Data Collection and Model Re-training

There are types of data generated by the edge device.

  • Raw video clips. With limited disk space on edge device, the video clips are regularly uploaded to a data center with multi-layer backups. This type of raw data is meanful for future study and backtracing.
  • Metadata from AI models. As previouly descibed, the AI software will recognize fishes appreared in the video streams. Therefore, the metadata will include image frames that actually contain fishes. For each meaningful image frames, the locations and categories of fishes will be marked. This type of metadata will enable more scientific analysis such as fish counting, fish habit research etc. More importantly, the metadata will be used to retrain the AI models used in the software. Overtime, the AI models will give more accurate recognition.

In order for the solution to operate optimal, it requires a good stable internet connection. In this solution fiber was available, but the solution should work just as fine over 5G and possible even over 4G as uploading can be done without real time

Having a centralized cloud storage solution is vital in order to reduce on site investments. It also enables the solution to share all previous learnings to new installations, giving them a stating point at the level of all existing solutions deployed. Each solution with contribute with additional learnings and increased quality benefitting all the others.