Google analytics in real life

Analyticat was built during the StirHack 2017 MLH event, over the course of 24 hours.

What is Analyticat designed to do?

  • Register IoT video sources to gain analytics about your customers; including:
    • a measure of recurring customers on an individual, but anonymous level, using AWS-powered facial recognition (you will not be able to track individual customers)
    • estimate demographics including gender, age etc.
  • View analytics in a clean dashboard. You can view analytics over various discrete timesteps (hours, days, weeks, etc.) for your registered video sources (or groups thereof).
  • Utilise our own REST API so that you can use your own analytics data for something more unique!

user interface mockup

Current Functionality

  • The frontend mockup is available to view.
  • Our REST API is somewhere in the region of 50% finished:
    • finished:
    • emotional and sentiment analysis of people in uploaded images
    • check similarity between two people in uploaded images
    • not finished:
    • demographic analysis (age, gender, etc.)
    • coordination and interfacing between the IoT layer, the front end and our AWS MySQL database
  • We currently have a camera watcher which continually watches over the default camera - whenever a face is detected the image is saved (but would be uploaded via our REST API upon completion).
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