Muse Schwarzwald:

the AI Farming

The Planet is for us, not for anyone else.

"It underscores our responsibility to deal more kindly with one another,
and to preserve and cherish the pale blue dot, the only home we've ever known."

― Carl Sagan, Pale Blue Dot: A Vision of the Human Future in Space

Why AI Transformation
in the Farming Industry?

Transformative Problem

  • Hit or Miss Base Harvesting
  • GMO (i.e. anti Pesticide) Centered
    Farming
  • Unreliable Yield Predictions from
    Short Term Historical Data
  • Retrospective Problem Solving-Based Risk Management

Our Action Now

  • Data Centered AI & Robotics
    Farming
  • "Correlated" Plants Centered AI
    Farming
  • Data Centered Yield Predictions and Preventive Risk Management

Palm Tree

More than 90% accuracy in image detection
  • Indoor/Outdoor Environment Mapping via LiDAR Sensors
  • Plants and Crops detection technology within the scanning space
  • More than 90% of detection accuracy
  • Target identification for specific fruits and crops in outdoor
    environment
More than 92% accuracy in Palm Fruit Classification
  • Partial Processing of the fruit from the whole detected image
  • Taggig Data Stack of Fruit Condition
  • Targeted Fruit Condition Recognization
  • 92% accuracy of object detection relative to the DNN technology
More than 88% accuracy in fruit ripeness analysis
    and productivity prediction
  • Continuous improvement of accuracy based on deep
    learning-based accumulated data
  • Determining the appropriate time to harvest crops and analyzing
    future yields
  • 88% accuracy of fruit analysis relative to the CNN technology

Feel free to contact us for any business partnerships or solution-related inquiries.

Medical Hemp (Coming soon)

The Core Problem

human labor centered farming under complicated governmental restrictions

Autonomous hemp
farming system

Save Our Planet Together

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