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IJSTR >> Volume 5 - Issue 1, January 2016 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Smartphone Based Approach For Monitoring Inefficient And Unsafe Driving Behavior And Recognizing Drink And Drive Conditions.

[Full Text]

 

AUTHOR(S)

G. V. Mane, Saurabh Dhabe, Utkarsh Nadgouda, Akshay Sonawane, Vipul Jadhav

 

KEYWORDS

Smartphone, On Board Dignosis II, Sensor, Real Time Systems, Inefficient and Unsafe Driving, Drunk Drive Detection.

 

ABSTRACT

Many automobile drivers having knowledge of the driving behaviours and habits that can lead to inefficient and unsafe driving. However, it is often the case that these same drivers unknowingly manifest these inefficient and unsafe driving behaviours in their everyday driving activity. The proposed system proposes a practical and economical way to capture, measure, and alert drives of inefficient and unsafe driving as well as highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The upcoming solution consists of a mobile application, running on a modern smartphone device, paired with a compatible OBDII (On-board diagnostics II) reader.

 

REFERENCES

[1] Ashutosh Kumar Choudhary, Piyush.K.Ingole, Smart phone based approach to monitor driving behavior and sharing of statistic, Department of Computer Science and Engineering G. H. Raisoni College of Engineering, Nagpur, 2014.

[2] J. Lee, J. Li, L. Liu and C. Chen, A Novel Driving Pattern Recognition and Status Monitoring System, in First pacific rim symposium, PSIVT 2006, pp. 504-512, December 2013.

[3] Michele Ruta, Floriano Scioscia, Filippo Gramegna, Giuseppe Loseto, and Eugenio Di Sciascio, Knowledge-based Real-Time Car Monitoring and Driving Assistance, Politecnico di Bari, via Re David 200 I-70125 Bari, Italy, 2012.

[4] Adnan K. Shaout and Adam E. Bodenmiller, A Mobile Application for Monitoring Inefficient and Unsafe Driving Behaviour, The Electrical and Computer Engineering Department The University of Michigan-Dearborn Dearborn, Michigan 48128, 2011.

[5] Jiangpeng Dai, Jin Teng, Xiaole Bai, Zhaohui Shen, Dong Xuan, Mobile Phone Based Drunk Driving Detection, School of Computer Sci. Engr. Southeast University, Nanjing, Jiangsu, China, Dept. of Computer Sci. and Engr. The Ohio State University Columbus, Ohio, USA, 2010.