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A method to determine a person's mode of transportation.

Details

Project TitleA method to determine a person's mode of transportation.
Track CodeUIC-2012-115
Short Description

Using GPS sensors, accelerometer sensors and transportation network data, this technology combines multiple common mobile phone sensors to effectively detect transportation mode. 


Abstract

Understanding a person's mode of transportation (bike, car, bus, train, walking) from sensor data is a very useful tool to assist people in travelling; it can also assist advertiser's in targeting their message. A person's mode of transportation denotes some characteristics of the mobile user's location. With knowledge of a traveler's transportation mode and location, targeted and customized advertisements may be sent to the traveler's device. For example, if the software identifies that the user is driving by car, the system may send her gas coupons or vehicle service specials.


UIC researchers have combined multiple common mobile phone sensors to derive new classification features that are effective for both indoor and outdoor transportation mode detection.


One very useful application of this technology is in cities with mass transit systems (buses and trains). In this application, the software combines GPS sensor, accelerometer sensor, and transportation network data-- consisting of real time location of buses, rail lines, and bus stop mapping. Using the transportation network data, the application is able to distinguish between motorized modes such as trains, buses, and cars with high accuracy. Furthermore, when they detect that a traveler is traveling by bus, they are able to identify on which particular bus the person is traveling.


APPLICATIONS

  • Can be used to determine a traveler’s mode of transport (bike, car, mass transit)
  • Allows for customized and targeted advertising

BENEFITS

  • Compatible with any mobile device fitted with GPS and accelerometer sensors
  • Does not require external sensor infrastructure

For more information, contact Mark Krivchenia.

 
TagsNone
 
Posted DateMar 17, 2016 10:51 AM

Researcher

Name
Bo Xu
Leon Stenneth
Ouri Wolfson
Philip Yu

Manager

Name
Mark Krivchenia
Sandra Thompson