Later on in the DNN anomaly detection project we had the opportunity to temporarily integrate our A.I. technology into a Barco control-room product called OpSpace that would be demoed at the 2018 ISE Expo. The OpSpace system contained a subsystem called the EDP Analytics Service (EAS) which used a graphical IoT builder call Node-RED.
Docker description TBD...
Experiences using this skill are shown below:
During greater part of 2017 and 2018, our team was doing research in Deep Neural Net (DNN) anomaly detection. The problem we were looking to solve was that control centers usually had far too many surveillance video cameras and control panels to monitor and not enough personal to pay attention to them all. Why not apply machine-learning (ML) anomaly detection on camera and computer monitor feeds to alert control center personal of abnormal events as soon as they occur?
By 2019, our machine-learning research project was now integrating and managing multiple cameras and video sources and as a result it was becoming increasingly difficult to configure using config. files only. I was given the task of creating a professional-looking desktop UI that could be accessed from a web browser on company locked-down PCs. It was decided that there would be no support for mobile devices and the GUI would be package as a Docker image.
Created several proof-of-concept webapps in 2017 experimenting with ideas that will make virtual meetings more immersive. Our approach was largely inspired by the Star Wars™ films. If you remember, the Jedi Council held meetings in which remote participants were sitting in seats using holographic projections of themselves and vs. versa. I prototyped the same two-way immersive meeting idea using WebGL 3-D and WebRTC in web browsers.
Developed several browser-based video playback and video device management applications. Some examples (in reverse chronological order):