?? AI for Vertical Farming: High-Density Crop Cultivation (CEA-HD) ??

If we divide controlled environment agriculture (CEA) into classes, then high-density controlled environment agriculture (CEA-HD) would be the upper class of CEA aristocrats.

This type of crop cultivation requires significant investments in automation where all environmental conditions are precisely controlled, but it also promises higher yields, a pest-free environment, and food grown in buildings and below ground level.

AI plays a crucial role in optimizing these environments for maximal efficiency and productivity. This is why HD-CEA is one of the best ways to grow food, particularly in urbanized areas (according to FAO , by 2050, 70% of the global population will live in urban settings).

We've already discussed how AI helps with root systems analysis in soilless agriculture, greenness measurement for lettuce, and predictive monitoring and analytics for crops in greenhouses.

That's why today we will check what does AI offer for high-density crop cultivation?

?? A Comprehensive Review of Innovations in Vertical Farming Technologies

Country: ???? South Korea, ???? Bangladesh, ???? USA

Published: 15 November 2023

This study aims to explore the latest technological advancements in vertical farming, focusing on the integration of sensors, automation, robots, and AI to optimize crop yield and resource efficiency.

The research utilized a comprehensive review approach, analyzing advancements in sensing technologies, monitoring and control systems, and unmanned systems. It employed a global perspective, assessing current technological trends in Asia, the USA, and Europe. Key methods included an examination of artificial intelligence applications in data-driven decision-making and the optimization of vertical farms.

In this study, AI plays a crucial role in enhancing data-driven decision-making and optimizing environmental control systems to improve crop yield and resource efficiency in vertical farming.

Key findings reveal significant advancements in sensing technology, automation, and AI applications in vertical farming. The integration of sensors and actuators enables precise environmental control, enhancing crop yield and resource efficiency. The study highlights a global market growth from USD 5.6 billion in 2022 to a projected USD 35 billion by 2032, driven by urbanization and the demand for sustainable food production.

Researchers, urban planners, and agricultural technologists can practically apply the results of this research while planning their vertical farming settings and managing them..

Main tools/technologies

- Sensors (temperature, humidity, CO2, light intensity, EC, pH, DO, water level)

- Actuators (heaters, CO2 delivery systems, lighting control systems)

- Artificial Intelligence

- Internet of Things (IoT)

- Automated control systems

?? Smart Innovations in Aeroponic Farming for Water Efficiency

Country: ???? South Korea, ???? Israel

Published: 6 June 2024

This study introduces a novel inflatable aeroponics smart farm system designed to enhance water efficiency and facilitate the cultivation of high-value crops.

The research utilized a one-month experimental period where the performance of the aeroponic system was monitored in a controlled environment. The methodology involved setting up the system and regularly measuring water usage, nutrient delivery, and plant growth metrics. The experimental setup included dual-space fabric structures for insulation and an innovative nutrient mixer system using inkjet printer technology for precise micronutrient control.

Integrating AI can enhance the inflatable aeroponics smart farm system by optimizing environmental controls, nutrient management, and predictive maintenance, thereby maximizing efficiency and crop yield.

Key findings demonstrate that the system significantly reduced water usage compared to traditional methods, achieving up to 93.5% water savings. The system also ensured consistent and efficient nutrient delivery, leading to optimal plant growth. Additionally, the portable and easily installable design of the inflatable structure facilitated its use in various environments, including urban settings and regions with water scarcity.

Agricultural technologists and urban planners can practically apply the results of this research.

Main tools/technologies

1. Inflatable dual-space fabric structures
2. Inkjet printer technology for nutrient mixing
3. Misting systems with 'dry fog' technology
4. Biofilter integrated drainage systems
5. Air circulation systems

?? Optimizing Air Distribution in High-Density Agriculture

Country: ???? Canada

Published: 2 January 2024

This study focuses on optimizing air distribution in high-density controlled environment agriculture (CEA-HD) using computational fluid dynamics (CFD) to improve indoor environmental conditions for crop growth.

Researchers employed CFD to simulate and optimize the air distribution within a small-scale CEA-HD space. The crops were modelled as porous media zones, and their interactions with the indoor air were represented using user-defined functions for transpiration and photosynthesis. The optimization process involved a simplified 2D model to reduce computational time, followed by validation with a 3D model.

AI can enhance this research by optimizing CFD models and simulations, reducing computational time, and improving the accuracy of environmental control predictions in CEA-HD spaces.

The optimization resulted in a more uniform distribution of airflow and environmental conditions, reducing mean airflow speed variations between cultivation tiers to 19.5% and achieving higher mean velocities of approximately 1.9 m/s at a lower inlet speed of 8 m/s. These improvements suggest better crop growth conditions and potential energy savings in CEA-HD spaces.

These findings can be practically applied by engineers and agricultural facility designers to enhance air distribution systems in vertical farms and plant factories.

Main tools/technologies used

1. Computational Fluid Dynamics (CFD)
2. ANSYS Fluent R19.2
3. Porous Media Model
4. User Defined Functions (UDFs)
5. NSGA-II optimization algorithm

?? What's next in "AI for Vertical Farming"?

In the next edition of "AI for Vertical Farming," we can explore how AI-driven predictive analytics can optimize nutrient delivery and irrigation schedules, ensuring optimal plant growth and resource efficiency in vertical farming systems.

?What do you think about this topic?

How relevant is it for you?

Let us know in the comments ??

See you tomorrow!

Wishes of high yields in your High-Density Crop Cultivation systems,

Maryna Kuzmenko , Chief Inspiration Officer at Petiole Pro

#controlledenvironmentagriculture

Photo credit for cover image

Kabir, M.S.N.; Reza, M.N.; Chowdhury, M.; Ali, M.; Samsuzzaman; Ali, M.R.; Lee, K.Y.; Chung, S.-O. Technological Trends and Engineering Issues on Vertical Farms: A Review. Horticulturae 2023, 9, 1229. https://doi.org/10.3390/horticulturae9111229

References in today's "AI for Vertical Farming: Monitoring of High-Density Crop Cultivation"

1. Kim, J.; Park, H.; Seo, C.; Kim, H.; Choi, G.; Kim, M.; Kim, B.; Lee, W. Sustainable and Inflatable Aeroponics Smart Farm System for Water Efficiency and High-Value Crop Production. Appl. Sci. 2024, 14, 4931. https://doi.org/10.3390/app14114931
2. Larochelle Martin, G., & Monfet, D. (2024). High-density controlled environment agriculture (CEA-HD) air distribution optimization using computational fluid dynamics (CFD). Engineering Applications of Computational Fluid Mechanics, 18(1). https://doi.org/10.1080/19942060.2023.2297027