The artificial pancreas (AP) is a set of increasingly sophisticated devices and algorithms that will automate the delivery of insulin to patients with type-1 diabetes. While the AP concept promises to alleviate the burden posed by the self-management of blood glucose levels, it also poses significant risks arising from a combination of external disturbances such as patient meals, physical activity, sensor errors, network delays and physiological variations.

Our proposal’s main objective is to realize cyber-physical platform and principles for (i) interrogating global modalities of intracellular transport with causative factors isolated at the single-molecule scale and (ii) realizing efficient and robust infrastructure for transporting micron/molecular scale cargo using distributed strategies We are realizing in-vitro, a transport network with roadways formed by microtubules where motorproteins, kinesin and dynein, will form vehicles ferrying cargo.

Despite many advances in vehicle automation, much remains to be done: the best autonomous vehicle today still lags behind human drivers, and connected vehicle (V2V) and infrastructure (V2I) standards are only just emerging. In order for such cyber-­‐physical systems to fully realize their potential, they must be capable of exploiting one of the richest and most complex abilities of humans, which we take for granted: seeing and understanding the visual world.

Performance monitoring data (e.g., measurements, logs, events) are becoming increasingly accessible and abundant (in terms of cost and availability) in modern distributed complex systems such as computer systems and networks, integrated buildings, industrial systems, transportation networks and power-grids. With efficient exploration of such data, health monitoring, diagnosis and prognosis can be greatly improved from the current state-of-the-art.

Assistive machines, like robot arms mounted on powered wheelchairs, promote independence and ability in those with severe motor impairments. Users of these assistive robots can teleoperate their devices to perform activities of daily living like eating and self care. However, as these machines become more capable, they often also become more complex. Traditional teleoperation interfaces cover only a portion of the control space, and it is necessary to switch between di erent control modes to access the full control space.

Overall Objective. The goal of this project is to facilitate the timely retrieval of dynamic situational awareness information from field deployed nodes by an operational center in disaster recovery or search and rescue missions, which are typically characterized by resource-constrained uncertain environments. Efficient situational awareness information retrieval under severe resource limitations is critical in applications like disaster response. Technology advances allow the deployment of field nodes capable of returning rich

Cyber-Physical Systems (CPS) are being increasingly deployed in critical infrastructures such as electric-power, water, transportation, and other networks. These deployments are facilitating real-time monitoring and closed-loop control by exploiting the advances in wireless sensor-actuator networks, the internet of “everything,” data-driven analytics, and machine-to-machine interfaces. CPS operations depend on the synergy of computational and physical components.

The project is to develop an Executable Medical Best Practice Guidance (EMBG) system to assist the adherence of acute patient care at a rural hospital to the best medical practice as if the patient care is at a regional hospital. The EMBG system is adaptive to the changing needs of a patient and physical resource availability, just as a GPS-enabled navigation system can driver’s preference and accommodate road condition changes.

The cities in the U.S. and elsewhere in the developed world are experiencing a transformation: Many people demand denser neighborhood with mixed use, while they choose to utilize public transportation, rather than private cars, for their commute and other daily transportation needs. To support this trend, cities are in need of novel transportation and logistics services that can help address the needs of their citizens, boost their productivity, and increase the wellness of their lives. There are a number of emerging technologies that can address this challenge.

Autonomy-enabled transportation networks are rapidly becoming a prominent Cyber-Physical-Systems (CPS) application area with tremendous potential for societal impact, as the autonomous systems technology penetrates into aerial/road vehicles and as the concept of connected vehicles emerge. The potential opportunities are not gone unnoticed. For example, unmanned aerial vehicle (UAV) based delivery networks has already attracted innovative companies like Amazon, Google, and Matternet.