A comfort measuring system for public transportation systems using participatory phone sensing
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A Comfort Measuring System for Public Transportation Systems Using Participatory Phone Sensing . Cheng-Yu Lin 1 , Ling-Jyh Chen 1 , Ying-Yu Chen 1 , and Wang-Chien Lee 2 1 Academia Sinica, Taiwan 2 The Pennsylvania State University at University Park, USA. What are people doing on the bus?.

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A comfort measuring system for public transportation systems using participatory phone sensing l.jpg
A Comfort Measuring System for Public Transportation Systems Using Participatory Phone Sensing

Cheng-Yu Lin1, Ling-Jyh Chen1, Ying-Yu Chen1, and Wang-Chien Lee2

1Academia Sinica, Taiwan

2The Pennsylvania State University at University Park, USA

What are people doing on the bus l.jpg
What are people doing on the bus? Using Participatory Phone Sensing

Comfort does matter!!

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How to measure it? Using Participatory Phone Sensing

Professional Instruments


Problems: Cost, Timeliness, and Scalability

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Participatory Using Participatory Phone Sensing PhoneSensing

  • A new sensing paradigm to exploit the sensing capabilities of modern smart phones to gather, analyze, and share local knowledge of our surroundings(e.g.,CenseMe, SoundSense, Nericell)

  • It does not rely on dedicated sensing infrastructures and the top-down model of data collection.

  • It is more penetrative, and encourages participation at personal, social, and urban levels.

Question: how about let’s combine the participatory phone sensing and top-down data collection model?

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Comfort Using Participatory Phone Sensing MeasurementSystem

  • Goal: to evaluate the comfort level of public transportation systems


Public Transportation Systems

Sensing data

(e.g. locations, acceleration, and time)

Authorized data

(e.g. bus trajectories and vehicle properties)

Data Mashup and Statistics

Scoring and ranking results

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Our Contributions Using Participatory Phone Sensing

  • We propose the Comfort Measurement Systemthat exploits participatory phone sensing (bottom-up model) and the authorized data (top-down model).

  • We prototype a CMS, called TPE-CMS, to evaluate the public bus transportation service in Taipei City.

  • We conduct a 70-day experience to reveal the insights of the Taipei e-bus system.

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Phone Sensing Using Participatory Phone Sensing

  • Exploit the GPS and G-sensor (3-axis accelerometer) of modern smart phones

  • Calculate comfort index by following ISO 2631

Weighted Average

Acceleration Level



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Authorized Data Using Participatory Phone Sensing

  • No need to reinvent the wheel!

  • We take advantage of existing real-time bus tracking systems, which are available in many major cities world-wide (e.g., Boston, Cambridge, Seattle, and Taipei).

  • It contains the bus trajectory, route number, operating agency, and the other useful data.

  • This may be the most challenge, because you have to talk to the authority 

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Data Mashup Using Participatory Phone Sensing

Bus Trajectory



User Trajectory

Di= average ( , )









We suppose the user is on the b-th bus, s.t. b = arg Min Di







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Implementation Using Participatory Phone Sensing

4,028 buses, 287 routes, 15 agencies, and 1 sample per minute



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Experiments Using Participatory Phone Sensing

  • Period: 2010/03/15 – 2010/07/22

  • 15 volunteers

    • Collect trajectory and vibration traces of Taipei buses using Android phones

    • Keep a memo of the ground truth (i.e., the agency, route, and license number of their bus rides)

  • 425 trajectories collected, involving 12 agencies and 3 types buses

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Results(1/3) - Using Participatory Phone Sensing Trajectory Matching Results

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Results(2/3) - Using Participatory Phone Sensing The Statistics based on Buses Types

  • Light buses are uncomfortable.

  • No significant difference between the standard buses and the low-floor ones.

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Results(3/3) - Using Participatory Phone Sensing The Statistics based on Buses Agencies

  • The most comfortable and uncomfortable agencies are exactly the same as the ones reported in the survey made by Taipei Department of Transportation.

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Conclusions Using Participatory Phone Sensing

  • We present a Comfort Measuring System for public transportation systems, and prototype the system in Taipei city.

  • The CMS system can be deployed in any cities, as long as there are volunteering participants and there are authorized transportation data available.

  • Work on analyzing other factors that affect comfort levels is ongoing (e.g., road conditions, drivers’ behavior, and traffic congestion).

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http:// Using Participatory Phone Sensing VProbe.org/


Thanks for Your Attention!