The Public Transportation BigData Clustering

Abstract

An increase in the use of GPS modules and cell phones with location services has created a need for new ways of collecting and storing data. Considering a fairly large number of devices, data collected in such way in most cases take up a vast amount of space on servers while on the other hand, they represent a source of very useful information. A large number of companies use this method of data collection in order to create prediction models, reports and data analysis. As an object of observation, we use the database of a modern public transportation system which contains information about vehicle telemetry. In this paper, we will describe the application and result analysis of some well-known clustering algorithms in order to solve public transportation problems like traffic congestion, passenger transport, etc.