SEVA-assisted analytics of spatialized sensor data
Data collection based on spatialized sensor networks
Air Quality Sensor Node (AQSN): A framework for assessing Indoor Air Quality data and its impact on human health of building occupants. Image courtesy of Ben Feagin / CASE
SEVA-assisted analytics of spatialized sensor data
Integrated Sensing
Currently the density and fidelity of environmental sensing networks needs to significantly improve in order to provide adequate information to responsively customize environmental conditions to the requirements of building occupants. Furthermore, the complexity of the system is not adequately represented by current data visualization techniques. The built ecologies of the future would greatly benefit from a real time data visualization platform that links the environmental conditions to the real time condition of occupants, with additional notation and semantic overlays. CEA is proposing a live testing unit the Built Environment Ecosystem Measurement unit (BEEM Unit) to evaluate multiple environmental conditions alongside human health indicators in order to establish relationships between environmental factors and human health outcomes.
Related Research
Sponsorship to Date:
U.S. DOE, NYSERDA, NYSTAR
Research Teams:
Anna Dyson, Kipp Bradford, Simone Rothman, Andreas Theodoridis, Ben Feagin, Mark Bradley, Josh Draper
Industrial Collaborators:
SOM, Future Air
Other Collaborators:
ANL, RPI