Accurate and reliable knowledge of time is fundamental to cyber-physical systems for sensing, control, performance, and energy efficient integration of computing and communications. This statement underlies the proposal. Emerging CPS applications depend on precise knowledge of time to infer location and control communication. There is a diversity of semantics used to describe time, and quality of time varies as we move up and down the system stack. System designs tend to overcompensate for these uncertainties and the result is systems that may be over designed, inefficient, and fragile. The intellectual merit derives from the new and fundamental concept of time and the holistic measure of quality of time (QoT) that captures metrics including resolution, accuracy, and stability. The proposal builds a system stack ("ROSELINE") that enables new ways for clock hardware, operating system, network services, and applications to learn, maintain and exchange information about time, influence component behavior, and robustly adapt to dynamic QoT requirements, as well as to benign and adversarial changes in operating conditions. Application areas that will benefit from Quality of Time will include: smart grid, networked and coordinated control of aerospace systems, underwater sensing, and industrial automation. The broader impact of the proposal is due to the foundational nature of the work which builds a robust and tunable quality of time that can be applied across a broad spectrum of applications that pervade modern life. The proposal will also provide valuable opportunities to integrate research and education in graduate, undergraduate, and K-12 classrooms. There will be extensive outreach through publications, open sourcing of software, and participation in activities such as the Los Angeles Computing Circle for pre-college students.

This highly interdisciplinary research addresses two fundamental challenges in image sensing and image understanding: 1) versatile camera systems in a small form factor, and 2) 3-dimensional scene and object recognition from 2-dimensional photos. These fundamental challenges are tackled together by developing a cyber-physical imaging system, called smart flexible camera sheet, which integrates an array of many micro-cameras (millimeters in size each) onto a thin substrate. The substrate has flexible geometric shape and the orientation of each camera is individually adjusted and controlled in real time via intelligent algorithms. The overall imaging system is ultra-thin and space-efficient, and can be easily mounted onto or embedded into any planar or curved surface. Hence it opens up a plethora of new civilian and military applications where surveillance and visual monitoring are required, thus bearing great commercialization potential. Example applications are: smart vehicles, smart transportation, highway safety, smart civil infrastructure, manufacturing lines, battlefield surveillance and reconnaissance, sensor networks, mobile robotics, medical facilities, and patient care.