Intelligent monitoring

How can we maintain flawless multi-channel broadcasting and multi-platform streaming without giving operators information overload? Monitoring by exception is widely accepted as a vital capability. But to gain all its benefits, the monitoring system needs to interpret more than just the hardware and software error messages. It needs to understand what is passing through the system, too.

Greater playout suite complexity, driven by multi-channel, multi-platform broadcasting, is forcing operators to concentrate on many more delivery channels than ever before. Even with the stability of modern playout systems, and the ability to filter error messages so that only the most urgent are presented, operators still can suffer from information overload. In the many-channel era, status reports will continue to proliferate, and as a result, operators could become blind to the critical messages.

Monitoring by exception aims to reduce the number of status reports, and only notify the operator when something needs attention. This technique is potentially transformative in the complex operating environment of modern broadcast studios; it also needs a dedicated system to collect comprehensive information on hardware, software, playlists, and signals.

After it is collected, all of that disparate information then needs to be processed and consolidated into customised graphic displays. User-configurable logic will present the messages in a coherent and operationally-relevant way. It will also assist the operator in figuring out what to do about an error message, and where to start looking for the root of the problem.

To be really useful, the monitoring by exception system should be capable of looking at the content and the playlists. Advanced algorithms can be applied to monitor visual impairments, for instance, so problems that previously needed the human eye can now be spotted by machine.

A good example is the “still-ish” picture. It is relatively easy to detect a frozen picture, with no movement. But what if that picture is frozen between two fields so is juddering? Or if the frozen picture has a moving logo keyed downstream? In both cases a simple frozen picture detector would not spot it.

There will also be cases when false error conditions are reported because the context of the broadcast content is not known by the monitoring system. But if you allow it to access and interpret key information from the schedule you bring new levels of sophisticated filtering.

Schedule-aware monitoring can be used to interpret some errors. Most obviously, the closing seconds of a programme may well cause “black” and “frozen” alarms, when in fact these are just parts of the credits sequence. So you could set rules which change the standard parameters for black and frozen warnings in the last minute of a programme.

Similarly, schedule-aware monitoring could check that the right content is being shown, by comparing channel outputs with a bank of reference signatures as well as ensuring that the content is present and unimpaired along the transmission and distribution paths. Traditionally, this has been too slow to provide viable results, but new technologies – such as Snell’s Media Biometrics – are sufficiently agile and robust to be applied to a wide variety of applications.

Playout automation continues to evolve, including channel in a box and channel without a box (software playout on virtual machines), making facilities delivering hundreds of simultaneous streams the norm. Alongside it, true intelligent monitoring is developing to provide a practical way of maintaining accurate, seamless and flawless playout.

Robert Rowe is managing director, Live TV, Snell

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