FEEDVIEW- A Cross-Platform Machine Learning Analytic App

Abstract

Abstract: Machine learning is a field of study that looks at using computational algorithms to turn empirical data into usable models. The machine learning field grew out of traditional statistics and artificial intelligences communities. thus, it's very important to assay this data in order to root some useful information and to develop an algorithm based on this analysis. We developed a feedback oriented multi-platform application to gather data from a mobile device and it's designed to create a survey for road transport and cars safety. It's a simple way to give a feedback or report for the concern department. Car companies will no longer have to wait for their car’s owner to create a complaint, with this app dealer or service team can directly contact the owner of the car for the issue with the resolution they may be facing. Road development department no longer need to do physical surveys with the data collected from multiple user’s they can directly take required actions. The smartphones have multiple assembled-in sensors each having a specific function which helps the device perform efficiently. To collect data our experiments will use the smartphone accelerometer and gyroscope. These sensors can potentially be used to gather required data. Keywords: Component, Machine Learning, Algorithm, Sensors, Network