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  Smart Transportation System using IOT and Computer Vision  
  Authors : Vidushi Bhadola; 2 Dr.Neha Agrawal
  Cite as:

 

Logistics is a process which ensures efficient and cost-effective flow of goods and. In India, the logistics sector is highly unorganized due to a lack of proper infrastructure and inclusion of technology which results in a lack of seamless movement of goods and people from one place to another. Also, with a surge in the number of taxis and trucks in the country due to increase in demand of the logistics sector, the accidents related to drunk driving and late alert of accident to the concerned authorities have drastically increased. In India, more than 60% of annual accidents are caused due to the menace of driving under the influence of alcohol. It is practically untenable for owners of these cab and trucks to keep an account of the activities of drivers and any accidents of these vehicles. The purpose of this research is outlining some of the key challenges faced by the logistics industry and providing a cost-effective and feasible solution for the same. This paper provides a solution called as SMART TRANSPORTATION SYSTEM and makes use of sensors and the IOT technology to track the activities of the drivers and notify the owners to take the right action and uses Computer Vision technology to detect a drowsy driver and alert him.

 

Published In : IJCSN Journal Volume 8, Issue 3

Date of Publication : June 2019

Pages : 270-275

Figures :13

Tables : 01

 

Vidushi Bhadola : IT, B. Tech Student, Maharaja Agrasen Institute Of Technology, Rohini New Delhi, Delhi, India.

Dr. Neha Agrawal : IT, Assistant Professor, Maharaja Agrasen Institute Of Technology, Rohini New Delhi, Delhi, India.

 

Accident alert, Drunk Driver, IOT, Drowsy Driver, Computer Vision, Arduino Uno, Shock Sensor, MQ-3 Sensor

The system is an accident alert system along with a drunk and drowsy driver detection system that detects the intoxicated level of the drunk driver with high level of certainty and detects any accident to the car and generates a corresponding alert. The system is also capable of detecting a drowsy and sleepy driver using the latest Computer Vision technology. The system detects drunk driver situation initially or during driving and activates the alternate mechanisms for local persons i.e. turning off the ignition if car is not moving along with remote indication to the authorized persons i.e. generating alert to the required authorities. The main aim of the project is to decrease the chances of loss of lives in accident, occurring due to the intoxicated or drowsy state of driver and late alert to the required authorities, hence improving public safety and also making a better system for the logistics companies to track their drivers. Based upon the latest Computer Vision technology and semiconductor gas sensing as well as a sensitive shock detector, the system is cost-effective and reliable. The development cost of the device would be less than INR 3000.

 

[1] Pankaj Chandra; Nimit Jain, "The Logistics Sector in India : Overview and Challenges" pp. 8-11. [2] Phalak; Kowekar; & Joshi. 2015. Smartphone and Sensor Based Drunk Driving Prevention System. International Journal For Research In Emerging Science And Technology, Vol.2, Issue 9. [3] Ramanath; Sudharsan & Udhayara. 2010. Drunken Driving and Rash Driving Prevention System International Conference on Mechanical and Electrical Technology-ICMET [4] Sivakumar; & R.Krishnaraj. 2012. Road Traffic Accidents (RTAS) Due To Drunken Driving In India challenges In Prevention. International Journal of Research in Management & Technology (IJRMT), Vol. 2, No. 4. [5] T.Venkat; NarayanaRao; &Karttik Reddy Yellu. 2017. Preventing Drunk Driving Accidents using IoT". Available at www.ijcset.net.| Vol. 8. No. 3. [6] Vijay; Saritha; Priyadharshini; Deepeka; &Laxmi. 2011. Drunken Drive Protection System. International Journal of Scientific & Engineering Research. Vol. 2, Issue 12. [7] Impaired Driving: Available at https://www.cdc.gov/motorvehiclesafety/impaired_drivi ng/impaired-drv_factsheet.html [8] Pranjali Ingale Patil; Priyanka Barhate; Bhagyashri Nemade; &Vijay D. Chaudhari. 2017. Alcohol Detection System in Vehicle Using Arduino. International Research Journal of Engineering and Technology (IRJET). Vol. 04 Issue: 06. Available at https://www.irjet.net/archives/V4/i6/IRJET-V4I651.pdf [9] Kiran Sawant, Imran Bhole, Prashant Kokane, Piraji Doiphode, Prof. Yogesh Thorat, "Accident Alert and Vehicle Tracking System", International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 5, May 2016 [10] Tereza Soukupova and Jan Cech, "Real-Time Eye Blink Detection using Facial Landmarks", 21st Computer Vision Winter Workshop Luka Cehovin, Rok Mandeljc, Vitomir ? Struc (eds.), Rimske Toplice, Slovenia, February 3-5, 2016 [11] Jaeik Jo Sung Joo Lee, Ho Gi Jung, Ryoung Park, Jaihie Kim, "vision based method for detecting driver drowsiness and distraction monitoring system", Optical Engineering, vol. 50, no. 12, December 2011. [12] Vidushi Bhadola, Neha Agrawal, "Smart Transportation System using IOT", IJIRT, vol.5, issue 6 , November 2018