THESIS PROJECT / 2023 / TEAM PROJCT WITH NILS ACHENBACH / 
iN COLLAboration with: AGILE ROBOTS AG

Greenhouse in 2040

Imagine a greenhouse entirely controlled by an AI designed to grow and harvest crops as efficiently as possible - a continuously changing environment, adapting to the optimal growing condition for each plant.

* images on this site have been generated by Midjourney

In short

ChatGPT about the project: “That sounds like an innovative and ambitious project! Designing greenhouses controlled by AI opens up a world of possibilities for optimizing plant growth and adapting to changing environmental conditions.

Predicting and simulating the impact of climate change on farmlands could greatly benefit agriculture while offering a research area for farmers and researchers would facilitate experimentation and innovation in farming practices. It's exciting to see how technology like AI can revolutionize the way we approach agriculture and food production.”

  • “According to FAO (The Food and Agriculture Organization of the United Nations), under current circumstances, by 2050 the agri-food sector will have to generate 50% more food and feed to be able to meet the increased demand for food.”

  • How might we improve food production through future automation, material printing, and robotics technology? 

* Operator view of the greenhouse productivity

Greenhouse development

From the Outlook to the next necessary steps for a AI run greenhouse

Sketch of Operator Control panel

Envisioning an interface several decades into the future is naturally challenging. This exercise aimed to visualize the key information that should be displayed for the greenhouse operator, explore how they interact and communicate with the AI, and deepen our understanding of the operator’s role in such a futuristic greenhouse scenario.

Sketch of Consumer service

For consumers, we could introduce a more seasonal approach, similar to today’s farmers markets, along with features like “wishlists,” an “experience tour” through the greenhouse, and more comprehensive information about the produce and its various possibilities.

Task Illustrations and Process Exploration

Planting circle

The "Planting Circle" illustration allows us to identify various touchpoints where potential human or robotics interaction occurs and when there is a need for resources from outside the greenhouse. This framework helps us understand and optimize the flow of interactions and resource management within the greenhouse environment.

Human and AI Tasks

Several tasks require human intervention. These include overseeing the process to ensure everything runs smoothly, receiving the harvest, and, most importantly, selling the produce and educating others about it—interactions that machines cannot replicate. Their involvement is crucial for the success and sustainability of agricultural operations.

Benefits

Adapt crops to the changing environments and have a more predictive instead of reactive approach.

AI - Playground

Increase the number of different crop types that are later sold at the market to embrace a more versatile diet.

Increase biodiversity

Introduce crop types that have been lost or deemed too difficult to farm on a large scale. 

Re-introduce ancient crops

Create or pre-grow new crops that are easier to implement in the new environment. 

Adapt to changed conditions

Try out new farming techniques as well as pre-grow crops in a sheltered environment and slowly transition to the climate of origin.

Imitate climate change

Ai-generated growing spaces will have a number of emerging use-cases.

Emerging opportunities

Research process explained

Method

Conduct research on current challenges, explore potential future scenarios, and develop a strategic plan outlining the necessary steps to achieve the desired future outcome.

Farming Evolution

Growing-space exploration

Humans are used to traditional grid-like fields, where we typically plant one crop at a time and build infrastructure around the growing fields for ease of movement. However, embracing more natural growing conditions could lead to improved efficiency, yield, and space usage in agriculture.

Superfoods

Several labs are focusing on creating fast-growing and nutrient-dense new crops, which could help meet the nutritional needs of regional populations. These efforts hold promise for addressing food security challenges and improving access to nutritious foods for communities worldwide.

Next steps

A step-by-step exploration of how we could use AI and robotics to transition to a more naturalistic growing environment.

Greenhouse layout

We explored a layout principle for AI-run greenhouses, consisting of a defined physical space digitally replicated for the AI, with some permanent structures providing essential infrastructure. Additionally, we aim to grant the AI complete freedom in designing the interior of the greenhouse using destructible strong and fragile temporary structures made from biomaterials.

Outlook

Farmers could try out new farming techniques before they need to implement them in their own fields. We could significantly improve the diversity of foods featured in our diet and start growing crops again that were lost due to monoculture in the past decades. We could adapt crops to

the upcoming climates by imitating the environmental changes, we are expecting in different regions around the world. To have a more predictive instead of reactive approach. 

RESearch greenhouses to adapt farming techniques to climate changes
We could enable a farmers market of 2050 in the megacities of the future, producing fresh and locally.
SUperfood greenhouses, adapted to grow nutrient dense food, developed in the next decades