PHOENIX—ATSC 3.0 data-streaming-as-a-service provider PEAK3 and HotEdge, a commercial and residential building automation company, have partnered on integrating the former’s 3.0 data delivery technology with the latter’s roof ice-melt systems, making it possible for building owners to reduce costs and remotely control and monitor their systems.

Field trials in Seattle and Salt Lake City are scheduled to begin this month with the goal of launching production and rollout in June, the company said.

“ATSC 3.0 is optimized to support highly flexible Distributed Transmission System (‘DTS’) network architectures, which will dramatically improve signal reception in indoor and outdoor environments, including small portable devices and mobile receivers,” PEAK3 CEO Alp Sezen said.

“The protocols implemented in the new broadcast standard are very similar to those used in 5G cellular networks but optimized to broadcast over a much larger area,“ Sezen said. “This capability uses the robust nature of ATSC 3.0 transmissions and the one signal to many receivers [one-to-many] feature of broadcast TV to cover a very large geographic area. Because of the higher transmission power levels, this DTA [Digital Transport Adapter] broadcast delivery method requires fewer transmission sites compared to traditional cellular network base stations.”

ATSC 3.0 merges Internet Protocol (IP}-based data transmission with over-the-air broadcasting opening up new data pathway applications for broadcasting in multiple markets. Some include data delivery to vehicles and content distribution network offload, the company said.

The integration of PEAK3’s ATSC 3.0 data-delivery technology with HotEdge’s roof ice-melt systems will give building owners real-time data on energy consumption, ice dam prevention and system performance to optimize energy use and enhance safety, it said.

Key optimizations delivered to the HotEdge Network devices include software updates, daily weather reports and local utility command-control access, it said.

Straits Research valued the U.S. smart-building automation market at $33 billion as of 2023 and $92 billion worldwide. By 2032, it is projected to grow to $247 billion globally, driven by demand for energy-efficient systems, advancement in Internet of Things (IoT) devices and technologies, growth in sustainability efforts and advanced analytics and AI integration to optimize building. PEAK3 will pursue this market using ATSC 3.0’s value proposition, it said.

“HotEdge is committed to providing innovative solutions that enhance safety and efficiency for homeowners,” Harrison Stadnik, vice president of strategic partnerships at HotEdge, said. “Our partnership with PEAK3 allows us to take our commitment to the next level by integrating advanced data broadcasting capabilities into our roof ice-melt systems. This collaboration will provide homeowners with unparalleled insights into their system's performance, enabling them to make informed decisions about energy usage and ice dam prevention.”

More information is available on the Peak3 and HotEdge websites.

NEEDHAM, Mass.—New data suggests that worldwide spending on the Internet of Things (IoT) is continuing to see rapid growth, with IoT spending set to jump by 10.6% in 2023 to $805.7 billion in 2023, according to a new International Data Corporation (IDC) Worldwide Internet of Things Spending Guide. 

Investments in the IoT ecosystem are expected to surpass $1 trillion in 2026 with a compound annual growth rate (CAGR) of 10.4% over the 2023-2027 forecast period.

"The last few years have shown that connecting with a digital infrastructure is no longer a luxury, but a necessity," said Carlos M. González, research manager for the Internet of Things at IDC. "For organizations to excel in data-driven operations, investing in IoT projects is essential. Connecting devices to data networks to gather insight, expand operations, and increase performance are the hallmarks of executing an IoT ecosystem."

IoT investment is a key building block to supporting an increasingly digital and distributed organizational footprint and in recent years has been a focus of telco and cable operators seeking to offer smart home and security services to their broadband customers. 

The IoT Spending Guide explores spending for Video Analytics, which involved the use of of artificial intelligence (AI) and other advanced algorithms to recognize, detect and analyze live or stored video feeds in a variety of uses, including business analytics, security surveillance, and other rapidly evolving adaptations of this technology. 

Video analytics requires IP networked capable cameras to support the advanced software whether embedded in hardware or provided by third party vendors, the IDC said.

IDC expects spending on Video Analytics solutions across all industries to be more than $23.5 billion this year. Future releases of the IoT Spending Guide will include additional broadly adopted use cases, such as smart buildings.

The IDC report notes that the largest use cases, however, are for Manufacturing Operations ($73.0 billion), Production Asset Management ($68.2 billion), Inventory Intelligence ($37.6 billion), Smart Grid (Electricity) ($36.9 billion), and Supply Chain Resilience ($31.6 billion). 

The IDC added that the use cases that will experience the fastest spending growth include: Electric Vehicle Charging (30.9% CAGR), Next Generation Loss Prevention (14.5% CAGR), Agriculture Field Monitoring (13.9% CAGR), and Connected Vending and Lockers (13.8% CAGR).

From a technology perspective, IoT services will be the largest area of spending in 2023 and through the end of the forecast, accounting for nearly 40% of all IoT spending worldwide, the researchers said. 

Hardware spending is the second largest technology category, dominated by module/sensor purchases. Software will be the fastest growing technology category with a five-year CAGR of 11.0% and a focus on application and analytics software purchases.

Western Europe, the United States, and China will account for more than half of all IoT spending throughout the forecast. Although Western Europe and the United States currently have similar levels of spending, Western Europe will expand its lead with an 11.0% CAGR over the 2023-2027 forecast, compared to an 8.0% CAGR for the United States. China's IoT spending is forecast to surpass the United States by the end of the forecast due to its 13.2% CAGR.

If there is a single truth about trends in the Internet security space, it’s that every year brings more of the same. Akamai’s 2018 State of the Internet (SOTI) report looks forward to 2019 by describing ongoing patterns from the past few years, and suggests they’ll likely continue to evolve in the ways that they already have. Broadcasters, like other internet users, should continue to expect threats in the form of brute force DDoS attacks, application level attacks, credential stuffing and the theft and sale of credentials.

A more specific portfolio of threats exists for broadcasters, who are heavily invested in the Internet of Things, which are also vulnerable. A recent Gartner report estimates that by 2020 there will be over 26 billion connected devices, excluding PCs, tablets, and smartphones.

[Read: Cybersecurity: What Execs Should Know]

There are a number of weaknesses in IoT devices, which make them vulnerable to hackers.

• Very little security is built into the device itself, often as an economy measure, but also because some safeguards may impede operation.

• Because of poor network segmentation, the device may be directly exposed to the web. It can act as a pivot to the internal network, opening up a backdoor to let criminals in.

• Developers of IoT devices sometimes leave behind code or features developed in beta that are no longer relevant. This hidden functionality can provide a way in for hackers.

• Default credentials are often hard coded. That means that the software won't force you to create a unique password. Typing “1-2-3-4-5” can get you into a surprising number of devices.

A glimpse at best practices might be gleaned by looking at the U.S. government, which introduced the Internet of Things Cybersecurity Improvement Act. It requires that any devices sold to the American government be patchable, not have any known security vulnerabilities, and allow users to change their default passwords. If you’re not working for the government, you’re on your own to figure all of this out.

Dateline 2014—at the time, the “digital universe” was growing at a phenomenal 40 percent annually and expected to continue “on into the next decade.” At the time, that growth rate reflected conglomerate sets of data that not only included people and enterprise, but included the relatively new term “Internet of Things (IoT).”

To a broadcast engineer, the term IoT used to mean “inductive output tube”—an alternative to the klystron, and both referencing transmitting tubes used in high-power TV transmitters, the latter in analog television and the former a most cost-effective device, which emerged full strength during the ATSC transition.

The modern day IoT may have equally as broad an impact for society as it did for the digital TV broadcast marketplace. The Internet of Things has propelled storage demands and solutions (including the object store) into the next universe, aiding and changing the perspective and dimensions of “big data” forever.

COMPREHENDING THE ZETTABYTE ERA

When the IDC conducted its study in 2014, they predicted the volume of unstructured data created and copied all over the world would reach 44 zettabytes (1 zettabyte = 2 to the 70th power bytes), i.e., 44 trillion GB, annually, by 2020. By perspective, just a year before that 2014 IDC prognostication, the amount of data created and stored in 2013 sat at a mere 4.4 trillion GB per year. If correct, the amount of data growth is outpacing Moore’s Law, and will increase tenfold in six years.

Ironically, according to that IDC report, the amount of useful data (if tagged and analyzed) grew by a much lesser amount. In 2013, only 22 percent of the data accumulated in the digital universe was considered “useful”—that is, it was relevant because it was meaningfully tagged or categorized and was searchable and retrievable.

By the year 2020, the IDC prediction reported in April 2014 stated that only 37 percent of the data collected will be useful because of that same criteria.

USELESS DATA RETENTION

So why do we continue to store data that isn’t useful? The simple answer: “Because we can.”

Irrespective of how, where, when or why we create this mass of data, we find that most companies, enterprises or individuals collect and save literally everything because, fundamentally, there isn’t the time to sort, catalog or even physically hit the delete key once the data is collected. On the personal level, think of how many VHS tapes or compact discs or DVDs you still have in boxes or on shelves in the basement or the attic.

Putting those collections into today’s perspective, all those memories are essentially just another set of data. If we digitized all those analog VHS tapes into compressed ones and zeros, we’d still have enormous sets of data that would likely remain unmanageable, ignored and probably lost in the digital quagmire of never-never land.

At least while in a tape format there was a storage container (the wrapper), information about the content (the metadata) and an easy methodology to catalog the content by orderly arrangements on shelves, boxes or with a 3x5 card catalog or even a digital picture of the box.

EXPONENTIAL EXPANSION

Production companies, news organizations, broadcasters all generate enormous amounts of data. The volumes continue to expand exponentially and will likely end up in the “no-where’s-land” of the digital landfill. For today, this enterprise digital repository is now an ambiguous, unknown depot that might be one of many ubiquitous “clouds”—some on premises, some in that atomic number 26 mountain place, some in a public cloud, and a lot more of it ending up in privately managed datacenters scattered around the globe.

For how long and what purpose do organizations intend to keep that data? It’s relatively inexpensive to hide those bits in a cloud and nearly zero cost to keep it there—until you want to retrieve it. However, to get meaningful use out of those bits, you needed to catalog it. Otherwise, you must pull it all down from the cloud, store it again (locally) and then search through it to find something usable.

For an enterprise of any size, this takes labor—which costs money. And that’s a resource that doesn’t grow automatically, like the data you and your friends and their friends are generating every second of the day.

INTELLIGENT DATA STORAGE

When you consider the daily couple of billion pieces of data “about” you, your friends and their friends, too, you can see the storage challenges which entities like Facebook, Google, Amazon, and the other social media or shopping platforms have on their hands. The difference is these companies have figured out how to intelligently collect the data, identifying each piece using artificial intelligence algorithms that are, incidentally, developed either by their own organization or acquired by buying another company with that expertise. Across each social group, they will cross-relationship every piece of their data and then store it in one-to-many of their “private” clouds—which are liberally dispersed data centers interconnected by networks based upon volumetric accessibility per region.

Their data is never stored just once. Instead, it is replicated multiple times for accessibility, protection and resiliency. How each organization diagnostically and dynamically protects that information and makes it nearly instantly retrievable is their secret sauce.

Yet today, some of the concepts and principles which social media companies have developed for their own applications are now becoming available to individuals and organizations. The goal in these products is to start diminishing the “uselessness” of the data by applying intelligent metadata that can then utilize more conventional search engine approaches for cataloging and retrieving those assets. These new AI-based approaches now differentiate the future from the more traditional legacy media asset management methodologies.

STRUCTURING THE UNSTRUCTURED

What we’ve learned by collecting huge sets of information about known places around the world is now supporting machine learning techniques that create accurate metadata tagged not just to a single image, but to an entire generation of data sets grouped as objects. Such information may use the angle of a shadow which then identifies a time of day, which, when coupled to a geographic (GPS) location, gives more information about the season or the atmospheric conditions. People in images can now be related to their siblings or parents, based upon data sets generated from favorites or albums. Road signs, window lettering on buildings, and other distinguishing characteristics add to the databases about the actual surroundings where that image, and those of others, were collected. What was heretofore considered useless information is now branded and repurposed by machines which “look” for this data and then catalog it without any direct human intervention.

Using these new autonomous techniques, every time a new piece of content (still image, sound or video) enters a system equipped with these technologies, the system turns that previously “unstructured” data into “structured” data that is then cataloged not just as a single image, but as collections of data sets bound into a global storage platform.

These are the roots of where we’re headed as the future of storage becomes an indirect, unsuspecting model that makes potentially useless data valuable again, for all.

Karl Paulsen is CTO at Diversified (www.diversifiedus.com) and a SMPTE Fellow. Read more about this and other storage topics in his book “Moving Media Storage Technologies.” Contact Karl atkpaulsen@diversifiedus.com.

LAS VEGAS--At NAB Show 2018, there was plenty of talk about data, connected cars, how to use the data generated and how the data generated needs to be protected. With the proliferation of the Internet of Things (IOT), that is no small task. A Broadcast Engineering and Information Technology Conference presentation, “Hacking Everything: The Dark Side of the Internet” provided some perspective on that task.

IBM security architect Jeff Crume says “with IOT, everything is a computer. A car is not just a car; in fact it’s a computer that carries you places.” That mobile computer (a/k/a “connected car”) contains data on listening, location, and a portal to control vehicle systems. “We have cars on the road today that have twice the amount of code in them, that are in (computer) operating systems.” He raised another point about information security: “All computers can be hacked. If they’re operational, and you give someone enough time, there will be a way to break into it (the computer or device).”

[Read: Akamai: Rise Of IoT Devices Causes Some Security Concerns]

As an example, he mentioned how connected DVR, players and other devices like pacemakers, insulin pumps, even airplanes have had the potential to be hacked. “The way you go in and make changes to these devices, and they have to be changed over time, is through a wireless connection. That means the “good guys” can install patches wirelessly and there remains the potential that the “bad guys” can install patches wirelessly as well, and what they would patch with is not the same thing.”

Crume said “I’m not saying this to be an alarmist; I say this so we get people’s attention and will start working on the problem.”

This article originally appeared in Radio World. 

CAMBRIDGE, MASS.—The Internet of Things (IoT) is a development that looks to connect the internet into everyday devices and a key part of many industries plans moving forward. However, while it is still in its early stages, its susceptibility to distributed denial of service (DDoS) attacks remains a concern. This was among the findings of Akamai’s Q4 2016 “State of the Internet/Security Report.”

While Akamai did highlight that the number of attacks were lower than expected in relation to the 2016 holiday season, IoT devices were a big source of the DDoS attacks that did occur. Akamai attributed most of the attacks to Mirai, and IoT-based botnet, though a pair of other IoT-based botnets also caused some issues. The growth of IoT devices, Akamai reports, is expanding the pool of attack resources. “As vulnerable devices are added to IoT-based botnets, we expect a second surge in botnet capabilities and DDoS attack size,” per the report.

The report also found that DDoS attacks greater than 300 Gbps are becoming more common. Seven DDoS attacks of more than 300 Gbps occurred in 2016, including three in the fourth quarter; the largest was a 517 Gbps attack from the Spike DDoS toolkit. However, none of these attacks were IoT-based, as Akamai indicates that the more botnets that develop for IoT-based attacks, the less availability they will have for resources.

Still, Akamai expects that the attacks caused by IoT-based botnets like Mirai are more likely to increase in the short term. “The Internet of Things is in its infancy, and device security is only starting to bubble up in the consciousness of IoT developers, the companies that employ them, and governments,” the report wrote. “We expect to see many more vulnerable and compromised devices before devices become more secure. The good news is that there are significant reasons for companies to invest in security in the future.”

Visit Akamai to read the full report.