This project aims to develop a new Science of Design for societal-scale Cyber- Physical Systems (CPS).

The Cyber-Physical Systems Virtual Organization (CPS-VO) was founded by NSF in 2010 to: (i)facilitate and foster interaction and exchanges among CPS PIs and their teams; (ii) enable sharing of artifacts and knowledge generated by the projects with the broader engineering and scientific communities; and (iii) facilitate and foster collaboration and information exchange between CPS researchers and industry. During the last five years, the CPS-VO has become the focal point of the CPS community in the US and it has played a significant role in catalyzing CPS research world-wide.

Transportation accounts for 28% of the total energy use in the United States and as such, it is responsible for immense environmental impact, including urban air pollution and greenhouse gas emissions, and may pose a severe threat to energy security. As we encourage mode shift from personal vehicles to public transit, it is important to consider that public transit systems still require substantial amounts of energy; for example, public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO2 emission annually.

Public transportation infrastructure is an essential component in cultivating equitable communities. However, public transit agencies have historically struggled to achieve this since they are often severely stressed in terms of resources as they have to make the trade-off between concentrating service into routes that serve large numbers of people and spreading service out to ensure that people everywhere have access to at least some service.

The rapid evolution of data-driven analytics, Internet of things (IoT) and cyber-physical systems (CPS) are fueling a growing set of Smart and Connected Communities (SCC) applications, including for smart transportation and smart energy. However, the deployment of such technological solutions without proper security mechanisms makes them susceptible to data integrity and privacy attacks, as observed in a large number of recent incidents. If not addressed properly, such attacks will not only cripple SCC operations but also influence the extent to which customers are willing to share data.

Anomaly detection, prognostication and automated mitigation are very critical for data center management. Most of these approaches can be divided into two categories - model-based and data-driven. While model-based techniques rely on physics guided models that can explain and predict the expected progression of parameters such as temperature and voltage in electronics, the data-driven approach is suitable for complex scenarios where a suitable physics based model is unavailable. The data-driven approaches can be further divided into supervised and unsupervised methods.

Cyber-Physical Systems (CPS) are composed of a wide range of networked physical, computational, and human/organization components. These systems are highly complex as they have many different heterogeneous components, such as physical, computational, and human. Simulation-based evaluation of the behavior of CPS is complex, as it involves multiple, heterogeneous, interacting domains. Each simulation domain has sophisticated tools, but their integration into a coherent framework is a difficult, time-consuming, labor-intensive, and error-prone task.

WIPER is a novel wireless animal-borne anti-poaching device that provides an immediate alert with a GPS location to authorities once a shot is detected near the protected animals. WIPER is based on a low-power acoustic shot detector integrated into existing GPS tracking collars currently being used to study a wide variety of animals. As opposed to muzzle blast-based detectors, WIPER detects the ballistic shockwave generated by the bullet that cannot be muffled by suppressors commonly used by poachers.