Imagine if plants could tell us exactly when they are thirsty or stressed by how they react to flickering lights. This project creates a high-tech 'translator' that uses fast-pulsing lights and sensors to read a plant's health in real-time. It then adjusts the lighting to give the plant exactly what it needs, avoiding wasted electricity and water.
Indoor farming consumes excessive water and energy because lighting and irrigation are often static. There is a lack of real-time, precise tools to detect plant stress and adjust resources dynamically.
Developed kinetic fingerprinting methods for stress detection, 100 kHz modulated lighting sequences, and low-cost imaging prototypes for plant monitoring.
If you are an indoor urban farm operator dealing with high electricity bills for LED arrays — this project developed modulated illumination and kinetic fingerprinting that optimizes light usage while supporting advanced plant growth.
If you are a greenhouse equipment manufacturer dealing with imprecise crop monitoring — this project developed low-cost imaging protocols and miniaturized data acquisition prototypes that ensure consistent monitoring in controlled environments.
If you are an algae producer dealing with unstable culture health — this project developed sensing protocols using kinetic data and Bode plots to detect stress in organisms like C. reinhardtii.
Based on available project data, specific pricing is not provided, but the project explicitly aims to decrease the cost of lighting by equipping it with sensing capabilities and using low-cost imaging protocols.
The project targets widespread adoption in greenhouses, vertical farms, and indoor gardens, and includes a server with incremental learning to extend sensing to various organisms and environments.
Based on available project data, the project utilizes an open source community for its learning server, but specific patent or licensing terms for the hardware prototypes are not listed.
The technology involves ultra-fast multisinewave lighting sequences capable of 100 kHz modulation, which would require integration into the lighting control hardware.
The project period runs from 2022-04-01 to 2026-03-31, suggesting that final validated results will be available by early 2026.
The consortium is well-balanced for technology transfer, consisting of 8 partners across 6 countries. With a 38% industry ratio (3 industrial partners, including 1 SME), the project bridges the gap between fundamental research at CNRS and commercial application in the scientific instrument and plant production sectors.
Contact the CNRS (Centre National de la Recherche Scientifique) in France.
Contact us to connect with the DREAM consortium for pilot testing of smart lighting prototypes.
