To the home of WP6 - Digital twin. A workpackage within SPoHF (Sustainable Production of Healthy Food).
image generated with chatGPT

The ‘digital twin’ is a concept used in different contexts, lets make them more explicit:
| Dashboard | Status | Reason/remark | Data source | URL |
|---|---|---|---|---|
| Blue | 🟢 Ready for use | Yookr API | Synced from Yookr API (AppComm) | wp6-blue.spohf.fontysvenlo.dev |
| Red | 🟢 Ready for use | Temporary data source (data from october 2025) | Fontys GreenTechLab database | wp6-red.spohf.fontysvenlo.dev |
| Grey | 🟡 Public demo only | Demonstrating generic platform capabilities (public) | Fake data | wp6-grey.spohf.fontysvenlo.dev |
In behavior they are different, due to different data, models, needs and usage.
The research on blueberries performed by our partner Compass Agro is more scientific-based. It is an experimental approach, where different fertilization strategies are applied in the field, and the results are analyzed chemically to see which one works best. Therefore, the data is being analyzed to find correlations between the sensor data, manual measurements and actions together with the fertilization strategy. Blueberries are perenial plants and the harvest is once a year, so the feedback cycle is very long, and the twin can help in prescribing actions to take over the year to get a more desirable harvest. These actions include irrigation, adding nutrients, and pest control.
The product features provides are therefore more focused on supporting the research and analysis, rather than being a ‘ready to use’ product for farmers or other users. Analysis happens on historical data, to find correlations and insights.
Pending work:
DLI prediction model - (on hold) With the sensor data and weather predictions, we built a model to predict the Daily Light Integral (DLI) in the greenhouse, which is a measure of the total amount of photosynthetically active radiation (PAR) received by the plants in a day. This can help in optimizing costs and light conditions for the tomatoes, especially in winter when artificial lighting is used.
Multi-height - (current focus) In WP1&WP2 a multi-height sensor setup is being implemented in the greenhouse, to measure the microclimate around the plants at different heights. We are investigating developing different views for this (driven by the needs of the users):
Detailed views with prescriptive insight around the microclimate, to support actions on the different growth stages of the plants, including leaf maintenance, heat control, light control and positioning and water control.
(AI-generated prototype)
3D visualization of the microclimates in the entire greenhouse, incorporating multiple multi-height setups
(AI-generated prototype)
Time-lapse visualization of the microclimate around a single plant, to see how it changes over time and in response to actions taken.
see architecture
github SPoHF-WP6-Twins repository