Analysis and Visualization Model for a GPS Dataset of Moving Vehicle

摘要

Smart transportation solution for developing smart city, needs continuous collection and analysis of GPS data. Smart traffic solution needs collections of data for movement of vehicles. This research paper suggests a model for studying GPS data by drawing a comparison between different data analysis techniques and visualizing a model for GPS dataset of a moving vehicle. Different clustering technologies have been used to identify corresponding accuracies, i.e. of K-Means, hierarchical and DBSCAN clustering algorithm. Various data attributes have been used to cluster the longitude and latitude of the current position of the vehicle along with the direction the vehicle is moving in. This research paper provides an insight to the usage of DBSCAN for better clustering model, better visualization and to implement it in future models. The dataset used is of a city in Ohio named as Cincinnati, located at 39 1031° N, 84.5120° W and is provided by the department of public services.