Emotics Attention Analytics Platform

At Emotics, I built a suite of tools to collect data, submit and process it, and display it to stakeholders. This starts with a modularized JavaScript SDK, which allows different features to be easily enabled, disabled, and configured in different integrations. The SDK can be embedded directly into web pages or packaged into e-learning content, like SCORM modules. The SCORM injects a new menu into the existing content to present terms and conditions to the learner and to request that they agree to have the learning session monitored. It then captures snapshots from the webcam and analyzes the imagery for authentication and attention tracking.

No imagery leaves the learners' computers. Instead, our artificial intelligence runs in their browser and sends only its results to the Emotics API. This is built on Express.js and deployed with AWS Elastic Beanstalk to ensure scalability and reliable service. This utilizes a PostgreSQL database cluster on RDS for storage.

After post-processing to summarize each session and optimize data schemas for reporting, our analytics frontend console can be used to review the collected data and the insights our system provides. Compliance managers are able to identify potential problems with ignored sessions or cheating, and learning management teams can identify exactly which elements of their content are succeeding and which content was not engaging to learners. The console is built as a React.js single-page app using material design standards.