Interra Systems will showcase new versions of its Orion monitoring and Baton QC platforms at the 2025 NAB Show, April 6-9 in Las Vegas.

The company will talk about new advances to its end-to-end video quality monitoring, content-aware quality control, advanced captioning, and in-depth video analysis tools. Harnessing the latest technologies, Interra Systems’ cutting-edge solutions enhance accuracy and efficiency, set new standards in QC and monitoring performance, and empower customers to optimize their workflows for peak video quality, the company said.

“We’ll be commemorating our 25-year anniversary at NAB 2025, where we'll present our latest innovations that enhance every aspect of media workflows,” said Anupama Anantharaman, vice president of product management at Interra Systems. “Our high-density, scalable solutions set industry benchmarks in media QC and monitoring, while our AI-driven tools demonstrate why global leaders in broadcasting and service provision rely on us to streamline workflows and deliver high-quality content faster."

Interra Systems will spotlight the Orion suite's latest capabilities, including a state-of-the-art multiviewer feature that transforms monitoring by enabling real-time visualization of multiple video and audio streams. This tool not only ensures seamless quality control and efficient workflow management but also allows operators to quickly verify alerts and resolve issues, thereby maintaining high broadcast integrity with greater accuracy and efficiency.

Alongside the multiviewer, Orion-OTT offers real-time monitoring of both linear and IP-based infrastructures and a comprehensive monitoring solution for live and VOD assets. Designed for flexible deployment across various environments and supporting an array of formats and protocols, the solution now features industry-first, all-frame decoding and deep-dive analysis for critical channels — significantly improving video quality checks and service playback.

In addition, the Orion suite now includes support for RHEL 8.10, Rocky 8.10, Dolby Atmos, IPv6, and more. The suite also boasts end-to-end ad insertion monitoring, which enhances workflow visibility from pretranscode to edge by comparing externally supplied ad scheduling information with actual DAI markers. Updates include closed caption availability reports, enhanced QoS and QoE scoring, comprehensive DRM integration, and flexibility in deployment models.

OCM, Interra Systems’ flagship video monitoring and management solution, provides quality tracing that monitors service quality and pinpoints issues across various stages of the video workflow. New features at the 2025 NAB Show will include advanced probe management and improved user group permissions, ensuring both efficient and secure video operations.

Interra Systems will also showcase Baton 9.2, now with enhanced autoscaling, enhanced video quality checks for 4K files, and new support for video quality, such as blank bars check and CIE color gamut check. It accommodates ITU-R BT.1702 2023 PSE video flash guidelines and contains algorithm improvements in QR code, freeze frames, duplicate frames, media offline, blockiness, defective pixels, video dropout, burnt-in text, shot transition, and more.

Baton 9.2 also supports Sony 360 Reality Audio, LZW compression in TIFF files, AV1 video format, BW64 audio, 24-bit LPCM audio in an MP4 container, sidecar Dolby Vision metadata files, an integrated Whisper model for audio language identification, and more. The latest Baton release also features significant installation process improvements for enhanced usability and resilience, along with UI support for dark/light themes, a new database manager tool, and enhanced diagnostics and alerts.

Interra Systems will also demonstrate advanced new updates to its award-winning Baton Captions solution — including caption placement as per scene change guidelines to avoid burnt-in text overlap and a host of QC and correction features. All of the updates take advantage of cutting-edge machine learning, automatic speech recognition, and natural language processing technology.

A new UI layout comes with many new features, including an integrated relay workflow service; vertical zoom on audio waveform; and intelligent caption segmentation during review, which enables automatic splitting, merging, and resegmentation based on properties such as row count and character count while adhering to clause boundaries and natural pauses.

Interra Systems will also demo its Vega platform for standards compliance, debugging, and stream interoperability assurance. The platform has been enhanced to support an extensive range of compression standards, including the latest in VVC, AV1, HEVC, MV-HEVC, AVS3, HDR, Dolby Vision, Dolby Atmos, ATSC 3.0, and more.

This broad compatibility reinforces Vega's role as a critical industry tool, Interra said. The platform's comprehensive capabilities enable media professionals to navigate the complexities of various video formats and standards with ease, ensuring high-quality content delivery across different platforms and devices.

Interra Systems will be in Booth W1921 in the West Hall of the LVCC.

WASHINGTON—Like any other technology, artificial intelligence and machine learning for video production and distribution came about in an effort to build a better mousetrap. Any product that does more with less effort has an advantage over products that don’t make the leap to the latest technology—that’s why self-driving car technology is often in the news.

There is no self-driving product for the television industry… no editing device that will automatically assemble a program, no camera that will point and adjust itself perfectly without human intervention, and no transmitter or distribution chain that will perfectly adjust itself to changing conditions and signal anomalies.

In Post
Those things are coming, however. There is no way to say exactly when, but my bet is that we are closer today to amazing artificial intelligence technology in the television industry than we are to the DTV transition in 2009. (And that seems like just a couple years ago!)

Meanwhile, there are several companies pioneering artificial intelligence and machine learning products that target a range of television applications. One of those is Blackmagic Design, which has AI functions in its DaVinci Resolve editing software.

“DaVinci Resolve Studio’s Magic Mask uses the DaVinci Neural Engine to automatically create masks for an entire person, object or specific feature, such as face or arms,” said Shawn Carlson, product specialist for DaVinci Resolve at Blackmagic Design. “DaVinci Neural Engine functions in Magic Mask offers specific human feature recognition for difficult isolation needs, like hair with bangs and exposed skin on a bearded face.”

Removing an object in a video shot can be difficult, especially if there is a lot of movement. DaVinci Resolve Studio users can remove unwanted objects using a combination of Power Windows, tracking and the object removal plug-in. The DaVinci Neural Engine analyzes the shot using machine learning and AI, and determines how to remove the object from the scene. Users can adjust various settings until the object disappears.

Carlson said that the DaVinci Neural Engine is for visual elements only at this time, and does not have any role with audio.

Streaming Data
The transport of streaming data is another function that benefits from AI and machine learning. With so much data moving so quickly there is no way that human observers can watch it all and compensate as necessary—it’s the perfect job for artificial intelligence.

Zixi is one company that uses AI to monitor streaming data and provide alerts and adjustments in the event of signal degradation. “We use AI/ML in two areas: video transport and video content analysis,” said Andrew Broadstone, senior director of product management at Zixi. “Low-level protocol measurements, such as round-trip time, network congestion and retransmission rate, are used to determine link quality and to anticipate upcoming signal degradation.”

Much of what Zixi tests is the transport stream quality, but the company’s quality measurements also drill down into the video encoding to ensure image and sound quality are maintained.

“Certain kinds of content analysis are independent of codec,” Broadstone said. “We also use AI and ML to estimate the perceptual quality of live video [VMAF] without a reference, but for this the video must be H.264/AVC transport stream format. In general, our customers overwhelmingly use H.264 since it is the most compatible format across devices.”

Broadstone said that Zixi’s IDP product uses tens of measurements collected every few seconds across all participants in a video workflow to determine what the company calls its “health score.” This health score lets IDP predict signal path quality and degradation.

“Zixi Health Score is the output of multiple models trained using gradient boosting across the entire Zixi data set with many months of data,” he added. “Zixi Health Score therefore is not a simple set of rules. However, it is typical to see the Health Score drop significantly when there is a sudden change in packet round-trip time, or if raw packet loss steadily increases.”

The aim of Zixi IDP is to anticipate problems and alert operators to the root cause, Broadstone said.

Cloud-Ready Monitoring
Monitoring data streams is also at the forefront of Interra System’s ORION, a real-time software-based, cloud-ready content monitoring system that enables service providers to deliver clean video. 

ORION provides real-time monitoring of IP/SDI/SDIoIP-based infrastructures that looks at all aspects of video streams such as QoS, QoE, closed captions, ad-insertion verification, reporting and troubleshooting. 

According to Ramandeep Singh Sandhu, senior management staff member at Interra Systems, ORION performs monitoring functions on hundreds of services simultaneously from a single platform, providing an operator with a single point of visibility and access to information such as status, alerts, alarms, visible impairments, error reports and triggered captures.

What are the typical anomalies that trigger an alert in ORION? “A total signal loss condition will typically be preceded by continuity counter errors, substantial reduction in program bitrates, high network jitter and packet drops,” Sandhu said. “QoS/QoE scores computed by ORION will also show significant dips in such cases.”

Identifying On-Screen Objects
As you might imagine, web-streaming specialist Amazon Web Services uses AI/ML for a range of applications. One example gives customers flexibility and precision when identifying on-screen objects. For example, AWS’s Media2Cloud can use Amazon Rekognition AI to identify that the on-screen object is a dog or something else.

According to Alex Burkleaux and Evan Statton of AWS, Rekognition is constantly adding new names, objects, and other features it can detect. For example, if a customer requires identification of specific kinds of dogs, Rekognition’s Custom Labels can be programmed to differentiate among images of different kinds of dogs, such as “labrador,” “terrier” or “boxer.”

Of course, recognizing faces is a frequent job for AWS Rekognition, and the faces of many celebrities are already in the database. Rekognition Face Search provides a mechanism for detecting people who are not part of the Celebrity Detection data set.

Where does all this AI power come from? Is it more processor power or better programming?

“They go hand in hand,” Burkleaux and Statton said. “Processing power and data are required to build and train machine-learning models. When you’re using AWS AI Services such as Amazon Rekognition and Amazon Transcribe, this is part handled by the managed service provided by AWS.”

AI/ML products may seem almost magical at times today, but they are only going to get more capable over time. Eventually, we may get to a Siri- or Alexa-like interface where you can simply describe what you want and have the service do the heavy lifting.

For example, you might say something like, “Analyze these six video clips and identify if any of the cars in them are Chevrolets” or “Monitor this data stream and report any conditions that either exceed standard parameters or consistently get close to a fault situation.” Of course, you might have an additional conversation to ensure the AI assistant understands what you are asking—that’s understandable.

It’s hard to say if that is five or 10 years in the future. It might be shown at next year’s NAB Show.

You can be sure that change is coming, and that there will be more AI/ML in the future.

CUPERTINO, Calif.—Frequency, a provider of linear video channel cloud origination services, has deployed Interra Systems' ORION and ORION-OTT systems in an AWS cloud environment.

By using the end-to-end, cloud-based systems, Frequency can monitor TSoIP contribution feeds while assuring audio-video quality and stability across its network of hundreds of FAST channels.

"As a provider of cloud-based linear video solutions, Frequency needed a next-generation monitoring platform that was comprehensive, scalable, and had efficient troubleshooting tools," said James Miller, vice president of operations at Frequency. "Interra Systems' ORION and ORION-OTT will allow us to monitor both IP and OTT streams on the cloud, an essential requirement for us, and enable us to keep a strict eye on the quality and stability of each stream delivered, verifying ad marker quality and precision in real time.”

“We are impressed by how well Interra's engineering and support team worked with us to put together a great monitoring solution for Frequency and our customers," said Miller.

ORION monitors IP infrastructures in real time, looking at all aspects of video streams, which allows Frequency to deliver error-free, superior-quality video. With ORION and ORION-OTT, Frequency will have a unified, consistent monitoring platform for checking QoS, QoE and ad insertion verification monitoring, including STCE-35 cue message and post-insertion verification for regulatory compliance, the company said.

ORION monitors hundreds of services simultaneously from a single platform, providing Frequency with a single point of visibility and access to important information, such as status, alerts, alarms, visible impairments, error reports and triggered captures. ORION and ORION-OTT's quality checking includes macroblocking, freeze and black frames. The audio quality checks include loudness, silence and levels and support all popular audio formats, including Dolby, it said.

Frequency also uses ORION-OTT to verify QoS and QoE for ABR videos. It checks for inconsistencies related to ABR package compliance, manifest and playlist syntax, download errors and content quality, the company said.

More information is available on the Interra Systems’ website. 

At IBC2018, Interra Systems will spotlight its Baton ABR and Orion-OTT solutions for delivering high-quality streamed video. Baton ABR and Orion-OTT perform quality control and monitoring for VOD content from ingest to NOC and other distribution points. The company says visitors will be able to see how Baton ABR’s checks at pre- and post-transcode stages, along with Orion-OTT's delivery-specific checks and features, assure QoE for every stream on every device. For live-event streaming, Orion-OTT offers a platform that can monitor a large number of streams for adaptive bitrate compliance along with audio-video quality checks in real time. The solution suite also supports closed captions, ad verification/compliance and DRMs.

Interra Systems’ OTT solutions can be deployed in the cloud or on premises, providing enhanced efficiency and flexibility for any workflow. When complemented by the company’s Orion system for real-time monitoring of IP-based infrastructures, Baton ABR and Orion-OTT provide broadcasters with a total solution for streaming superior-quality services. Orion looks at all aspects of video streams, such as QoS, QoE, closed captions, ad-insertion verification, reporting, and troubleshooting.

Interra Systems also will introduce Winnow, a machine-learning-driven add-on for its Baton QC solution. Enabled by artificial intelligence, Winnow offers broadcasters a compliance solution powered by machine-learning and computer vision technologies. The company says that integrated with Baton, this enhancement can be deployed in both cloud and on-premises environments. Relying on user-defined rule sets, Winnow checks compliance and identification of content against regulations in different countries, regions and organizations.

Baton also includes support for the VAST protocol, hybrid QC workflows, as well as enhanced support for HDR content and audio language-detection capabilities.

Demonstrations will be held in the Interra Systems’ Stand 7.C09. The IBC2018 show is Sept. 13–18, in Amsterdam. For more information or to register, visit www.ibc.org.

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