Last year we launched the preview of Live Video Analytics (LVA) to enable you to build video analytics solutions at the edge. Based on feedback from several of you we worked on enhancing LVA and are pleased to announce the availability of Azure Video Analyzer as an Azure Applied AI Service. As an Azure Applied AI service, AVA provides a platform for solution builders to build human centric semi-autonomous business environments with video analytics. AVA enables businesses to reduce the cost of their business operations using existing video cameras that are already deployed in their business environments.
Many businesses take a manual approach to monitoring mundane business operations. This is prone to a higher degree of error and miss-rate due to human error and the fact that assessing the criticality of a visual event sometimes requires corelating multiple signals in real-time. AVA, in conjunction with other Azure services, addresses this challenge by providing a mechanism for businesses to automate mundane visual observations of operations and enable employees to focus on the critical tasks at hand.
AVA is a hybrid service spanning the edge and the cloud. The edge component of AVA is available via the Azure marketplace and is referred to as “Azure Video Analyzer Edge,” and it can be used on any X64 or ARM 64 Linux device. AVA Edge enables capturing live video from any RTSP enabled video sensor, analysis of live video using AI of choice, and publishing of results to edge or cloud applications. AVA Cloud Service is a managed cloud platform that offers REST APIs for secure management of AVA Edge module and video management functionality. This provides flexibility to build video analytics enabled IoT applications that can be operated locally from within a business environment as well as from a centralized remote corporate location.
AVA can be used with Microsoft provided AI services such as Cognitive Service Custom Vision and Spatial Analysis as well as AI services provided by companies such as Intel. It is also possible to build and integrate a custom AI service that incorporates open-source custom AI models. Business logic that corelates AI insights from AVA with signals from other IoT sensors can be integrated to drive custom business workflows.
AVA has been used by companies such as DOW Inc., Lufthansa CityLine, and Telstra to solve problems such as chemical leak detection, optimizing aircraft turn-around, and traffic analytics. AVA has enabled DOW get closer than ever to reaching their safety goal of zero safety-related incidents. In the case of Lufthansa CityLine, AVA has enabled human coordinators to make better data-driven decisions to reduce aircraft turnaround time, thus reducing costs and improving customer satisfaction significantly. Telstra has been able to unlock new 5G business opportunities with the combination of Azure Video Analyzer, Azure Percept, and Azure Stack Edge.
AVA offers all capabilities that were available in LVA and more. A short summary of some of the prominent capabilities are as follows:
AVA Edge can be deployed on any Azure IoT Edge enabled X64 or AMD64 Linux device. Live video from existing cameras can be directed to AVA and processed on the edge device within the business environment’s network. In turn, this provides organizations with a solution that considers limited bandwidth and potential internet connectivity issues, all while maintaining the privacy of their environments.
As mentioned earlier, AVA can be integrated with Microsoft provided AI or with AI that is custom built to solve a niche problem, such as Intel’s OpenVINO™ DL Streamer that provides capabilities such as detecting objects (a person, a vehicle, or a bike), object classification (vehicle attributions) and object tracking (person, vehicle and bike).
In addition to the existing building blocks provided by LVA, the current release of AVA enables a variety of live video workflows via new building blocks such as Object Tracker, Line Crossing, Cognitive Services extension processor and Video Sink.
AVA provides a video playback widget which simplifies app development with a secure video player and enables visualization of AI metadata overlaid on video.
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