AiPlantCare
(by Fazel Ganji)
AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
Downloads:
190
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AiPlantCare Grasshopper plugin is open-source API to our cloud computing services. This feature helps designers and architects who have already a 3D model in Grasshopper or Rhino and wants to evaluate lighting situation for occupants and plants. AiPlantCare plugin makes it possible to upload your project specifications and 3D geometry to our server smoothly.

You need to register on our website to get your API-Token. Early access is completely free of charge.

This tool estimates the environmental parameters for plants (currently available for lighting. It will be extended for water, temperature, humidity ...). Predicting this information leads to a more sustainable biophilic design solution for offices, landscapes, or even for indoor growers and urban farmers. This also helps growers to decide upon choosing the right plant species among our database (+100,000 cultivars) and estimate the electricity costs for artificial lighting and cooling if needed over the course of a year.

We calculate hourly PAR values on the sensors-grid and Daily light integral (DLI) which have been used in horticulture for decades to express lighting for plants, We introduced annual metric to evaluate the buildings in an early stage of design:

  1. Annual DLI Autonomy (DLIa10) is an annual metric which describes how many day in year (as percentage), a certain point in a room receives enough natural daylight (DLImin  based on the type of cultivar, e.g. 10 mol/m²∙d ). 
  2. Spatial DLI Autonomy (sDLIa10) describes how much space receives enough DLI (in DLI-target range) over the course of a year
  3. Annual PAR exceeded (APE350) was defined to be checked as a pass/fail metric. APE describes how many hours on a certain point a room receives too much sunlight (above PAR cut-off e.g. 350 μmol/m²∙s). The value for PAR cut-off is based on the light saturation point of plant species and may range from 90 μmol/m²∙s to 350 μmol/m²∙s respectively for tulip and rose. 
  4. Spatial Annual PAR exceeded (sAPE350) describes how much of space receives excess PAR (assuming the cut-off upper limit, e.g. 350 μmol/m²∙s).
  5. Annual Risk of Plants SunBurn (RPS350_5hr) describes how many days in year on a certain point in a room receives PAR above cut-off level (e.g. 350 μmol/m²∙s) and longer than the daily limit (e.g. 5 hours in a day). This metric shows the risk of plant sunburn when plants do not have enough time to overcome light stress.
  6. Total Annual electricity demand for artificial lighting (kWh/year) and lighting schedule, an hourly time series profile with required fraction of supplemental light (0-1). These calculations are based on the selected Grow Light’s parameters such as: location in the room and Photosynthetic Photon Flux Density (PPFD). PPFD is the amount of light that actually reaches your plants within the PAR spectrum in μmol/s.m².

  7. Annual shading schedule, an hourly time series profile with required fraction of sun protection on your windows (0-1) for a complete year. This profile is calculated based on receiving excess PAR (assuming the cut-off upper limit, e.g. 350 μmol/m²∙s) in different places in the room.

More documentations you can find here. 

Developed by:

  • Fazel Ganji
  • Morteza Kasravi
License Cost:
Free
  • AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
  • AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
  • AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
  • AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
  • AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
  • AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
  • AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
  • AiPlantCare gh. plugin is open-source API to our advanced cloud-based tool for predicting light for plants using state-of-the-art simulation models and cloud computing features.
Downloads
For instructions on installing Grasshopper Add-Ons, please see FAQ for details.
Title
Description
Platform
 
AiPlantCare ghAPI v0
2021-09-17
AiPlantCare Grasshopper plugin is open-source API to our cloud computing services. You need to register on our website to get your API-Token. Early access is completely free of charge.
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