Big Data Architecture for Intelligent Transport Systems Optimization
Mounica.B,1 Lavanya.K2
1Mounica .B, School of Computer Science and Engineering(SCOPE) ,VIT University, Vellore, India.
2Dr. K. Lavanya, School of Computer Science and Engineering(SCOPE) , VIT University, Vellore ,India.
Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1281-1286| Volume-8 Issue-9, July 2019 | Retrieval Number: I8119078919/19©BEIESP | DOI: 10.35940/ijitee.I8119.078919
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Day by day as the volume of data is being generated massively, storing of data and processing of data becomes a ever growing challenge in intelligent transport system (ITS). In intelligent transport system there are different areas to concentrate like smart parking systems, dynamic toll charging, smart traffic management etc. This paper is mainly focused on big data architecture for intelligent transport system for dynamic toll charging, traffic management and traffic analysis related data collection from various sources. The data collected from various sources can be in the form of structured data, semi structured data and unstructured data. Because of verity of data collected, this paper gives an idea about which data model is appropriate depending on data collected for transportation system.
Keywords: Big data architecture, Data model, ETL tool, Hadoop, Intelligent transport system, Spark.
Scope of the Article: Computer Architecture and VLSI