as a next stage of smart device use, and its evolution with data science. Smart devices have been enabled to help people carry out their daily activities. Some smart device operating systems have special apps to make it easy for users to record information about walking, running, jogging, and stepping through the Activity Recognition process, even recording physiological information. Advanced smart devices can now be used to record information about moving vehicles, as it has begun by enabling paid advertising on personal motor vehicles. However, with advancements in smart device technology, as analyzed and proposed by this paper, people will be able to utilize this technology with new data science methods to analyze far more information related to moving vehicles and public transportation. In this paper, we have proposed a method to recognize the vehicle that the subject is currently using by recorded accelerometer and gyroscope sensor data embedded in a smart device. In other words, we have implemented a machine learning model Artificial Neural Network to classify vehicles from the sensor data.