SBIR Phase II: Intelligent modular vertical farming system

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve vertical farms. The global threat to food security and the need to deal with unpredictable climate conditions have opened the doors to advanced precision agriculture and vertical urban farming. Rapidly growing global populations, demand for higher agricultural yields with limited arable farmland drive demand for vertical farming and new technologies to expand access to this method of sustainable crop cultivation.

The proposed system will reduce the burden on the environment by decreasing water, fertilizers and pesticides required to grow crops. These micro-farms will boost agricultural profitability by providing a reliable, sustainable food system with fresh, healthy, and eco-friendly produce. This reduces food waste and the environmental impact of the food supply chain while improving yields and nutritional density.

This SBIR Phase II project advances a system with integrated environmental control, consumables management, alerting, and scheduling. Furthermore, the automated controls are continuously improved by using camera vision to estimate yield and machine learning to forecast yield and optimize the environmental variables. To make the system cost-effective, a novel multispectral camera will be developed to collect agricultural data.

Using machine learning, the images collected will be correlated to the environmental variables, such as pH and nutrient concentration, so that those variables can be optimized to increase yields. In order to improve scheduling and logistics, the platform will track inputs such as seeds, nutrients, and pH solution, using sensors and QR codes to automate consumable replacement.

Sensors and software checks will determine when component or human failure have occurred, before they lead to crop failure, leading to just-in-time component replacement and maintenance.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.