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@TinyCamML

TinyCamML

Hi there đź‘‹

IN PROGRESS README

The purpose of this organization is to describe how to build an sensor with on-device machine learning and cellular transmission to identify spatial extent of coastal flooding. The two main devices are the OpenMV and Particle Boron. Below are a list of the repositories within this organization that help understand the individual devices (including firmware and circuit diagrams) and how they can be combined to create a functioning long-term, low cost, high efficiency sensor.

This organization is a community of scientists from the University of North Carolina at Wilmington, North Carolina State University, and Sediment,LLC.

There is several active repositories.

  • TinyCamML repository, which contains firmware for the openMV and the Boron, a circuit diagram, and more images of what you should be looking at. The Boron's firmware in this repository is unique from the other repositories because it includes added cellular transmission and long-term sleeping capabilities. With this updated firmware and correct power supplies you should be able to create a device independent of the computer that has cellular transmission and publishing abilities. This repo is in progress.

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  1. TinyCamML TinyCamML Public

    This repo is continued progress between Boron and OpenMV as a self contained device that can successfully monitor flooding on roadways.

    Jupyter Notebook 3 1

  2. Flood-Model Flood-Model Public

    The repository for development of the ML model for OpenMV

    Jupyter Notebook 1 1

  3. .github .github Public

  4. DeploymentAnalysis DeploymentAnalysis Public

    Analysis codes for data from TinyCamML deployment

    Jupyter Notebook

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