The direct-to-consumer revolution is not only transforming the consumer experience, but it’s also transforming how content is backhauled. The rapid expansion of high-definition video and livestreaming adds to the challenge of that transition. As such, more of an emphasis will be placed on producing anywhere and lowering latency in 2024. 

The Complexity of Multicloud Environments
Cloud adoption had already been steadily climbing in the decade leading up to 2020, but during the lockdown it skyrocketed, owing in no small part to the need for remote collaboration across the media and entertainment supply chain. The benefits include tremendous flexibility, accessibility, processing power, affordable storage, and efficient collaboration on the production side, from editing to sound to animation. The advantages are great, which is why we’ll certainly see continued growth in cloud adoption in 2024, but there are associated challenges. 

The architectural complexity of multicloud environments is hard to manage. Engineers can more easily familiarize themselves with a single cloud environment, which is simpler to mold to the needs of an organization. The more technologies are incorporated, the more of an undertaking implementation becomes, leading to delays, increased costs and more troubleshooting. 

Additionally, managing a growing roster of SaaS providers has become more of a burden. As such, companies will increasingly look to partners that can offer multiple solutions on one platform as a way to reduce costs, boost productivity and streamline operations. 

The explosion of FAST Channels, IP delivery, OTT and other bandwidth-intensive advancements only complicates matters further. As a result, companies will increasingly invest in technologies and solutions that will help address those capacity challenges. Edge technology, for example, enables organizations to process and analyze data much faster, while potentially bolstering security by reducing the distance that data travels from the production to the end consumer. 

The Cybersecurity Challenge of a Decentralized Supply Chain
In 2017, hackers obtained the files of the yet-to-be-released fifth season of Netflix’s Orange is the New Black. Even though Netflix refused to comply with the ransom, the PR fiasco served as a reminder for the media and entertainment industry: Your cybersecurity is only as strong as your weakest link. 

In this case Netflix felt the experience they already provided consumers was better than what any hacker could provide. As details emerged hackers didn’t steal the files directly from Netflix. They stole it from a post-production company working on Netflix’s signature series.

The decentralized nature of the media and entertainment industry means that exposure is often interconnected. Media and entertainment companies engage with a wide variety of third-party providers, particularly on big productions, which can include special effects, animation, sound, graphics, so on and so forth. 

With so much data and intellectual property outsourced across a constellation of players, which may include smaller production studios, freelancers and other contractors, it can be difficult limiting the number of people who have access to business-critical information. Some vendors may be specialty studios that lack the resources for dedicated security personnel, which could effectively serve as a backdoor for hackers to obtain valuable data that wouldn’t have otherwise been able to get. 

The In-venue Use Case
With more valuable content on the cloud, therefore, the need for robust cybersecurity solutions has emerged as a priority for the industry—a trend that will only accelerate in the following year. While investing in threat detection and perimeter security solutions goes a long way toward mitigating risk, how these organizations structure their networks will have a big impact on security. Consider the in-venue example. 

Historically, venues have posed challenges both for venue operators and consumers with regard to internet access. Anyone who’s been to a large sporting event or concert, for example, can testify to the difficulty of accessing the internet. There’s just too many people trying to gain access at the same time—and often with highly bandwidth-intensive activities like livestreaming. Couple that with high-resolution video, interactive experiences, and broadcasting and/or livestreaming production setups on the venue side, and the bandwidth demands skyrocket. 

As a result, more and more venue operators are investing in private networks, which deliver greater capacity, speed and security. Connecting a MEC solution to the private 5G network can accommodate applications with a requirement for ultra-low latency and can provide greater support for differentiated experiences, onsite analytics and AI applications. 

Controlling data and IP in 2024
This year, media and entertainment companies will continue to invest in IP connectivity, cloud, Edge and private network solutions. They’ll continue to invest in 5G because it provides the capacity they need to process and analyze large amounts of data. Investing in capacity and speed leads to more responsive systems and applications.

Keeping more data onsite and on the Edge generally helps reduce the security risk. Media and entertainment companies will seek tighter control of their network in the face of continuing threats and industry flux.

Last year was a transformative year for content delivery, with new innovations, technological breakthroughs and exciting digital experiences emerging by the day. But don't unbuckle your seatbelt yet, because 2023 is poised to be even more fast-paced and disruptive across the entire digital ecosystem.

Not only will we see major advancements in performance, but the year will also bring new and immersive experiences, major improvements in sustainability, an increased race to monetize the edge and more.

These developments will be pivotal for CSPs and other organizations who face evolving demands and must get the most out of their existing infrastructure. Especially in today’s world, where data-rich content is placing greater pressure than ever on critical systems and the industry is quickly adapting to needs for greater bandwidth and performance.

Service Differentiation Will Come From Edge
Edge computing is growing at a CAGR of 17.8%. This growth and advancement is creating a blue ocean for innovation in latency-sensitive applications, and will play a critical role in unlocking a plethora of new use cases for greater product differentiation to attract customers’ eyeballs and serve the general public.

For instance, the ability to deliver digital experiences and instantaneous transactions is becoming a must in virtually every industry, from telemedicine to sports betting and other microtransactions.

One example can be found in sports, where many teams and leagues have already launched their own consumer apps that require instantaneous updates in real time, from rapidly updating player stats to curating highlights of a goal being scored. In healthcare, the edge could enable practitioners to better assess patients remotely, which can be especially beneficial in rural areas.

Throughput per Server Will More Than Double and Power Savings Will More Than Halve
Akin to Moore’s law, the standard for throughput per server and Gbps per Watt will increase more than twofold in 2023, accelerating new benchmarks for performance, power and savings while scaling content. This greater efficiency will pave the way for next-gen digital experiences and enable organizations to scale effortlessly around the world with a steep reduction in TCO.

Paving the way for this change will be more efficient methods and technologies for content delivery. For example, certain software stacks will help organizations optimize their caching and invalidation strategies, their load balancing and traffic routing, and more to ensure the best performance and I/O possible.

Other advancements to software optimization will factor in too. For instance, non-uniform memory access (NUMA) is gaining traction, as it allows multiple processors to use the same I/O resources and memory locally. This can provide many advantages: data can flow faster with less latency, the need for data replication can be reduced and the architecture is highly responsive and scalable.

Software Takes Center Stage for Content Delivery
Public cloud and legacy hardware that were once ‘cutting edge,’ have already become dated and a technical debt. In particular, many cloud solutions have become limiting and are no longer cost effective now that content delivery is more data intensive, and there is a greater need to get more with less infrastructure.

Rather than adding more hardware—and costs—to scale, organizations will turn to efficiently written software that is purpose-built to drive performance without new, costly infrastructure or storage space from a SaaS vendor.

As a result, efficient software will inevitably be the key enabler of scale. IT teams across the world are having to relearn how to write efficient code, and software designers are having to adopt efficiency as a core operating principle from the ground up, even before laying down a single line of code. 

2023 Will be The Year of 4K Streaming
There’s been a whole lot of talk about 4k streaming, but few have yet to actually walk the walk. In fact, in 2014, the HBO hit series “Silicon Valley” referenced using Varnish Configuration Language to scale the delivery of a viral 4k video—but little did they know this joke was years ahead of its time.

Organizations big and small have continued to struggle to deliver true 4k streams, but this is about to change. New advancements in content delivery are cutting the costs and technical complexity of delivering live 4k streams at global scale. It’s an opportunity that virtually every organization can now capitalize on, without breaking the bank. 

Consumers’ homes are already saturated with 4k TVs. With the 4k market growing at a CAGR of 21.7%, delivering flawless 4k content will be a must to stay relevant and is empowered by a reduction in TCO.

Sustainability (Not Audiences and Eyeballs) Will Fuel New Partnerships
4K programming requires 8 times more bandwidth than streaming HD. Ramp this up  to 8K programming, and it will require 100 Mbps, or 40 times more bandwidth. This can have a sizeable environmental impact, when you consider that delivering media relies on a large amount of energy and infrastructure, such as networks, data centers, end-user appliances and other technologies.

Last year, we saw countless partnerships all about gaining more users and subscribers with content (think T-Mobile and Netflix or Verizon and HBO Max). But in 2023, organizations across the streaming ecosystem will shift their attention as sustainability becomes a key focus.

This shift entails a move from the conventional idea of “price and performance” to a model of “price, performance and power consumption” as well as the resulting impact on our environment.

Organizations like the Greening of Streaming alliance have already begun this incredibly important work—helping to join global industry players in technology, media and government to address the impact of streaming on the environment and establish a common lexicon to discuss, measure and translate between streaming and climate science. 

Prepare Now to Adapt Quickly to Technology’s Changes
Optimized content delivery is becoming a competitive tool and differentiator that involves technical and business decisions alike. By understanding these trends—and capitalizing on emerging opportunities—companies can better prepare their infrastructure and set themselves apart from the competition.

These decisions will have major impacts across the digital ecosystem – whether it’s ensuring performance and speed, delivering more dynamic services, cutting costs or simply providing an unbeatable customer experience.

BASKING RIDGE, N.J.— Verizon and AWS have expanded their 5G mobile edge computing offering to more U.S. metro areas with the addition of Nashville, Tenn. and Tampa, Fla.

Launched in August 2020, the expansion means that companies now provide mobile edge computing via AWS Wavelength Zones in 19 locations in the U.S. and that 75% of the U.S. population is now within 150 miles of a Wavelength Zone. 

For consumers, being in closer proximity to the applications they use, shortens the roundtrip that data needs to travel, which in turn significantly reducing lag time, or latency, for getting data to your device from the cloud, the companies explained. 

For developers and businesses, Verizon 5G Edge and AWS Wavelength allows them to build and deploy a variety of latency-sensitive applications for such applications as immersive VR gaming, video distribution, and connected and autonomous vehicles.

“With the ongoing expansion of our mobile edge compute infrastructure, we’re enabling developers to build transformational applications that enhance consumers’ experiences by moving the data and processing done by applications and services to the edge of Verizon’s wireless network and closer to the end-user’s device,” said Tami Erwin, CEO of Verizon Business. “By offering both public and private mobile edge compute, we’re giving businesses ultimate optionality. This can transform the way companies can leverage predictive analytics, allowing them to improve operational efficiency, mitigate risk and increase revenue.”

“With the rapid expansion of AWS Wavelength Zones across the US, even more developers can innovate faster and deploy powerful cloud-based applications to the edge – offering ultra low latency, high bandwidth, and high performance for these applications,” said George Elissaios, director and general manager of AWS EC2 core product management at AWS. “We’re excited to collaborate with Verizon to bring AWS services to the edge of the Verizon 5G network across the US to help our customers transform consumer experiences.”

Verizon 5G Edge with AWS Wavelength is currently available in 19 locations including Atlanta, Boston, Charlotte, Chicago, Dallas, Denver, Detroit, Houston, Las Vegas, Los Angeles, Miami, Minneapolis, Nashville, New York City, Phoenix, the San Francisco Bay Area, Seattle, Tampa, and Washington DC. 

Verizon and AWS also offer private mobile edge computing for enterprises called Verizon 5G Edge with AWS Outposts.

Gamification is changing the rules of the game for live sports, and this is the right time for media companies and sports organizations to take notice. Gamification brings greater fan engagement and more at-scale monetization opportunities that industry players need to notice. 

Scale for live video means the number of feeds for any given event. So far, latency between the venue where the live sports takes place and the device where fans are watching the game has averaged around 30-40 seconds. 

Therefore, live content hits the consumer platform 30-40 seconds too late, severely damaging the opportunities to create deep, meaningful, and lucrative fan engagement. Increased latency has resulted from existing complex cost-prohibitive workflows relying on the cloud to do the heavy-lifting when processing live feeds. 

Edge computing for live video changes all this removing the challenges of latency in live streaming by simplifying workflows and augmenting the cloud by adding powerful processing capabilities at the point of video origin.

Edge computing at the source of live video creates a unified experience for live sports fans and betters, enabling broadcasters and sports leagues to engage their audiences consistently at scale. Live sports consumption turns from passive to active, allowing media and sports organizations to unlock more scalable monetization opportunities.

Why At-scale Ultra-low Latency is Critical for Live Video Monetization and Viewer Engagement
Live video has exploded, with streaming audiences in the U.S expected to reach 158 million in 2022. Live sports is one of the leading sectors driving this growth on several platforms. Broadcasters and sports organizations need to take advantage of live video’s exponential growth to harness monetization opportunities.

Today, we are already seeing live video platforms deliver active viewer engagement instead of the more traditional ‘passive’ linear TV viewing experiences. Live social commentary, betting, and performance tracking are examples of deeper fan engagement available at scale.

Live streaming workflows need to change to deliver compelling live sports content. The current methods of sending a live video feed to the cloud for processing create workflow complexity that increases latency and costs and degrades the video quality. 

Ultra-low latency (ULL) is critical for sports gamification as any delays will result in poorer viewing delivery and limit the fan’s immersive experience. By overcoming the latency challenge, media and sports organizations can engage fans and encourage monetization through sports gamification at-scale.

Edge Computing: Augmenting Cloud Capabilities and Driving Monetization
Research has shown that in 2022 197 million US adults will watch content on a second device while watching a digital video or traditional TV. A second screen is becoming an essential source of personalized content for audiences that can consume content on the platform they want—often in conjunction with a linear program. It creates an excellent opportunity to pioneer secondary, often lightly-produced, content, including different camera feeds or commentary options typically accompanied by on-screen statistics and graphics. These complementary options enable viewers to have a gamification experience, providing an extra layer of game insight and data analytics.  

But for this to happen, media companies need to ensure the live content reaches consumers with ultra-low latency. A video edge computing platform can revolutionize live streaming workflows, putting advanced compute capabilities and processing power on-premise, right at the source of the video, instead of relying on the cloud to do the heavy lifting. 

Changing how we package live video feeds to bypass or augment cloud functions can enable direct output of HLS and DASH in a low-latency format. The feeds can then be pushed into the CDN and delivered to viewers worldwide. These scalable workflows can be simultaneously adapted to HTTP, SRT, or WebRTC, providing the same ULL. 

A video edge computing platform also addresses the OPEX challenge, shaking up the economics of the cloud. By optimizing their dependence on the cloud, media companies can perform and complete critical processing tasks on-premise in a standards-based streaming environment. 

In addition, organizations can take advantage of edge computing’s scalability and build and deploy the functions they require —  customizing their platform to meet their business needs today and in the future. Workflows become simplified as the steps to send feeds to and from the cloud are removed from the delivery chain. 

Depending on the use case, this reduces latency dramatically to less than 3 seconds or even sub-seconds. Let’s take the example of Web RTC. Bypassing the cloud directly to a Web RTC Gateway can bring latency down to sub 1 second. Audiences get an experience of improved quality, less latency, and a unified experience across various platforms at scale. In today’s ever-competitive market, this can give video producers a much-needed edge as it delivers the fan the experience they want in a scalable and unique way. 

Harnessing Gamification and Fan Engagement with Edge Computing for Live Video
Gamification is changing how we consume live sports and opens a host of monetization opportunities for media and sports organizations — provided they resolve the critical latency challenge and achieve real-time content delivery.

A video edge computing platform revolutionizes live streaming workflows by creating powerful computing and processing capabilities on-premise, at the source of live video. Therefore, an encoder no longer needs to send live feeds to the cloud for processing before reaching a CDN. The live video delivery chain becomes shorter, simpler, and more efficient. Media companies optimize costs and deliver content to the consumer with ULL creating consistent fan engagement — and scalable monetization doors open up for live sports gamification.

We’ve only begun to scratch the surface of what gamification and consistent fan engagement can bring to the media and broadcasting industries. As the growth of live video explodes, a video edge computing platform that delivers at scale changes the realm of possibilities for media and sports organizations, bringing new viewing and at-scale monetization opportunities that we can’t afford to miss.

STATE COLLEGE, Pa.—Edge computing tech startup Videon has announced that it has raised an additional $9 million in funding, boosting the total investments in the company during the past seven months to $16.3 million.  

The funding, led by Alter Venture Partners with participation from Fortson VC, Bruce Chizen, Voyager Capital, and Cercano Management, will be used to further develop and improve its next-generation video edge computing platform, Videon said. 

Videon’s technology already powers tens of thousands of hours of live video every day for audiences across more than 19 countries. Techex, THEO Technologies, V-Nova, and Zixi are currently building and deploying applications that harness the benefits of Videon’s edge computing capabilities for their customers, the company reported. 

“Live video streaming continues to see exponential growth across everything from news and sport to security, emergency services, and corporate content, with the live streaming market estimated to be worth $4.26 billion by 2028,” said Tricia Iboshi, CEO at Videon. “For our customers, just getting live video over the internet is table-stakes and only the start of the story for what they need to achieve. We’ve spent the last 6 months working with industry leaders across the video ecosystem to unlock the potential of the edge to deliver new experiences, drive greater efficiencies, and create more opportunities for personalization and monetization. The latest funding will enable us to continue to innovate, adding more video applications, enabling disruptive workflows and driving live video at scale.”

Videon puts edge computing power at the point that video is created, enabling a huge array of video processing tasks to be completed before content goes into the cloud, the company said. This enables users to significantly reduce the complexity and cost of live production, adding multiple camera angles and remote feeds to meet growing audience expectations for personalized content.

Moving computing power to the edge where the video is created is the key to reducing latency, the company noted, and is especially vital for sports, gaming, and betting applications.

“Live streaming is exploding but it’s actually only at the first stage of its potential,” said Louis Toth, managing partner at Alter Venture Partners.  “At the moment, the economics of creating and distributing live video are restricting what content creators and media organizations are able to do. Videon is revolutionizing live video through powerful edge processing at an unrivaled price point. Videon’s video edge computing platform has huge market potential — it opens up unlimited live video use cases across sectors powered by low latency, multiple camera angles, technologies like AI and Machine Learning, and new monetization opportunities.”

FREMONT, Calif.—The Broadband Forum industry standards group has announced a new release of TR-466 that is designed to help operators bring edge computing to cloud-based broadband networks and will enable service providers to improve their customers’ quality of experience (QoE) while increasing their revenue streams.

Broadband Forum’s TR-466 ‘Metro Compute Networking: Use Cases and High Level Requirements’ is a framework defining a new metro-compute networking architecture in ways that ensure a greater user experience by moving applications or content towards the lower edge tiers in the network hierarchy, the industry group said. 

The metro-compute networking architecture will include in-depth integration of computing and network on top of the cloud-based broadband network with the purpose of connecting isolated edge sites—such as Broadband Forum’s CloudCO—as one cloud to serve edge computing services, the Forum said. 

“The latest release of TR-466 represents a big step for the industry as the standard will help cloud providers and operators overcome the routing and scalability challenges at the edge,” said Broadband Forum SDN/NFV Work Area co-director George Dobrowski. “Furthermore, it enables virtualization and disaggregation of edge elements and nodes to run applications in proximity to the customer where latency is important. This is particularly important for enterprise networks and will provide a shareable infrastructure for customers that can be seamlessly managed with reduced complexity,” 

“Our work enables faster and more efficient provisioning of low-latency and high-bandwidth edge computing services,” he continued. “TR-466 perfectly complements the Forum’s in-progress work on WT-474 subscriber session steering, which can deliver flexible on-demand bandwidth that detects traffic changes and automatically scales to preserve the user experience. This is achieved by utilizing compute-aware routing and dynamic session steering, as demonstrated at Broadband World Forum. These specifications enable operators to unlock new revenue-generating services.”

In describing the importance of the release, the Broadband Forum noted that edge computing represents a unique opportunity for operators as they already own a large number of edge sites. It will enable them to transform into an ICT service provider and adapt their business offering from bandwidth to network connection, computing and storage to deliver service information and content, not just bandwidth. For Over-The-Top (OTT) streaming, gaming, or Virtual Reality services, providers will be able to save asset investment and Operation and Maintenance (O&M) costs through edge sharing.

The Forum also noted that Metro-Compute Networking benefits have been recognized by some of the largest and innovative operators in the world with lab and additional field trials including significant activity within China, including China Mobile, China Telecom and China Unicom. In addition, IRTF is preparing a new research group, RISE, following a similar direction in Q4 2021 after the release of TR-466. These proponents consider TR-466 as a key step in helping them move towards the required ICT transformation, the group said. 

“Until now, no industry standards organization has considered the possible impact on multi-service broadband networks under the trend of edge computing or addressing the unique challenges that this has presented,” said Broadband Forum SDN/NFV Work Area co-director Bruno Cornaglia. “This latest Broadband Forum work will see us play a critical role in edge computing and utilize the virtualized network infrastructure to enable carriers to increase revenue via edge cloud services.”

The group’s free technical reports and white papers can be found at www.broadband-forum.org/. 

At this point in the technical evolution, we’re firmly in what might be called the “cloud computing era.” Yet, there is a somewhat interesting and possibly equally mysterious transition that is changing the location and the value proposition of the cloud.

Many of the new applications thought to be ideal for cloud computing may actually be occurring closer to the source of the data, that is at the “edge.”

At the personal level, many of us use products and services that are powered by intelligence that is found in the cloud. We place content in the cloud and we pull content from the cloud. These well-known products include those from Google (Chromecast), Amazon (Echo) and Apple (TV). Centralized services are familiar to many—those by Gmail, DropBox, Adobe Creative Cloud and Autodesk AutoCAD. These organizations use cloud services to store, backup, protect and interchange data and are always looking into new methods to achieve better security, decrease latency and reduce internet bandwidth traffic.

The “edge” is a relatively recent buzzword; similar in context to the cloud and the Internet of Things (IoT). Maybe “the edge” is not yet as familiar as AI and VR/AR, but it has similar importance to other technological capabilities that circle our universe and impact our lives on a daily basis. And people trust these services—we allow them to routinely collect our data and utilize it in ways that we can’t possibly manage ourselves. We let these companies “own” that data (unless you’re doing the GDRP thing), and we recognize that it’s literally impossible to halt the external/additional uses of our data due to myriad reasons, privileges or end-user-license-agreements (EULAs) that we graciously sign and accept before landing a single piece of data in their repository.

CLOUD DEPENDENCY

A significant number of companies have openly adopted the use of the cloud and rely on the hosting, machine language (ML), infrastructure and the power offered by the cloud. Nonetheless, the use of the cloud—as expected—continues to ebb and flow with the needs and capabilities of the technology ecosystem. Fundamentally, because of evolution, compute and other dependencies, we are beginning to see that certain functionalities and capabilities are now moving from the “public” cloud to what is known as “the edge.”

To see where this is headed, we start by looking at what “the edge” and “edge computing” is about. Basically, edge computing are those computational properties that are performed or “live” as close to the source or information gathering points of the data as is possible or practical.

But why do this when the cloud can do this work, probably faster and more efficiently than at the edge? There are multiple reasons and rationale for this, some influenced by technological evolution and others because the ecosystem, in whole or in part, allows this to happen.

PRIVACY

Families, institutions, enterprises, small businesses and individuals are increasingly more concerned about data privacy (and piracy). Many of you have likely had your credit card hacked at least once. While we may trust the cloud, and the firms providing the service—one can only wonder not if, but when something will be compromised.

If only the least amount and most applicable data needed is sent to the cloud service, then certain (unknown) risks might be mitigated. If only that data that absolutely needed to go to the cloud were encrypted locally, contained a biometric key and was sent over a protected channel—possibly using blockchain technologies—the user could feel better protected. To do this means that some of the compute process should be brought to the edge.

At least one major smartphone manufacturer does just that. They brought what was once only available as cloud-based computing out to the edge, creating a powerful change in how compute power is distributed.

SECURITY

We’ve heard about poorly managed IoT devices because the processing needed at the source was either absent or relegated to a location that passed through other less secure channels (e.g., the public internet) before reaching the cloud service-center destination. Today, browsers located at the edge, which have moved to the “evergreen” model, are finding success when employing edge computing principles in terms of increased security and better use of bandwidth.

“Evergreen” refers to services that are comprised of components that are always up to date. Evergreen IT encompasses services that are employed at the user level and at all the underlying infrastructures, whether localized, at the edge or in a cloud. Edge computing can help manage security by bringing only the needed information to the (public) cloud. Browser and cloud providers are working on OS and certified microcontrollers that will manage the types and depth of information that is cloud-bound.

BANDWIDTH

Proponents of edge services (for computing) believe that bandwidth can also be saved. That is, the bandwidth needed when to get every piece of data from host (user) to the cloud can be reduced if some or much of the compute efforts are done before going to the cloud. Artificial intelligence is helping to enable this. Say for example, in a camera security model, you are monitoring only one source (i.e., one camera) and carried only that full image to the cloud; there might not be much savings by edge “computing.” However, if you have several sites (i.e., multiple cameras), you could gain substantial bandwidth savings by combining the data—as smaller images from each of the individual cameras—into a single multiviewer and then transporting a single “composite” image to the cloud.

If you added AI at the edge to detect, for example, any movement—as in a motion detection security function—and only then switch the camera from one of several images on a screen to a single, full-screen size—then you’ve eliminated issues with having to continually look at every image as well as send only what is needed to the cloud for storage or other functions. Once any movement stops, the multiviewer reverts to all the cameras on a single raster. The AI function might also cache the other non-active images to a local (memory) store and hold it until reviewed by the user later.

LATENCY

Issues associated with bandwidth utilization may also be equated to minimizing latency. Major data information companies such as Google and Apple are working hard to localize the compute issues using AI to help control bandwidth and data-traffic demands. Furthermore, if you use “off-line first” techniques—i.e., you open the app on your mobile device without first connecting to the internet—then you conserve bandwidth without compromising performance.

Pay attention to these up and coming active changes when you consider IoT for your home security system or other monitoring features including thermostats, fire detection, etc. When appropriately managed, edge computing solutions aided by AI can help control security and return answers faster and more reliably.

Karl Paulsen is CTO atDiversifiedand a SMPTE Fellow. He is a frequent contributor toTV Technology, focusing on emerging technologies and workflows for the industry. Contact Karl atkpaulsen@diversifiedus.com.