Controlling and Optimizing Artificial Ecosystems Using Advanced Plant Feedback Loops

Important results from the project

This project has demonstrated the potential of combining AI and sensor technology to enable smarter, more efficient farming systems. By testing the solution in a demo environment, we gained valuable insights into how crops respond to changing environmental conditions. These findings led to increased yields and laid a solid foundation for Ljusgårda’s continued development and future large-scale implementation.

Expected long term effects

The project is expected to enable plant-driven, AI-based cultivation systems with higher yields and reduced resource use. By interpreting plant signals in real time, growing conditions can be optimized automatically. This increases efficiency, reduces climate impact, and strengthens Sweden’s position in sustainable AgTech. The solution is scalable, exportable, and lays the foundation for continued AI development and future autonomous food systems.

Approach and implementation

The project had three phases: sensor technology, cultivation, and AI. The first phase took longer than planned, as the technology required more calibration. This affected the time for test cultivation and AI training, but the collaboration provided deep insights into the crop’s specific needs. With a month´s extension, we demonstrated that the sensors enable dynamic environmental adjustments and that the AI can provide recommendations based on the plant’s needs, including light and irrigation.