Plant LED biofeedhack system

multispectral LED computer vision plant biofeedhack system

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The goal of my project is to ‘bio-hack’ a plant in order to optimize its overall growth. The project incorporates a digital camera, light emitting diodes (LEDs), and software image analysis tools to conduct non-contact plant growth analysis. The system measures growth parameters such as leaf size, plant height and leaf reflectance. Plant growth characteristics can then be used to regulate the spectral and temporal output of the LED grow lights. The goal of the system is to provide real time feedback to optimize plant development with minimum energy.

I believe this project directly relates to the climate change, overpopulation, food shortage challenge of the ‘Design your concept’ contest. Combining LED and computer vision technology creates the opportunity to develop plant light algorithms that can simultaneously improve plant yield and greenhouse energy efficiency.

The figure shown on the project board is my first attempt to demonstrate the multispectral computer vision plant biofeedhack system concept. The picture was taken with a modified LED grow light and Raspberry Pi noir camera. The picture shows different images of a five week old basil plant leaf illuminated by different LED wavelengths. Top left is a computer vision enhanced image. Top right is white light image. Images below are recorded with ultraviolet (uv1,uv2), blue(blu), green (grn), red and infrared (ir) LED light. Remaining pictures are processed composite images that highlight color contrast. Computer vision software (SimpleCV) extracts the leaf image (colored dark green) and measures number of pixels in the area, length, width and perimeter (bottom text). The picture shows that a measurement system can be built to characterize plant growth and multispectral leaf reflectance. The measurements can then be used to tailor the LED light for different growth conditions.

I am reaching out to the hackaday community for support to build a more advanced prototype (see schematic) and develop improved plant light growth algorithms. I learned a lot building the first prototype for my high school science fair and would like to improve the design by using different LEDs and adding environmental feedback sensors.



Portable Network Graphics (PNG) - 125.43 kB - 03/30/2017 at 04:34

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  • Timelapse computer vision measurement

    mn271828182804/28/2017 at 05:51 0 comments

    Attached video shows computer vision measurments of a basil plant over a 30 day period. The goal was to understand computer vision performance for the LED plant biofeedhack system. Images show the ability of computer vision to measure small features less than 1mm without contact. The next step is to regulate the LED grow lights with data collected from the computer vision measurements. Thanks for following and special thanks for those who 'liked' the project!

    Computer vision software (SimpleCV) extracts basil plant ‘blob’ features from soil background and counts number of pixels in each plant ’blob’. Picture info: Unprocesssed Image (right), computer vision processed image (left) marks counted pixels in green. Text below displays # of pixels in area/ length/width and perimeter for each image. Images are scaled/calibrated by ruler - 1 pixel measures .6mm x .6mm.

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