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It’s a brave new world for video AI application development and consumption. The variety of video AI use cases is exploding, with the global computer vision market valued at $11.22 billion. And it’s expected only to continue to grow at a compound annual rate of 7.0% over the next couple of years.
Catalyzing this rapid growth is deep learning techniques, which are expanding the possibilities for computer vision solutions across a multitude of industries. Recent developments in this area have improved neural network architecture and training algorithms, increased the affordability of hardware to power AI algorithms, and made data more accessible across sectors.
With these technological advancements, the potential for video AI use cases is almost endless and certainly no longer limited to select industries.
It’s showing up in cities for safety detection, in the transportation industry for wrong-way detection, and even in manufacturing for defect detection. Additionally, warehouse management is becoming more streamlined than ever before with SKU counting and visual inventory management. And forensic specialists can now view the contents of a lengthy surveillance video in just a few minutes. These are just a small set of the possibilities with video AI today.
The Duality of Video AI Market Challenges
But this explosion of AI possibilities also comes with market fragmentation challenges, which are highly pertinent to developers creating these applications and the organizations that leverage them.
On the development side, developers are struggling to get their applications discovered by potential users. And on the organizational side, businesses are struggling to consume AI applications at scale.
With these #technological advancements, the potential for #VideoAI use cases is almost endless and certainly no longer limited to select industries. @awirosweb via @insightdottech
Part of the problem has been that computer vision applications have traditionally been developed by different companies focusing on niche areas with limited geographical spread. But the growing diversity of customer needs in video AI is spanning across industries, and it’s becoming harder and harder to find video AI apps to meet their specific needs.
Even if an organization does find a reputable developer with a suitable app or two, it doesn’t solve their scalability issues—making it difficult for niche app developers to justify their offering. Considering the cost of critical elements enabling video AI adoption such as network, hardware, infrastructure, and cameras, no company is going to achieve a favorable return on investment by investing in one or two siloed applications, explains Kavishwar.
“In our experience, enterprise customers seriously exploring video AI applications are aiming to purchase eight to ten apps minimum,” he explains.
Solving Computer Vision Market Fragmentation
As a result, Awiros is working to solve this market fragmentation with its software platform and operating system Awiros OS. The solution is designed to enable enterprise customers to achieve diverse insights and business outcomes from static video content and real-time camera streams.
Through its centralized marketplace Awiros AppStack, customers can source a collection of video AI apps in a quick and integrated manner, and third-party developers can access tools to build, deploy, train, scale, and manage video AI apps.
For example, when a leading global luxury car manufacturer was looking for a set of video AI apps to cater to its 14 unique use cases, it turned to Awiros. With Awiros OS, the company found a centralized way of discovering, hosting, and managing its large number of video AI apps under a single platform. And the Awiros AppStack provided them with the ability to search for existing apps that solved its immediate needs.
In just two short months, the Awiros team successfully executed the proof of concept (POC) using Awiros OS, which integrates multiple applications, websites, and servers across several geographical locations. Not only did Awiros offer video AI applications that solved for each of the customer’s use case parameters, but its application marketplace AppStack (Video 1) provided future solutions for a variety of use cases, all hosted in the same platform.
Developers and Enterprise Customers Benefit from an AI OS
One of the biggest advantages Awiros brings to customers is through eliminating camera-specific limitations and expanding the possibilities.
Enterprise customers can enjoy the freedom to choose from 60 applications currently available in the Awiros AppStack, specify a camera stream, deploy the application for whatever time is required, and automatically schedule the redeployment on other cameras. All of this enables more efficient management of resource-hungry apps and drives greater ROI, Kavishwar explains.
Developers can also benefit from a low-code environment—allowing them to bring their applications to market quickly without the hassle of containerization. Additionally, Awiros provides a platform for niche developers to create applications that are domain-specific and require localized data. This is a critical gap closure since the best trained algorithms are trained on localized data, which is often siloed itself, according to Kavishwar.
Awiros has been able to successfully deploy its operating system in a cloud, on-premises, and within hybrid environments, thanks to Intel’s help. The company is leveraging Intel hardware such as Intel® Xeon® processors for some of its most critical projects as well as the OpenVINO™ toolkit for its entire computer vision library set.
The Future of Video AI Is Bright
Despite the barriers and fragmentation of video AI development, Kavishwar expects adoption to continue to rise over the next couple of years.
“The role of camera-as-a-sensor and IoT as a technology are increasing,” he observes. “The more proliferation of these technologies leveraged in solving day-to-day problems that businesses face, the more relevant video AI will become.”
Going forward, Awiros aims to make it easier than ever to discover relevant solutions to business challenges by creating a marketplace of 1,000 video AI applications, the majority being third-party developed by 2025.
This article was edited by Christina Cardoza, Associate Editorial Director for insight.tech.