Title: A smart-sensing AI-driven platform for scalable, low-cost hydroponic units
The aim of the project is to develop a cost-efficient smart-sensing ICT platform capable of monitoring the crops’ health and nutrient content of hydroponically cultivated microgreens in order to optimize the cultivation process and allow the harvest of the best possible products in any hydroponic installation. GOhydro aspires to culminate in the production of a radical platform that will be a shifting paradigm of how AI-driven technological innovation can become an affordable, accessible-by-all and user-friendly tool applicable to all forms of urban farming. In a nutshell, the proposal aims at creating an easy-to-use e-agronomist which will assist any grower to fine-tune and optimize her hydroponic production every step along the way.
The final outcome of the project will be a prototype of a smart-sensing ICT platform that can be used with any low-cost hydroponic unit available in the market. The GOhydro platform will integrate different sensor kits for nutrient, plant health and environment monitoring for indoor production of basil and other microgreens. Low-cost hydroponic units will be used with the GOhydro platform, which will serve as an e-agronomist to aid informed decision-making by hydroponic growers to produce nutrient dense and high yields of basil and other microgreens. Project outputs will contribute to a number of economic, societal and environmental benefits by integration of nutrient, plant health and environmental sensor kits into one single integrated unit to monitor the plant growth and improve the quality and quantity of low-cost hydroponic units. The project will test and validate the functions of the platform in basil production. The same platform is envisioned to be amenable in its future versions for other commonly grown microgreens, such as lettuce, mint and coriander.
The core of the GOhydro platform will be based in the merging of two innovative tools: (a) a new type of fully-immersible, microfluidic-free silicon photonic probes capable of effortless on-the-spot spectral recording of microgreen pulps and (b) an artificial intelligence (AI) component implementing a multi-model approach that will be able to produce accurate predictions and recommendations with limited amounts of data. The development of the platform will be driven by a thorough review and analysis of the factors that affect microgreens growth and nutrient quality, in terms of nutritional and environmental requirements as well as lighting needs of the plants (light quality, quantity, intensity and photoperiod). The analysis will lead to the selection of sundry sensing devices to be included in the platform as a Multi-modal sensor kit, and the subsequent definition of multiple climate recipes, i.e. environmental and nutrient configurations to be checked for optimising the cultivation of microgreens. To obtain reliable results, the project will adopt a strategy of multiple evaluation cycles of incremental proximity to the realistic usage of the platform, i.e. as a stand-alone hydroponic unit installable in everyday settings (offices, houses) and requiring no expertise to be managed and configured.
Funding programme: ERA-NET COFUND ICT-AGRI-FOOD
24 months (01.12.2020 - 05.12.2022)
- Total budget: 983.6k€
- Holisun budget: 123.7k€
Steps and reports:
- Modeling the architecture of the analysis platform 01/12/2020 - 05/12/2021
- Development of the platform and algorithms for data analysis and platform validation 06/12/2021 - 05/12/2022
- Scientific and technical report
- Final report