Road Accident Data Analytics Using Map – Reduce Concept
R. Joshua Samuel Raj1, T. Sudarson Rama Perumal2, N. MuthuKumaran3

1R. Joshua Samuel Raj, Professor, Department of Information Science and Engineering, CMR Institute of Technology, Kundalahalli, Bengaluru.  
2T. Sudarson Rama Perumal, Assistant Professor, Department of CSE, Rajas Engineering College Vadakankullam, Tirunelveli.
3N. MuthuKumaran, Professor, Department of ECE, Francis Xavier Engineering College Tirunelveli.
Manuscript received on 26 August 2019. | Revised Manuscript received on 08 September 2019. | Manuscript published on 30 September 2019. | PP: 1032-1037 | Volume-8 Issue-11, September 2019. | Retrieval Number: I8927078919/2019©BEIESP | DOI: 10.35940/ijitee.I8927.0981119
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 (

Abstract: In recent years, the accidents on road have been increasing exponentially on yearly basis because of heavy traffic which has increased great concerns across the world. The enormous growing drift of motorization and the improvisation of the social and economic position of the people have influenced the annoying road safety scenarios with wounded and eternally disabled injuries. This paper has an extensive in-depth study through the accidents and its causes due to the reasons like weather Conditions, Age, Lighting, Vehicle Conditions, Road conditions etc. Data mining algorithms are applied to the provided dataset and factors which cause accidents. Utilization of this paper is to find out the factors which cause accidents and it can be given to the public so that the accidents can be reduced. This paper has established a linkage from the causes to the consequences with event classification of certain cases during the duration2009-2014. Keywords—
Keywords: Road accident, clustering, Data mining, association rule mining, and Map Reduce.
Scope of the Article: Data mining