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Pivot3 2020 Predictions: We'll start harnessing the power of video computing data

VMblog Predictions 2020 

Industry executives and experts share their predictions for 2020.  Read them in this 12th annual series exclusive.

By Bruce Milne, Chief Marketing Officer, Pivot3

We'll start harnessing the power of video computing data

If it feels like we're at the dawn of the Big Data Era, well, that's because we are. Businesses are collecting more data every day than they used to collect in a year. We use this data for everything from customer profiling to planning product roadmaps, from targeting marketing campaigns to predicting equipment maintenance intervals-well, just about everything. But if this is truly the Big Data Era, why are most companies leaving sixty percent of that data sitting in their data centers, untouched?

The reason is that this "idle data" is in non-traditional formats like video, streaming data, and IoT data feeds of all descriptions. Sixty percent sounds like a lot to be doing little more than taking up space, but it's also probably a conservative number. Video data is necessarily large, of course, and the higher quality or resolution of the stream, the more storage it requires. But why store so much of it if we never use it?

In 2020, I predict companies will start to recognize streaming media as a strategic asset, and to leverage the power of the video data they are sitting on. But a few other things will have to change over the next year to realize this potential.

We'll begin to see this mega-data as an asset, rather than a liability

I often hear data is a company's biggest asset, so why do most of us treat it like a liability? In retail, video data is captured for both loss prevention and to limit liability in case of in-store incidents. Other businesses monitor facility access and use video to aid investigation of breaches. In smart cities and on campuses, the goal is safety, prevention of crime, and investigation, sometimes in real-time, often after the fact. While the reasons vary from one industry to another, most businesses still view retaining all that data as a necessary evil-a liability, expense and inconvenience rather than an asset.

Next year, organizations will start waking up to the many advantages to be gained from mining that information. Uncovering trends in data coming from IoT sensors. Tracking the number people riding an elevator every day, the time of day, and even their collective weight! Identifying faces of people entering and exiting secure areas. Whatever the industry or application, we'll starting seeing that analyzing this massive collection of idle data can provide insights into preventing crimes, optimizing public transportation, and any number of other actions-insights that can make a building, a city, or a transportation system more appealing for the people who visit, live, and work in and around them.

Companies will recognize and start applying the power of this data

When companies start realizing the potential of applying the video data and analytics, what will they find that applies to them? I believe they'll go beyond thinking of abstract what-ifs and come up with concrete applications for their industries and realize competitive advantages. What types of solutions might these be?

A transit system could use video-based data to optimize its operations, rather than just reviewing it when something bad happens. What if they could calculate, based on empiricism, how many trains to send and on what schedule to match the patterns of need? Video-based computing can count heads on the platforms, in vehicles, and in stations to see where overcrowding (or under-crowding) occurs, enabling route and capacity optimization. This is a marked improvement from turnstile counting, which may not specify train, track or route, or even direction of travel, of the passengers.

What about smart video-enabled parking garages? Video surveillance is currently used extensively for security in these facilities in malls and airports, but with computer vision, garages can self-identify and highlight open parking spots, or help you locate your lost car.

Retail stores use video surveillance data for loss prevention, yet it might also be used in real time to prevent shrinkage-stock loss-before it happens. For example, the labor savings of grocery self-checkout lanes becomes a shrinkage liability when shoppers forget about items in the bottom of their cart. Video-based computing could eliminate this situation in real time, without requiring additional staff to monitor the self-checkout lanes.

To take that example one step further-perhaps beyond 2020-computer vision could eliminate the need for the checkout counter entirely. When a shopper puts an item into their cart, cameras could look at the shopper's face and the product and add it to the shopper's account, charging them as they leave the store. Futuristic, perhaps, but it demonstrates how video-based computing can rapidly create opportunities for new business services, conveniences, and lifestyle improvements. Pilots of this sort of technology are already in use.

These are just a few ideas that will help businesses differentiate themselves by leveraging the video data they're already capturing but aren't really using.

Companies will wrestle with the ethical responsibilities of using this data

With all the recent concerns over misuse of technologies like facial recognition, I expect privacy concerns to become more profound and contentious. As companies explore new ways to use video data-even if the goal is ultimately to benefit the end user-they'll also have to develop internal rules and policies on how it will and will not be used. We already intuit the types of advertisements to display to Internet users based on web search history and patterns; some appreciate the convenience, while others see it as an invasion of privacy. When we add video-based computing and IoT into the mix, more concerns are bound to arise issues about how we collect and use that data.

As more cameras and IoT devices are deployed in 2020, we'll see enormous public and policy pressure to define standards about how video data is collected, how it is used, and where and how long it is stored. If you can tie data back to a location, an IP address, a time, a person's face, their phone's IMEI... at what point does it become personally identifiable information (PII)? If data exists to piece together everything a person does in a day, does that person have a say in how private that information remains?

Social mores on the topic of privacy in the Big Data Era will continue to evolve, and innovative new uses of video and IoT data are not exempt. There's an emerging collective unease with how Facebook uses the personal data it collects. As computer vision, AI and analytics technologies grow over the next year, so will the debate over their use. Meanwhile, until more standards are defined, we who apply technologies like video-based computing to better the world will need to define and communicate the guidelines we believe customers need to understand and adopt in order to maintain ethical and moral standards.


About the Author

Bruce Milne, Chief Marketing Officer, Pivot3

Bruce Milne 

Bruce Milne is a visionary technology executive and Chief Marketing Officer at Pivot3, where he leads the company's growth in emerging markets that are ripe for transformation with IoT and smart technologies. With more than 20 years of experience, Bruce has played an instrumental role in establishing a vision and executing a go-to-market strategy for software companies that include Socialware, Hyperformix, and OpenText (formerly Vignette).

Published Friday, December 13, 2019 7:40 AM by David Marshall
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