HARNESSING RECENT PROGRESSES ON WASTEWATER TREATMENT, FOOD SECURITY, DATA ANALYTICS, AND MACHINE INTELLIGENCE, WE PROPOSE TO STUDY NOVEL OPTIMIZED TECHNOLOGY-DRIVEN CONTROLLED-ENVIRONMENT AGRICULTURE (CEA) SYSTEMS THAT CAN ACHIEVE HIGH AREAL VEGETABLE PRODUCTIVITY TO INCREASE THE FOOD AND NUTRITIONAL SECURITY IN URBAN AREAS WITH LOW OPERATING COST AND REDUCED ENERGY CONSUMPTION.OUR PROJECT FOCUSES ON TWO CORE CPS RESEARCH AREAS, I.E., CONTROL AND DATA ANALYTICS, INSPIRED BY THE DESIGN AND OPERATIONS OF A PILOT TESTBED AT GEORGIA TECH FOR COUPLING THE WATER AND NUTRIENTS IN DOMESTIC WASTEWATER (DWW) TO HIGH-PRODUCTIVITY CEAS. FOOD PRODUCTION IN THE CEAS MUST WARRANT THE HIGH COST OF LAND IN URBAN AREAS, WHICH MAKES IT NECESSARY TO REDUCE THE TOTAL DWW-CEA OPERATING COST AND INCREASE PRODUCTIVITY. HOWEVER, IT IS HIGHLY CHALLENGING TO CONTROL AND OPTIMIZE THIS COMPLEX SYSTEM OF SUBSYSTEMS. IN OUR CASE, WE NEED TO COORDINATE THE PILOT-PLANT AND PILOT-FARM, EXAMINE THEIR INTER-CORRELATION, AND SUPPORT DYNAMIC AND ROBUST OPTIMAL DECISIONS TO ACHIEVE THE HIGHEST PRODUCTION YIELD, WHILE SIMULTANEOUSLY SATISFYING VARIOUS PERFORMANCE SPECIFICATIONS ON NUTRIENT COMPOSITIONS, OPERATING COST AND ENERGY CONSUMPTION, AND MEETING OTHER SAFETY REQUIREMENTS OF DWW-CEAS. MOREOVER, THE PROFOUND IMPACT OF NUMEROUS OPERATING CONDITIONS AND PARAMETERS ON THE VEGETABLE PHENOTYPE, YIELD AND NUTRIENT COMPOSITIONS DURING DIFFERENT GROWTH PERIODS NEED TO BE THOROUGHLY UNDERSTOOD. WE HAVE TO MOVE FROM MODEL-DRIVEN CPS FUNDAMENTALS TO AN INTEGRATED DATA-DRIVEN MODEL-BASED APPROACH.