As IP-based workflows become more common, AV systems are becoming increasingly interconnected, creating new challenges for organizations managing multiple video sources across their operations.
Parker Group recently launched AVenue StreamPortal, a platform designed to synchronize video sources and bring different feeds together within a single workflow. We spoke with Ray May, CTO; Chase May, Lead Engineer; and Valerie Parker, CEO, about the technology behind synchronized video management, the challenges organizations are navigating, and what’s ahead for the industry.
Organizations are generating more video than ever before. From your perspective, how have customer expectations for video management changed over the past few years?
Valerie Parker: We're seeing a massive volume of information, especially now with the advent of AI and the growing need for greater storage. But it’s not just about having more information — it’s about how you differentiate that information and funnel it into the right channels. Having volumes and volumes of data is not enough; the challenge is creating a clearer, more connected view of that information.
The human brain can’t process the sheer amount of data coming in, even when it’s visual. Whether it’s 20 or 50 channels of video, audio or static screens, one of the biggest changes I’ve seen is that people are struggling to manage that volume of information. More importantly, the focus is on how to turn that data into intelligent, real-time insights that help support situational awareness and better decision-making.
What does synchronized video management mean from a technical standpoint, and why has it become so important in IP-based AV environments?
Ray May: It's 2026, but we're still using terms like convergence. There's been a big convergence between information technology and audiovisual technology. They now ride on the same network. You've got AV over IP, voice over IP, and audio over IP. Everything is riding on the same network, so that convergence has to be managed properly.
When you're talking about security operations centers, utility operations centers, traffic operations centers, or any operational environment, you'll often have multiple networks generating computer imagery and displays, not just IP cameras. What we like to do is separate what we call the control plane from the situational awareness plane. One network is generating all of that imagery and data, while another IP network is managing the audiovisual information itself.
Going back to what Valerie was saying, customer expectations around video management have changed because there's now an incredible amount of situational awareness information available. In these environments, you're constantly deciding what needs to be displayed on a video wall or in front of an operator. If you try to show everything, you can actually create situational blindness because there's simply too much information. The focus has shifted toward refining what gets displayed over time.
Loading...
What are some of the biggest technical hurdles behind capturing, synchronizing, and replaying multiple video streams accurately and reliably?
Ray May: One of the biggest is integrating all of those video sources. Ideally, everything would be on the same IP network, but that's not always the case. When you have disparate IP networks managing those audiovisual feeds, and you're trying to tie them together, you run into firewall challenges, protocol challenges, and streaming protocol challenges. There's really no system that can federate all of those into one network.
Valerie Parker: You also have budgetary challenges. Many organizations have legacy equipment, and the global environment has made budgets very constrained. One of the biggest challenges is figuring out how to take a ratcheted approach, or a stair-step approach, to upgrading technology over six months, a year, or two years, while still maintaining the equipment you've already invested in. That capital investment has been huge for many organizations.
As organizations manage more cameras, higher resolutions, and larger volumes of video, what technical considerations have become most important when designing reliable video management systems?
Chase May: From an AV-over-IP standpoint, I'm an integrator, so one of the biggest considerations is making sure security is happy, IT is happy, and the stakeholders are happy. There are a lot of different teams that have to become cohesive and work together. You also have bandwidth planning. You're dealing with a lot of multicast traffic in AV over IP, so you have to fine-tune things like IGMP and Precision Time Protocol (PTP) to make sure all of your devices are synchronized. Then you have codec compatibility and making sure everything works together.
Valerie Parker: I'd add storage to that. What do we keep? Where do we store it? How much does it cost?
Ray May: It also depends on the application. Are you doing analysis? Are you doing forensics? Is it for training? Compliance? Post-incident review? There are a lot of different considerations when you talk about storage and the proper amount of storage that you need for all of those different use cases. Because it is requirements-driven.
Chase May: Storage has a lot more to it than just saying, "I need a terabyte." You also need the speed that storage can be written to. You need the performance capability behind it. All of those things become very important.
Looking ahead, what trends do you think will have the biggest impact on the future of video management over the next five years?
Ray May: No doubt AI. There's no doubt about that. AI is already making its way into operations centers and control environments. There have been some challenges because people are starting to lean on it too much without keeping the human in the loop. You can get false positives, and sometimes AI gives you a narrative that isn't necessarily the correct answer or the correct action. I think AI will get there. It really will. But it's going to take a team effort. Organizations are going to need people writing the algorithms and prompts that support their standard operating procedures in these operations centers.
Valerie Parker: It's the difference between truth data and perceived truth. When you're talking about prompts and AI, it's really an age-old problem. What goes in comes out. AI is so advanced in many ways, but it’s only learning from what we’re feeding it. There's an opportunity for AV in terms of creating learning models for AI because you can control the input going into those learning models.
Ray May: People are using AI to screen video to look for things like, “Is there a suitcase that was left behind?” or “Is there an object on the screen that you can identify?” — that kind of thing. But AI can also be used to manage the traffic itself.
Instead of operators managing video management tasks, AI can take over some of those routine activities. There's a lot of operator fatigue in control room environments. I always say people working in those rooms for eight hours a day are having the worst eight hours of their day. It's our job as pro AV engineers to make that environment better, and I think AI can definitely help with that.
Is there anything we haven't discussed about synchronized video management or the future of IP-based AV workflows that you think readers should understand?
Ray May: I want to go back to something I mentioned earlier. There are all these different video sources out there, whether it's IP cameras, desktop video, static video, or other devices. Right now, there aren't many products like ours that can federate all of those under one simple system.
We don't care whether it's a camera feed, a Windows desktop, a laptop, a Linux feed, a control system, or SCADA in a utility environment. We can aggregate all of those feeds, regardless of the streaming protocol, synchronize them, timestamp them using Precision Time Protocol, record them, and then play them back either as a subset or all together — whatever the customer needs to recreate that event for their use case.
Valerie Parker: It's really a little bit of a data fusion element. The ability to federate all of those different sources into one view is powerful. Then, going back to what Ray said about AI, once you have that federated view, AI can look across all of those disparate feeds and help identify events that might be critical.