Data-driven intelligence is an essential foundation for physical systems in transportation safety and efficiency, area surveillance and security, as well as environmental sustainability. This project develops new computer system infrastructure and algorithms for self-sustainable data-driven systems in the field. Research outcomes of the project include (a) a low-maintenance, environmentally-friendly hardware platform with solar energy harvesting and super capacitor-based energy storage, (b) virtualization software infrastructure for low-power nodes to enable inter-operability among distributed field nodes and from/to the data center, and (c) new image and data processing approaches for resource-adaptive fidelity adjustment and function partitioning. The synergy between the self-sustainable hardware, system software support, wireless communications management, and application data processing manifests through global coordination for quality-of-service, energy efficiency, and data privacy. In broader impacts, this project enables data-driven intelligence in the field for important physical system domains. Integration of the technologies involved is accomplished through real-world system deployment and experimentation, including an intelligent campus traffic and parking management system and collaborative work with industry collaborators. The results of this project will further enhance the technological competitiveness for US industries in key areas such as intelligent transportation. The education component includes cross-disciplinary curriculum enhancements and the development of a new instructional platform for realistic experiments with cyber-physical systems. Within the scope of this project, the PIs perform mentoring and outreach activities to recruit/retain women and minorities in science and engineering.