The goal of this research project is to develop a scalable cyber-physical system (CPS) framework for the integration of physical and computational systems for bridge lifecycle monitoring. Bridge monitoring involves several independent but isolated components. Sharing of information and software modules across different systems is limited. Information sharing and system integration would facilitate meaningful use of data, thereby enhancing bridge operation and maintenance and public safety.

This project is focused on the fundamental research in establishing a foundational framework towards the development of an autonomous Cyber-Physical System (CPS) through distributed computation in a Networked Control Systems (NCS) paradigm. Specific attention is focused on an application where the computational, and communication challenges are unique due to the sheer dimensionality of the physical system. An example of such CPS is the smart power grid, which includes large-scale deployment of distributed and networked Phasor Measurement Units (PMUs) and wind energy resources.

Abstract: Cycling communities have been related to lower obesity rates and lower stress levels. Nevertheless, one of the main obstacles to increase ridership in cities is the lack of information regarding perceived cycling safety at the street level. City planners have typically used extensive road network and traffic information to approximate cycling safety levels.

This project features conception, design, and deployment of a wireless network of embedded devices, for monitoring the behavior of animals in the wild.  The system is being deployed and tested in biologically relevant scenarios.

This NSF CPS EAGER project supports the SmartShuttle and SMOOTH II NIST GCTC technical cluster projects of the City of Columbus and the Ohio State University by developing a unified and scalable solution architecture for low speed automated shuttle deployment in a Smart City. This project will help the development of Columbus as a Smart City, having a broad impact on the mobility choices of its inhabitants.

We apply formal specification and verification techniques for checking correctness properties of artificial pancreas control algorithms. Formal specification and verification techniques attempt to systematically and exhaustively explore the behaviors of closed loop in silico models to understand the worst case effects of disturbances such as meals, external boluses, sensor noise, pressure induced sensor attenuation and set failures on the predicted blood glucose levels of a “virtual” patient.