OpenCivi

What is OpenCivi? #

Is an edge platform and framework for archeologists to analyze images in remote locations using computer vision. This project was born because of the local archeologists needs in Guatemala, that often research about Maya civilization. This project was created and maintained by Sergio Méndez and collaborators around the USAC university in Guatemala.

Why is called OpenCivi? #

OpenCivi refers as a series of tools for archeologists to understand old civilizations like Mayas, Incas and Aztecas, that where it comes the Civi abreviation for civilizations. Also Civi can be Civ + i, where i is the Roman number for 1, also we can say Civ1, that is the first civilization. Civ1 also refers to a video game called Civilizations or Civ1. Also because this project should start using OpenCV as a tool for Computer Vision sounds pretty similar, thats the reason to use the name OpenCivi. Civi = Civilization = Civ1 + OpenCV = OpenCivi or could be called OpenCiv1 or just Civi Let’s see what people prefer.

Features #

OpenCivi implements the following features to analyze archeology data like maps and images::

  • Image analysis for glyphs using Machine Learning (Neural Networks)
  • Image processing and object detection (Computer Vision with OpenCV)
  • Remote data processing using low-resources devices (Kubernetes)
  • LiDAR (light detection and ranging) for map creations using Laser
  • KAMiDAR (Photos and analysis) for map creation using Photos
  • Portable embedded SO to run OpenCivi on RPi devices
  • Support for ARM and Intel

Note: Some of these features are not implemented yet

Use cases #

OpenCivi is mostly used by archeologists in remote location but not limited to. It could be used for:

  • Image analysis (Glyphs,Photos, etc)
  • Object detection (Glyphs,Ceramic,Sediment, etc)
  • GPS maps (Altitude maps)

Challenges #

Create a sustainable solution for archeologist around the world focused on low budget projects, so the main idea is that this platform should be accesible to anyone, in order to implement this platform. So for this platform we have the following challenges:

  • Low energy consumption
  • Resist weather conditions
  • Run on remote locations
  • Portable
  • Low-cost