20240015405. DYNAMIC LIGHTING FOR PLANT IMAGING simplified abstract (Mineral Earth Sciences LLC)
Contents
DYNAMIC LIGHTING FOR PLANT IMAGING
Organization Name
Inventor(s)
Erich Schlaepfer of Sunnyvale CA (US)
DYNAMIC LIGHTING FOR PLANT IMAGING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240015405 titled 'DYNAMIC LIGHTING FOR PLANT IMAGING
Simplified Explanation
The abstract of the patent application describes a method for adjusting the illumination of an agricultural robot or modular sensor package based on uneven illumination in captured image data. This is achieved by processing the image data using a reinforcement learning policy model to generate illumination output, which indicates the lights that need to be adjusted.
- The method involves capturing an initial instance of image data using one or more sensors of the agricultural robot or modular sensor package.
- The initial image data captures one or more crops in a portion of a plot of land.
- The reinforcement learning policy model is used to process the image data and generate illumination output.
- The agricultural robot or modular sensor package can adjust one or more lights based on the illumination output.
- An updated instance of image data is captured with the adjusted illumination.
Potential applications of this technology:
- Precision agriculture: The technology can be used in agricultural robots or sensor packages to optimize lighting conditions for crops, ensuring even illumination and improving crop growth.
- Plant monitoring: By adjusting lights based on uneven illumination, the technology can help in monitoring the health and growth of plants more accurately.
- Indoor farming: The method can be applied in indoor farming systems to provide optimal lighting conditions for crops, enhancing their growth and yield.
Problems solved by this technology:
- Uneven illumination: The technology addresses the issue of uneven lighting in agricultural settings, which can negatively impact crop growth and yield.
- Inaccurate plant monitoring: By adjusting lights based on illumination output, the technology improves the accuracy of plant monitoring systems, providing more reliable data for analysis.
Benefits of this technology:
- Improved crop growth: By adjusting lights based on uneven illumination, the technology can enhance crop growth and yield.
- Efficient plant monitoring: The accurate adjustment of lights ensures more reliable plant monitoring data, leading to better decision-making in agricultural practices.
- Increased efficiency: The use of reinforcement learning policy models allows for automated adjustment of lights, reducing the need for manual intervention and saving time and effort.
Original Abstract Submitted
various implementations include processing an instance of image data using a reinforcement learning policy model to generate illumination output, where the illumination output indicates one or more lights of an agricultural robot or modular sensor package to adjust based on uneven illumination in the instance of image data. in many implementations, the initial instance of image data is captured using one or more sensors of an agricultural robot or modular sensor package, where the initial instance of image data captures one or more crops in a portion of a plot of land. in various implementations, the agricultural robot or modular sensor package can adjust one or more lights based on the illumination output, and can capture an updated instance of image data of the given one or more crops with the updated illumination.
