Analysis and prediction of patterns in automobile behavior

1. Analysis and prediction of patterns in automobile behavior As part of Capstone project, CSE651 Emerging Applications and Platforms By, Mathews Peter CB.EN.P2.ATS12034

2. Abstract Motivation The National Crime Records Bureau (NCRB) report reveals that every year, more than 135,000 traffic collision-related deaths occur in India. What am I aiming to achieve? Collect acceleration information, GPS location, vehicle make details and time information from automobiles. If there is sudden acceleration or deceleration of vehicles at a particular place, then that place is more prone to accidents. I try to find such patterns in the collected data. Upon identifying such a location, an alert may be provided to vehicles approaching that location. I aim to reduce the number of accidents by alerting the vehicles upon reaching a accident prone place.

3. Concept Diagram GPS locations identified as hot spot for accidents Predictive alert to vehicles as they approach the hotpot

4. How? How am I planning to achieve the aim? Arduino Uno can be connected to GPS for location, accelerometer for acceleration details, GPRS for sending the information to cloud. The stored data includes (GPS location, acceleration) along with other optional details like velocity, time, vehicle model etc. Filter out the data based on the below categories <23kmph Using k-means algorithm in R, find patterns in acceleration. Filter out the accelerations which are >5g. If there are any GPS locations more frequently present in the clusters, then that is a hot spot. This location is saved in cloud. As and when location information is received from vehicles, check if the location is nearby any hotspot by a few hundreds of meters. In that case, alert the vehicle.

5. What is a collision? Any acceleration above 5g happening above 23kmph resulting is reduction of speed to below 5kmph is an accident. Reference : A treatise on crash sensing for automotive air bag systems by Ching-Yao Chan. Providing accident detection in vehicular networks through OBD-II devices and Android-based smartphones by Jorge Zaldivar, Carlos T. Calafate, Juan Carlos Cano

6. ADXL345 accelerometer This device can be connected to Arduino Uno which provides acceleration details in 3 dimensions. Communication may be based on I2C or SPI protocol.

7. Parallax PMB-688 GPS receiver This device can be connected to Arduino Uno which provides GPS location information.

8. Cloud connectivity and storage Arduino based GPRS module is used to transfer the collected data to cloud. Google Appengine can be used for demonstration purposes.

9. Big data analysis The stored data in cloud is imported to a big data analysis tool, like R. Then the program tries to identify patterns of high acceleration and deceleration. Such patterns may provide a common GPS location. Such identified locations are flagged as hotspots. Hotspot information is sent back to the cloud for storage.

10. Predictive analysis Whenever a vehicle is near a hotspot by a few hundred meters, the cloud identifies that it is nearing a hotspot. An alert can be issued to the vehicle through GPS receiver installed in the vehicle.

11. Thank you