Tag: ECE

Crowd in Action: Human-Centric Privacy-preserving Multi-scale Data Analytics for Environmental Public Health

This project is to address the fundamental challenges on collecting and analyzing multi-scale data from multi-sources for environmental public health in a privacy-preserving manner. The developed technologies empower each individual in a community to proactively contribute real-time data of themselves and surroundings for the betterment of public health without compromising his/her privacy. In addition, this project also serves as a training ground for educating future decision-makers and workforce on privacy-preserving healthcare technologies.

Reconfigurable In-Sensor Architectures for High Speed and Low Power In-situ Image Analysis

Cameras are pervasively used for surveillance and monitoring applications and can capture a substantial amount of image data. The processing of this data, however, is either performed a posteriori or at powerful backend servers. While a posteriori and non-real-time video analysis may be sufficient for certain groups of applications, it does not suffice for applications such as autonomous navigation in complex environments, or hyper spectral image analysis using cameras on drones, that require near real-time video and image analysis, sometimes under SWAP (Size Weight and Power) constraints.