Clemson University is leading the way in transforming indoor crop production using high-tech methods. Javad Velni, a professor of mechanical engineering, is at the forefront of this change. He is working on new techniques in controlled-environment agriculture.
This type of agriculture involves growing crops in greenhouses and other structures. It uses advanced engineering and horticulture techniques instead of traditional outdoor farming. It has many benefits, such as moving food production closer to cities, increasing efficiency, reducing supply chain issues, and protecting against extreme weather.
However, it also has high costs for artificial lighting and climate control. Velni and his team are trying to reduce these costs. They are using renewable energy sources, advanced sensing, computing systems, and innovative networked sensing and control systems.
The goal is to decrease energy use and optimize crop growth by continuously adjusting the greenhouse’s conditions, such as lighting, temperature, and carbon dioxide levels. They want to create fully autonomous greenhouses that produce as much energy as they consume. “We need more efficient agricultural practices to feed growing urban populations around the world,” Velni said.
“Controlled-environment agriculture has delivered an increase in production efficiency, but current greenhouse facilities consume a substantial amount of energy just to power the electric lighting and heating and cooling systems. With our work, we are aiming to cut the cost of electricity.”
The world’s population is expected to increase by 26% by 2050, with 68% of people living in urban areas.
High-tech solutions in indoor farming
Velni and his team are using an interdisciplinary approach to tackle this challenge. They combine expertise in automation, control systems, computing, data science, and agricultural science. In a new federally-funded project, researchers plan to test their ideas in a greenhouse by growing lettuce and tomatoes.
They will build custom autonomous robots to collect detailed data on the crops. These robots will have cameras and specially designed arms to capture images from various angles. The thermal and RGB images will help researchers create a model to predict crop growth and yield.
The project also aims to develop a model to help greenhouses control environmental conditions. This will optimize photosynthesis for crop growth while using weather forecasts and crop needs to predict energy consumption and maximize efficiency. Velni has a background in advanced controls, using data-driven approaches and first-principles tools.
He has applied his work to various applications, including autonomous vehicles. In 2018, he began focusing on supplemental lighting control for greenhouses. “The cost of electricity used for the supplemental lights alone varies between 10% and 30% of the total cost of running a greenhouse,” he said.
“Funding for this new research will help us tackle that challenge and others. We have assembled a talented team and are well-positioned to make advances in controlled-environment agriculture.”
Velni’s latest project is funded by the National Science Foundation and the National Institute of Food and Agriculture. He is collaborating with researchers from Texas A&M, the University of Virginia, and the University of Memphis.
