| 
  • If you are citizen of an European Union member nation, you may not use this service unless you are at least 16 years old.

  • You already know Dokkio is an AI-powered assistant to organize & manage your digital files & messages. Very soon, Dokkio will support Outlook as well as One Drive. Check it out today!

View
 

FrontPage

Page history last edited by Ricardo Piedrahita 10 years, 7 months ago

 

Welcome to MAQS (Mobile Air Quality Sensing System)    

 


 


 

Project Overview

Technology and User Resources

Team

Deployment of MAQS

Publications 

Support

Forum


 

Overview

 

          Our team is developing a Mobile Air Quality Sensing system, MAQS for short, that allows individuals to continuously and inexpensively measure the air quality they are exposed to, as well as giving them a framework to understand what the measurements indicate, and a place to discuss and explore their finding with fellow users.  The MAQS system consists of wearable personal monitors, M-Pods, an Android-based mobile phone app (MAQS App) , and an online social network (MAQS Network).  The M-Pods send readings over Bluetooth to the user's smart phone running the MAQS app.  The app then allows the user to view his or her personal air quality measurements in real time, offers some simple analysis tools, and uploads the data to a server whenever the smart phone is connected to a WiFi network.  The server's database can then be accessed via a web interface, which takes the form of an online social network, so a user can query measurement data and communicate with other users. 

 

Importance of the Project

 

          New ways of assessing air quality are very important as the problem of air pollution continues to grow in many places in the developed and developing world.  In the United States alone, poor air quality is responsible for approximately 50,000 premature deaths a year and $150 billion in medical costs (as determined by the National Oceanic and Atmospheric Administration, http://www.noaawatch.gov/themes/air_quality.php). 

     Precise air quality information is difficult to ascertain on an individual level; there are many different pollutants posing different threats, and these pollutants vary by location and time.  Since monitoring equipment is expensive,  measurements of air pollutants are taken at relatively few locations, and while this is important, more individualized information is also necessary.  This is particularly true of indoor air quality (IAQ), considering so much time is spent indoors and the factors that affect IAQ vary from building to building.  Through the use of new technologies, our team hopes to address these issues. 

 

              

Photo Credits: 1 2 3 4

 

Project Goals

 

          The projects aims to develop cost-effective, reliable air quality measurement devices and a network that allows for data collection and analysis, as well as, encouraging social interaction to discuss data and explore ways of improving air quality and protecting the environment.  All of the components will be designed for ease of use and comprehensibility for users both within the scientific community and outside of it.  Together these technologies will facilitate a large-scale environmental social study, which will provide detailed data that might allow for correlations between the temporal, spatial and behavioral relations of pollutants to be examined.  This information would benefit both scientific researchers and the users of the technology, possibly even raising awareness regarding our worsening air quality and prompting action to protect it.  

 

              

                               M-Pod and MAQS Mobile App                                                                    Project Overview

 

 

 

The MAQS project will monitor an individual's air quality throughout their day both indoors and outdoors.

 

return to top

 

Resources

 

An Explanation of the Technology

Getting Started with the MAQS System (User Info)

Interpreting MAQS Data

          Indoor Air Quality

          General Pollutant Information

FAQs

 

Send a ticket if you are having a problem with any part of the MAQS system

 

Team


 

Li Shang (project PI)

Qin Lv

Mike Hannigan

Rob Dick

Kun Li

Yifei Jiang

Xin Pan

Lei Tian

Ricardo Piedrahita

Berkeley Hippel

Xiang Yun

Lan Bai

Ashley Collier

return to top

 

Deployment of MAQS

 

Rural Ghana (in collaboration with NCAR), Winter 2011

CU-Boulder and University of Michigan Engineering Students in our team, Spring 2011

Dine Environmental Institute Science Pathway Program Interns, Dine College, Summer 2011

Dine Environmental Institute Science Pathway Program Interns, Dine College, January 2012

Dine Environmental Institute Science Pathway Program Interns, Dine College, Summer 2012

 

Follow this link to learn about the Project Status

 

Publications

 

 

Journals: 

 

1. Y. Jiang, K. Li, R. Piedrahita, X. Yun, L. Tian, O. M. Mansata, Q. Lv,R. P. Dick, M. Hannigan, L. Shang (2013). User-CentricIndoor Air Quality Monitoring on Mobile Devices. AI Magazine. 34 (2), 11. 

 

Status = PUBLISHED; Link: pdf

 

2. Y. Jiang, D. Li, Q. Lv (2013). Thinking Fast and Slow: An Approach toEnergy-Efficient Human Activity Recognition on MobileDevices. AI Magazine. 34 (2), 48.

 

Status = PUBLISHED; Link: pdf

 

Thesis/Dissertations: 

 

3. Yifei Jiang. Crowdsourcing Based Room Localization on Smartphones.(2013). Ph.D. Thesis, University of Colorado Boulder.

 

Status = PUBLISHED

 

Conference Papers and Presentations

 

4. R. Piedrahita, Y. Jiang, X. Pan, K. Li, X. Yun, N. Masson, A. Collier,M. Hannigan, R. Dick, Q. Lv, L. Shang. Validation of low-cost mobile air quality monitors and initial personal exposure results of carbon monoxide, total volatile organic compounds,and carbon dioxide. in Proc. Environmental Health. 2013. Boston, MA.

 

Status = PUBLISHED;  Link: pdf  

 

5. Y. Xiang, R. Piedrahita, R. Dick, M. Hannigan, Q. Lv, and L. Shang.(2013). A hybrid sensor system for indoor air qualitymonitoring. DCOSS 2013: in Proc. the 9th IEEE International Conference on Distributed Computing in SensorSystems. May 2013, pp. 96–104. Cambridge, MA. 

 

Status = PUBLISHED;  Link: pdf 

 

6. Y. Jiang, Y. Xiang, X. Pan, K. Li, Q. Lv, R. P. Dick, L. Shang, and M.Hannigan. Hallway based Automatic IndoorFloorplan Construction using Room Fingerprints. UbiComp 2013: in Proc. the 2013 ACM International JointConference on Pervasive and Ubiquitous Computing. Zurich, Switzerland. 

 

Status = PUBLISHED;  Link: pdf

 

7. Y. Jiang, X. Pan, K. Li, Q. Lv, R. Dick, M. Hannigan, L. Shang. ARIEL: Automatic Wi-Fi based Room Fingerprinting for Indoor Localization. in Proc. the 14th intl. conference on Ubiquitous computing. Sep. 2012.

 

Status = PUBLISHED;  Link:pdf

 

8. Y. Xiang, L. S. Bai, R. Piedrahita, R. P. Dick, Q. Lv,M. P. Hannigan, and L. Shang, “Collaborative calibration and sensor placement for mobile sensor networks,” in Proc. Int. Conf.  Information Processing in Sensor NetworksApr. 2012, pp. 73–84.  

 

Status = PUBLISHED;  Link: pdf

 

9. L. Bai, R. P. Dick, P. Chou, and P. A. Dinda, “Automated construction of fast and accurate system-level models for wireless sensor networks,” in Proc.  Design, Automation & Test in EuropeConf., Mar. 2011, pp. 1083–1088.    

 

Status = PUBLISHED;  Link: pdf

 

10. L. Bai, R. P. Dick, P. A. Dinda, and P. Chou, “Simplified programming of faulty sensor networks via code transformation and run-timeinterval computation,” in Proc. Design, Automation &Test inEurope Conf., Mar. 2011, pp.  88–93. 

 

Status = PUBLISHED;  Link: pdf

 

11. Y. Jiang, K. Li, L. Tian, R. Piedrahita, X. Yun, O. Mansata, Q. Lv, R. P. Dick, M. Hannigan, and L. Shang, MAQS: A Personalized Mobile Sensing System for Indoor Air Quality Monitoring. In Ubicomp '11: in Proc. the 13th ACM international conference on Ubiquitous computing, 2011. ACM, New York, NY, USA.

 

Paper Summary: MAQS: A Mobile Sensing System for Indoor Air Quality

 

Status = PUBLISHED; Link: pdf

 

12. Y. Jiang, Du Li, G. Yang, Q. Lv, and Z. Liu, Deliberation for Intuition: A Framework for Energy-Efficient Trip Detection on Cellular Phones. in Proc. the 13th ACM international conference on Ubiquitous computing, 2011.

 

Status = PUBLISHED; Link: pdf

 

13. Michael Hannigan, Ricardo Piedrahita, Nicholas Masson, John Ortega, Yifei Jiang, Xiang Yun, Kun Li, Qin Lv, Robert Dick, Li Shang.  Personal Exposure Results for the M-Pod, a Portable Low-Cost Air Quality Monitor.  AAAR Conference.   Portland OR, Sept. 30th-Oct. 4th, 2013.

 

Status = Presented; Link: pdf

 

 

In Preparation

 

14. Ricardo Piedrahita, Yun Xiang, Nicholas Masson, John Ortega, Ashley Collier, Yifei Jiang, Li Kun, Robert Dick, Qin Lv, Michael Hannigan, Li Shang.  The next generation of low-cost personal air quality sensors for quantitative exposure monitoring.  2013.  Atmospheric Environment.

 

Status = IN PREPARATION 

 

 

15. Nicholas Masson, Ricardo Piedrahita, Xiang Yun, Michael Hannigan, Qin Lv, Robert Dick, Li Shang.  Quantification Methods for Metal-Oxide Semiconductor Gas Sensors. AAAR Conference.   Portland OR, Sept. 30th-Oct. 4th, 2013. 

 

Status = IN PREPARATION

 

 

 

 

Support

 

This work was supported by the NSF under awards CNS-0910995 and CNS-0910816.

 

return to top

Comments (0)

You don't have permission to comment on this page.