STTR Phase I: Automation and Optimization of Aquaponics for Urban Food Production

Period of Performance: 07/01/2015 - 06/30/2016


Phase 1 STTR

Recipient Firm

Clearton, LLC
199 E. Montgomery Ave. Suite 100
Rockville, MD 20850
Firm POC
Principal Investigator

Research Institution

University of the District of Columbia
4200 Connecticut Ave NW, DC 20008
Institution POC


The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project will be to develop an automated high-intensity food production system that can be operated in urban neighborhoods to provide fresh food to urban populations. This innovation, through the development and testing of the automation technology, will enhance scientific and technical understanding of how computer science and information technology can be used for urban food production. Food systems address not only the environmental/physical dimensions of urban sustainability, but they are also intensely cultural. Food creates communities. Food systems can, therefore, address both the social/cultural and the environmental/physical aspects of urban sustainability. The goals are to make disruptive and innovative contributions to urban food security, and to improve the state of the food-related illnesses such as obesity, diabetes, and hypertension in urban neighborhoods. This STTR Phase I project proposes to develop an "automated and continuously optimized" aquaponics system that can be operated in urban neighborhood for high-intensity food production. This system builds on the symbiotic relationship of animal farming and growing vegetables. The waste produced by the animal supplies nutrients for the plants. Yet, such a symbiotic relationship is not simple. The main research objective is to control the symbiotic nutrition flow in order to maintain the optimal balance of the delicate ecosystem in a continuous and maximally automated manner. This project will develop an urban neighborhood aquaponics automation package that consists of sensor-actuator technologies and an automated controller based on Big Data and Internet of Things technologies. This will enable research that will determine if linear control theory with perturbation theory or nonlinear time-domain state-space methods can be effective in the automation. This research and development will redefine the state-of-the-art in the area of high-tech aquaponics using control theory, Internet of Things, cyber-physical computing, and Big Data technologies at the juncture of human and nature intersection.