Integrating Eye Tracking Data with a Data Center Infrastructure

[Arthur Leo]

Hello everyone,

I’m working on a project to integrate Tobii’s eye-tracking technology with a cloud-based data center infrastructure for an enterprise application. Our goal is to gather real-time eye-tracking data from multiple users and relay it to a central data center where it will be processed, analyzed, and used for predictive modeling. This setup aims to enhance our application by providing users with tailored content based on their engagement and interest levels.

I’m currently using the Tobii Stream Engine API to collect data, but I’m curious about the best practices for transmitting this data securely to a remote server. Has anyone here managed eye-tracking data collection and integration within a large-scale environment like a data center? Specifically, I’m looking for insights on:

1. Data transfer protocols: Which protocols are recommended to ensure data security and minimal latency for real-time applications?

2. Data storage and processing: For continuous eye-tracking data, what data storage solutions would be ideal in a data center, especially when prioritizing performance and scalability?

3. Compliance with Tobii’s transparency policies: Are there specific guidelines I should follow to remain compliant with Tobii’s data transparency policies when storing user data in an external data center?

Any experiences, resources, or recommendations would be highly appreciated! Also, if there are alternative ways to handle high-volume data from Tobii’s devices in a secure, scalable way, I’d love to learn more about them.

Thank you!

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