PRECISE: Personal Real-time Exposure using Cell-phone Integrated portable Sensors

Real time data for DelhiMigration and Pediatric AsthmaCellphone Apps to track location & time
Most Recent Levels at
>0.5µm (#/ft3)
VOC (ppm)NO2 (ppm)CH4 (ppm)CO2 (ppm)CO (ppm)NH3 (ppm)O3 (ppb)
2017-01-2914:12:593,092.00.3 0 1,336.400.02117.623.149.583
PRECISE Summary: One-quarter of the disease/disability burden can be attributed to environmental conditions (WHO1). While we have made great strides in characterizing personalized genotypes and phenotypes, we lack the ability to monitor personal environmental exposure. The mission of the University of Miami PRECISE (Personal Real-time Environmental Exposure using Cellphone Integrated SEnosors) is provide patients, researchers and healthcare professionals and providers with the mixture of pollutants, including multiple gaseous, particulate and organic pollutants, and their associated personalized or individual specific risks in real time. PRECISE includes an onboard (microcontroller), multiple optical sensors that record dust, CO, CO2, temperature, relative humidity, WiFi and storage card (Figure 1). It uploads data to a server through smartphones or WiFi in real time. The cost of the instrument about $550 (see real-time streaming of data from PRECISE deployed at The University of Miami RSMAS Campus). PRECISE can also be mounted inside home, on a car and can be carried by study participants, and it offers an unprecedented opportunity to quantify personal exposure to the mixture of air pollution in real time, and monitoring and management of acute effects of air pollution.

UM team is also developing a real-time prediction of fine particulate (PM2.5) by integrating high-resolution satellite data and optimal interpolation techniques, i.e. local-time space Kriging UM team has developed2. This system allows a user in the US and Indian subcontinent to retrieve historical concentrations of PM2.5 around a given location, and 24h prediction. Click here to browse data for Cleveland, OH3

1. WHO, 2006. Preventing disease through healthy environments - towards an estimate of the environmental burden of disease, World Health Organization: Geneva, Switzerland.
2. Liang, D. and N. Kumar, 2013. Time-space Kriging to address the spatiotemporal misalignment in the large datasets. Atmospheric Environment, 72:60-69 (R-Library
3. Kumar, N., D. Liang, A. Comellas, A.D. Chu and A. Thad, 2013. Satellite based PM concentrations and application to COPD in Cleveland. Journal of Exposure Science and Environmental, 23: 637-646. 2013. DOI:10.1038/jes.2013.52.

For any further information contact the University of Miami PRECISE TEAM