Dense Urban Environment Dosimetry for Actionable Information and Recording Exposure (DUE DARE)
Abstract
In dense urban environments there is currently a lack of accurate actionable information on atmospheric composition (gaseous and particulate) on fine spatial and temporal scales. By simultaneously measuring both the environmental state and the human biometric response we propose a holistic sensing environment and methodology for providing accurate actionable information. A state of the art sensor network involving fixed and mobile sensors using machine learning calibration and uncertainty estimation. Comprehensive wearable biometric sensors are used to characterize the real time human response to the composition of the air, making the human response an integral part of the sensor network. The holistic sensor network incorporates embedded real time machine learning to increase functionality in providing actionable insights for active human participants.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 2022
- Accession Number
- AD1190454
Entities
People
- David J. Lary
Organizations
- University of Texas at Dallas