loading page

An Assessment of Control Methods in Closed-Loop Agriculture Systems
  • +1
  • Michelle Ragany,
  • May Haggag,
  • Wael El-Dakhakhni,
  • Benzhong Zhao
Michelle Ragany
Department of Civil Engineering, McMaster University

Corresponding Author:[email protected]

Author Profile
May Haggag
Department of Civil Engineering, McMaster University
Wael El-Dakhakhni
Department of Civil Engineering, McMaster University
Benzhong Zhao
Department of Civil Engineering, McMaster University


Climate change and a growing global population pose ongoing threats to critical resources. As resources required by the agriculture sector continue to diminish, it is critical to leverage the emerging technologies and new solutions within the sector. New cultivation practices have emerged over the years, allowing food to be grown within urban areas. Greenhouses are versatile in the resources needed for their operation, as well as the foods that can be grown. While greenhouses provide a potential for a more constant food supply, there is a lack of optimization between the components. There are benefits to having modular components of a greenhouse, allowing for adjustments or repairs to singular pieces. However, there is inefficiency in the entire system, since each component functions without considering the others. To improve greenhouse efficiency, a closed-loop system can be introduced. A greenhouse is a closed system, and by repurposing, reusing, and recirculating resources, a greenhouse can evolve to have a closed-loop system. This enables the components of a system to share resources more effectively, communicate any systems changes that are required, and minimize waste outputs.
This research explores the current technology in the space of agriculture and computer science to create a fully closed-loop system. The most noticeable system components are food waste, nutrient systems, water systems, growing media, and heating and energy. Not all components within a greenhouse can leverage the same artificial intelligence methods and techniques based on existing findings. There are methods in place that allow the components to interpret data gathered from the greenhouse and alter its operational patterns. There remains a lack in communicating this information to other aspects of the system to have it make informed data-driven decisions as well. One can optimize singular components thereby reducing resource reliance, to a certain threshold until it impacts the plant’s development and yield. When all the systems components’ resource needs and outputs converge the functionality of the system can be optimized to utilize resources at a higher efficiency. Results are indicative of very siloed and isolated research, exploring closed-loop systems within greenhouses, but not leveraging its full capabilities.
12 Apr 2023Submitted to AGU Fall Meeting 2022
16 Apr 2023Published in AGU Fall Meeting 2022