Vivent Biosignals · Decision support

Plant-Driven Lighting

Translating plant-science knowledge into analysis and dashboards that help people reason about lighting and climate.

In 30 seconds

Question
When might additional light help, and when could climate limit the plant's response?
My contribution
Data analysis, analytical logic, Grafana dashboards and product communication with plant scientists.
Outcome & evidence
Decision-support dashboards for investigating lighting and climate. The public infographic explains the concept; internal implementation remains private.

The problem

More artificial light does not necessarily mean a plant can use it effectively. Temperature, humidity and other conditions can limit its response. This work explores how the plant’s own signals can help assess when additional light may be useful.

The approach

The approach combines plant-science expertise with analysis of plant and environmental data. My contribution covers the analytical logic and Grafana dashboards, refined through feedback on how clearly they communicate. These views help users assess the situation and decide what to investigate next.

Plant signals and light and climate data inform dashboard analysis and a grower’s lighting assessment.Enlarge
Plant-Driven Lighting
Text description of the infographic

Plant signals and conditions are analysed together. A grower uses the dashboard to consider more light, maintaining the current level or less light. The visual describes decision support; it does not show autonomous control.

The challenge

A dashboard needs to distinguish an observation from an interpretation. It should make a complex plant response understandable without suggesting that one signal proves what a grower should do.

Outcome & value

Decision-support concepts and dashboards for exploring whether additional light may help, whether climate could be limiting plant activity, and whether increasing, reducing or maintaining lighting warrants investigation. This work supports human decisions; it is not presented as autonomous greenhouse control.

Lessons learned

The analytical result and the way it is shown are part of the same product. Collaboration with domain specialists made both the reasoning and its limits clearer.

Evidence & artifacts

This case describes my contribution at a conceptual level. Internal data, code and dashboards remain within Vivent.

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