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Educational Datacasting and ATSC 3.0 Deployments: Major Datacasting Updates

Educational Datacasting and ATSC 3.0 Deployments: Major Datacasting Updates

In the last 24 months, it has been rewarding to watch datacasting became a driver for positive change in education and continued to show its value for emergency preparedness.

Public media and datacasting have two decades of history in experimentation, deployment, and execution – along with SpectraRep – and we are excited about what is happening right now. Here are two quick updates on educational datacasting and ATSC 3.0 deployments.

Educational Datacasting

When COVID drove funding to support remote learning, many public stations along with SpectraRep used it to assist local/state educational systems.

SpectraRep’s datacasting technology is now engaged in several states to support remote learning in households without access to reliable broadband services. Plus, feedback from teachers helped us enhance our technology workflows that will have a far-reaching impact on all datacasting services.

Here are just a few of the states enjoying success with our public media partners: Indiana, South Carolina, Tennessee, and Nevada. 

In particular, in New Mexico, Franz Joachim, New Mexico PBS GM and CEO, was just honored for his datacasting work with the Pillar of Public Service Award at the APTS Media Summit. New Mexico PBS is leading the way in ATSC 3.0 datacasting, which is powered by our EduCast™ service.

You can read all about New Mexico’s success here.

ATSC 3.0 Deployments

SpectraRep’s cloud services now support ATSC 3 datacasting. The most important part of this advancement is that deployments are seamless, not requiring any equipment at all.

We have deployments on-the-air on almost 100 public television transmitters and translators. Our deployments support reception in police and fire vehicles with improved reception not possible with ATSC 1.

Datacasting is making a difference in the communities that have it, and the future for this technology looks very positive. Please share this message with any colleagues who might also be interested in datacasting.

Want to know more? Have a datacasting question? Drop us a line at