User-Centric Indoor Air Quality Monitoring on Mobile Devices


  • Yifei Jiang University of Colorado, Boulder
  • Kun Li University of Colorado, Boulder
  • Ricardo Piedrahita University of Colorado, Boulder
  • Xiang Yun University of Michigan
  • Lei Tian University of Colorado, Boulder
  • Omkar M. Mansata University of Michigan
  • Qin Lv University of Colorado, Boulder
  • Robert P. Dick University of Michigan
  • Michael Hannigan University of Colorado, Boulder
  • Li Shang University of Colorado, Boulder



Since people spend a majority of their time indoors, indoor air quality (IAQ) can have a significant impact on human health, safety, productivity, and comfort. Due to the diversity and dynamics of people's indoor activities, it is important to monitor IAQ for each individual. Most existing air quality sensing systems are stationary or focus on outdoor air quality. In contrast, we propose MAQS, a user-centric mobile sensing system for IAQ monitoring. MAQS users carry portable, indoor location tracking and IAQ sensing devices that provide personalized IAQ information in real time. To improve accuracy and energy efficiency, MAQS incorporates three novel techniques: (1) an accurate temporal n-gram augmented Bayesian room localization method that requires few Wi-Fi fingerprints; (2) an air exchange rate based IAQ sensing method, which measures general IAQ using only CO$_2$ sensors; and (3) a zone-based proximity detection method for collaborative sensing, which saves energy and enables data sharing among users. MAQS has been deployed and evaluated via a real-world user study. This evaluation demonstrates that MAQS supports accurate personalized IAQ monitoring and quantitative analysis with high energy efficiency. We also found that study participants frequently experienced poor IAQ.

Author Biography

Kun Li, University of Colorado, Boulder

Department of Electrical, Computer, and Energy Engineering




How to Cite

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