Three big IT growth areas are destined to overlap and interlink: Real time communications (RTC), Internet of Things (IoT) and Big Data. And it's with a bit of irony that hot-running WebRTC is actually the slowest piece of the puzzle when it comes to linking all the bits and pieces together when you look at all the items on the board.
WebRTC has roared into the developer and cloud spaces, offering an easy way to drop voice and video into any app running on just about any platform. There's an evolving ecosystem of service providers offering WebRTC as a service, so adding in voice and video is a matter of dropping in a few lines of code into any website or mobile app. Google, Microsoft, and Mozilla all support WebRTC within their newest browsers and it's only a matter of time before Apple catches up into the space.
The simple case for WebRTC + IoT + Big Data is in the collection of voice and video. If you have the streaming bandwidth available, WebRTC can provide an easy and quick solution for home and security monitoring. Withings Home product, available off-the-shelf at $199,boasts its video camera uses the latest in WebRTC protocols to provide smart monitoring and cloud recording, with up to 30 days of continuous video recording stored in the cloud (for an additional $19.95 per month mind you; the "basic" package only keeps a 2 day history).
Similarly, Plantronics has rolled WebRTC into its products, including headsets, to handle voice. One of its demonstrations included an integration between it and AT&T's new WebRTC APIs, so customer interactions can be rolled into the cloud for direction to the appropriate contact person and stored for future reference.
Collecting voice and video using WebRTC through IoT devices means that you can build large data sets of voice and video that can be processed and analyzed - the essence of Big Data. Conversations with call centers can be mined for insight into customer opinions, competitive intelligence, and agent performance. Video can provide data on customer reaction using facial recognition and emotion analysis, such as Microsoft's Project Oxford tools provide, and be mined more deeply to identify images providing information on product performance. For instance, a surge of pictures on Instagram or Twitter depicting a broken part or a particular type of usage could be used to improve future products.
Where RTC needs more work and examples is in the data channel arena. IBM's WebSphere Liberty and Bluemix packages are the best example of bringing together the rest of the IoT - everything that doesn't need voice or video - with WebRTC, leveraging WebRTC's ability to deliver data in real time to talk to devices and pass data. Voice and video don't have to be a part of the solution, making IBM's approach much more usable for the millions of devices that need to pass data to the cloud for action and analytics.
And the big play for RTC+IoT+Big Data (RIBD?) is in large numbers of small devices, each device collecting information, sending it back to the cloud, each piece analyzed if real time action is needed, otherwise stored and adding up to Big Data that is mined for actionable information, including consumption of resources, ways to save energy and increase efficiency, and the ability to predict when something needs maintenance and/or replacement.
IBM's Bluemix page has a couple of case studies showing how things between devices and the cloud fit together, including a smart building solution and a real-time monitoring system for high-speed race boats that can perform complex diagnostics in real time while the boat is zipping along in the ocean. We're going to see a lot more vendors than IBM and a lot more case studies in the future to make the RTC+IoT+Big Data future work successfully.