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Towards A Wearable Crowdsource System to Monitor Respiratory Symptoms for Pandemic Early Warning

In this research, we propose to leverage the ubiquitous wearable devices to develop a wearable crowdsource system to monitor respiratory symptoms such as cough and fever.

Towards Intelligent Multi-Zone Thermal Control with Multi- Agent Deep Reinforcement Learning

In this paper, we investigate the multi-zone thermal control with optimized energy usage and canonical thermal comfort modeling. A multi-zone thermal control algorithm (MOCA) is proposed to solve the problem by deriving optimal control policies.

Lab-on-Mask for Remote Respiratory Monitoring

A smart mask integrated with a remote, non-contact multiplexed sensor system, or “Lab-on-Mask” (LOM) is designed for monitoring the respiratory diseases such as the COVID-19.

DeepComfort: Energy-Efficient Thermal Comfort Control in Buildings via Reinforcement Learning

We implement a building thermal comfort control simulation environment and evaluate the performance under various settings of DDPG based approach.