In 2022, Computomics, Fraunhofer UMSICHT and Osnabrück University of Applied Sciences received a grant for the project LightSaver AI. The goal of the joint project is to create the basis for an intelligent production system for indoor farms in urban areas.
Computomics is responsible for the machine learning (AI) part of the project, and is actively working on an AI-assisted CEA (Controlled Environment Agriculture) method. This method predicts plant performance and development using AI techniques, incorporating chlorophyll-fluorescence data and environmental parameters from the indoor farm. The AI will optimize light conditions in the indoor farm to save energy efficiently, while optimizing the plant's biomass gain.
Project Meeting in Osnabrück
On 30 January, 2024, Rupashree Dass and Michelle Hagen from Computomics traveled to Osnabrück to discuss next steps in the LightSaverAI project. We met with Dr.-Ing. Felix Thoma from Fraunhofer UMSICHT, Prof. Andreas Ulbrich, and Matthias Preusche from Hochschule Osnabrück.
During the visit to the Hochschule Osnabrück's modern greenhouse, we observed live chlorophyll-fluorescence measurements. This experience was particularly exciting, as it offered a firsthand look at the entire system in action. It complemented our previous work with the measurement data obtained on-site.
The meeting concluded successfully, with agreements reached on the design of follow-up experiments. Our productive discussions set a positive tone for the project's progression. As part of our continuing collaboration we’re planning to invite the project partners to our office in the beautiful city of Tübingen later this year.
In the greenhouse (from left to right): Matthias Preusche from Hochschule Osnabrück, Rupashree Dass, Michelle Hagen, and Dr.-Ing. Felix Thoma from Fraunhofer UMSICHT
We are developing the AI algorithm with the time series data from Osnabrück University of Applied Sciences. We have also already developed an app with which the data can be analyzed and compared. This makes it possible to identify trends between light intensity and plant growth. A wide variety of data is collected: Chlorophyll-fluorescence values, environmental parameters - and now also image data, which can be used to track plant growth with the help of computer vision. In the coming months, further data will be generated at Osnabrück University of Applied Sciences, which will help us to optimize and validate our AI. We defined the design of experiment for these trials at our meeting.
Project LightSaver AI is scheduled until March 2025.
Read more about LightSaver AI:
Dr. Rupashree Dass