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Weighbridge automation using Raspberry Pi, YOLO object detection, and AWS.

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Weigh Bridge Automation

Project Video

Project objective

  • A weighbridge is one of the key critical areas for crop selling to the framers.
  • A lot of mischievous activities happening at this stage which resulted in farmer's suicide rate increased by 15% every year.
  • We want to solve the weighbridge problem using object detection by the YOLO framework a neural network and deep learningmodel which runs on a cloud for processing and images captured by Raspberry Pi.
  • This framework guides the user to avoid the weighbridge misplacement.

Project environment

  • Using Anaconda Navigator with YOLO,Tensorflow a video guide for object detection.
  • The following link holds important files:Google drive.
  • The reference video is TeamGo.mp4.
    • You need a Windows10 PC with 8GB RAM and Nvidia GPU.
    • First of all create a separate work environment on Anaconda Navigator to run YOLO work-flow.
    • Download YOLO files of .cfg and .weights for object detection from offical website.YOLO
    • Install tensorflow-gpu, conda numpy etc prescribed in TeamGo.mp4.
    • Inorder to use C++ files of YOLO we need to install Visual Studio developer version 13+ version.
    • Use help.txt file commands info.

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Weighbridge automation using Raspberry Pi, YOLO object detection, and AWS.

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