We just made building video analytics solutions simpler from edge to cloud with a new Azure IoT Central application template. This application template integrates Azure Live Video analytics video inferencing pipeline and OpenVINO™ AI Inference server by Intel® to build an end to end solution in a few hrs.
The number of IP cameras is projected to reach 1 billion (globally) by 2021. Traditionally, these types of cameras are used for security and surveillance. With the advent of video AI, businesses increasingly want to use their cameras to extract insights that help improve their profitability and automate (or semi-automate) their business processes. Such video analytics applied to live video streams help businesses react to real-time events and derive new business insights by observing trends over time.
Building a video analytics solution involves multiple complicated phases. This is relatively elaborate instrumentation that requires significant technical expertise and time. These solutions typically start with setting up new cameras or leveraging existing IP cameras for video traffic. IP cameras are versatile devices that support comprehensive configuration and management based on ONVIF standards. Once the IP cameras are set up, you need to ingest the video feeds, process the video, and prepare frames for analysis using inference servers that use specific AI models. These inference servers must be highly performant so that the solution can scale to dozens of cameras at any facility. The results from video analytics need to be collected and stored along with the relevant video for business applications to consume.
Using the new Azure IoT Central application template you can design, define, deploy, scale, and manage a live video analytics solution within hours. Video analytics template supports object and motion detection scenarios with key value propositions, as shown in the following illustration.
Figure 1. Customer & Partner value proposition from Video Analytics – Object and Motion detection app template
In our mission to democratize video analytics, Microsoft and Intel collaborated to build end-to-end video analytics solutions using IoT Central. These solutions leverage:
The IoT Central application template brings the goodness of Azure IoT Central, Live Video Analytics, and Intel components integration to enable building scalable solutions in a few hrs. as described in tutorials
Figure 2. Block diagram of Video Analytics - Object and Motion Detection app template
The app template stitches the following components,
The IoT Central application template natively provides device operators view for object and motion detection scenarios, as shown in the following illustration.
Figure 3. Dashboard from IoT Central template for Video Analytics - Object & Motion Detection
The dashboard in the new Video Analytics – Object & Motion Detection template for IoT Central is shown above. The template requires,
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