Research Fellow/Professor  |  Chen, Ling-Jyh  
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Software Name:AirBox: An Participatory Sensing System for PM2.5 Monitoring
Inventors:Ling-Jyh Chen

We propose a participatory urban sensing framework for PM2.5 particle monitoring. To develop it, we conducted a comprehensive set of evaluations to compare the accuracy of commercial off-the-shelf (COTS) low-cost particle sensors with two professional devices. Based on the evaluation results, we identified feasible sensors for PM2.5 sensing applications. Then, in collaboration with maker communities, industry partners, and the Taipei City Government, we developed various types of PM2.5 monitoring devices for different communities. By July 2019, we had deployed more than 10,000 devices in Taiwan and 47 other countries.

In addition, we have been working on the provision of a data service, data visualization, and data analysis. All the measurement data are released in real time with the open data approach. We have also developed a number of data visualization tools to allow more advanced analysis of PM2.5 monitoring data. Finally, we conducted spatio-temporal data analysis to identify potential PM2.5 emission sources. The results can be extended to facilitate on-demand responses and government policymaking in the future.

The contribution of this system is three-fold:

  1. We constructed a successful eco-system in collaboration with academic institutions, industry partners, govern- ment authorities, and citizen groups; and developed a participatory urban sensing system.
  2. The proposed framework is based on an open architecture, open hardware and open-source codes; and the collected data is released in an open data fashion in real time. The system is highly scalable because it allows people to develop their own devices and contribute tothe system freely.
  3. Through extensive data analysis, our framework can provide micro-scale air quality information, thereby en- abling on-demand responses and influencing government policymaking in the long term.

Project Website:

Data Visualization Tools:

  • Voronoi Diagram:
  • IDW Diagram:
  • Device Dashboard:
Software Name:VProbe
Inventors:Ling-Jyh Chen (PI) and Cheng-Yu Lin (RA)

VProbe exploits sensing technologies of modern smart phones to evaluate your daily driving experience. Using web-based graphical interface, you are now enabled to re-examine your driving behavior, figure out where you drive most uncomfortable, and improve your driving skill. Moreover, by sharing your driving experience and social each other on Facebook, you can compare your driving skills with your friends, and find out the best drivers among your friends, your family, and your school.

The Android-based implementation of this appication has been released on our website on 2010/02/26 and on Android Market on 2010/10/21. The iOS version of VProbe has been released on Apple Application Store on 2011/04/11.

VProbe has been used in the TPE-CMS project ( to measure the comfort level of the Taipei e-Bus system since 2010/03/12. TPE-CMS exploits the GPS and 3-axis accelerometerfunctions of modern smart phones to measure the comfort level of bus rides. Then, it mashes up the sensed data with the authorized data of the public transportation systems, and provides a detailed comfort statistics as a value added service. By far, the system has supported the bus systems in Taipei city and New Taipei city in Taiwan. Moreover, the system has attracted more than 350 users worldwide, with a contribution of more than 20,000 valid trajectories, and the number is still increasing now.

The succeeding application of VProbe, called Bus+, has been launched on Google Play (the Android App Market) on October 5, 2011, and available on Apple App Store on April 27, 2012. Bus+ won the First Prize in Taiwan App Star Contest (Taipei Open Data Application Innovation Track). It has reached more than 2,500 downloads and currently has 316 active installs (according to the official statistics of Google Play, accessed on 2012/05/20).

Project website:

  • VProbe:
  • TPE-CMS:
  • Bus+ video on YouTube: