Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems
Aaron Washington - Central State University
Co-Author(s): Marcus Nagle, Central State University, OH
Using artificial intelligence technology, a system was trained to regulate the growth conditions in a hydroponic chamber to help the plants grow faster, larger, and more nutritious. This was modeled after the concept of the MIT food computer which uses microcontrollers and programming to set up a monitoring system. The artificial intelligence optimized conditions for the plants by changing environmental factors to encourage more nutritious growth. Within the constructed system, pH, temperature, relative humidity, and electric conductivity were regulated under the design of a CEF (controlled environment farm). The system was validated with lettuce plants grown over successive 6 week periods. Growth and biomass production were documented. Images of the plants were recorded throughout the growth process and are being used to create a large database of plant information to a neural network that will read the sensor data and cause the system to react based on attributes of how the plants grow. This data is being interfaced with a web app to visualize the system and alert the user of conditions. The results presented serve as a basis for home and urban gardening systems of the future.
Funder Acknowledgement(s): Funder Acknowledgement(s): I thank Central State University and NSF-IPSRG for funding.
Faculty Advisor: Dr. Marcus Nagle, email@example.com
Role: I worked on the sensors, data management, AI creation, and the hydroponic system.