Towards Reliable and Optimized Data-driven Cyber-Physical Systems using Human-centric Sensing

Full title: CAREER: Towards Reliable and Optimized Data-driven Cyber-Physical Systems using Human-centric Sensing

Participatory science has opened opportunities for many to participate in data collection for science experiments about the environment, local transportation, disaster response, and public safety. The nature of the collection by non-scientists on a large scale carries inherent risks of sufficient coverage, accuracy, and reliability of measurements. 

This project focuses on these challenges in cyber-physical systems (CPS) experiments. It utilizes a framework that tightly combines the underlying methods and techniques (such as statistics, optimization, control, natural language processing, CPS fundamentals, and coordination of participants) to improve efficiency, effectiveness, and accountability. Validation of the framework is conducted through simulations, case studies, and on real-world CPS-enabled experiments. This project closely integrates education and training with foundational research and public outreach that enhances interdisciplinary thinking about CPS systems, engages the public through participatory science, and broadens participation in science, technology, engineering, mathematics, and computer science.