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In the last article in this series, we looked at why integrated monitoring is a necessity in modern broadcast IP workflows. In this article, we dig deeper to understand what is new in IP monitoring and how this integrates with traditional workflows.
Television ratings service Nielsen recently released a report that showed streaming platforms pulled in a bigger share of viewers’ time then broadcast networks did. In fact, Netflix and YouTube alone now make up about 12 percent of the time Americans spend in front of their TVs.
The basic goal is for consumers of video services to be highly engaged. It is easy to say but hard to do. Yet it is at the core of being a D2C streamer. D2C requires a deep understanding of the end customer’s satisfaction. But rather than this understanding relating only to the content itself, at which Broadcasters have excelled for many decades, a D2C streaming service requires an understanding of satisfaction with the service – the quality of it, the ease of use, the style of use – which requires the right technology and a focused information-gathering approach. What should be done to achieve this all-important outcome?
Optimization gained from transitioning to the cloud isn’t just about saving money, it also embraces improving reliability, enhancing agility and responsiveness, and providing better visibility into overall operations.
Video, audio and metadata monitoring in the IP domain requires different parameter checking than is typically available from the mainstream monitoring tools found in IT. The contents of the data payload is less predictable and packet distribution more tightly defined leading to the need to use specialist media stream centric monitoring tools.
Doug Deems had 25 years of experience under his belt as a monitor engineer, touring the world with some of the biggest music artists in the U.S., when he became a live broadcast sports A1. “I’m surprised there aren’t more monitor engineers, specifically, that come over to broadcast sports,” he says. “Because there is a lot in common.”
More than 52% of survey participants report at least three-second latency delays or more in their live streaming broadcasts.
As artificial intelligence (AI) continues to invade the video production space, and more specifically the unmanned robotic camera studio, the addition of automated shot correction/facial tracking and recognition software technology is helping to computerize tasks previously performed by a human operator in the control room and making life easier for everyone involved.