https://store-images.s-microsoft.com/image/apps.39538.1063565f-ee94-4a5f-b2e6-783346b2b327.97ae6f0d-bb88-4f49-a343-09a79beb1932.74420097-45d7-4ca8-b7d8-c9402a6eefe7
Multimodal Data Visualization Micro Service SaaS
Dace IT℠d/b/a Sense Traffic Pulse™
Multimodal Data Visualization Micro Service SaaS
Dace IT℠d/b/a Sense Traffic Pulse™
Multimodal Data Visualization Micro Service SaaS
Dace IT℠d/b/a Sense Traffic Pulse™
Multimodal Data Visualization Micro Service SaaS
Overview
This SaaS App features interoperable containerized microservices for developing and deploying optimized video analytics pipelines built using Intel® DL Streamer as inferencing backend. The pre-built container images provided by the package allow users to replace the deep learning models and pipelines used in this SaaS App with their own video files for deep learning models and pipelines referencing. This SaaS App microservices can be deployed independently or with Edge Insights for Industrial (EII) software stack to perform video analytics on the edge devices.
Video Analytics refers to transforming video streams into insights through video processing, inference, and analytics operations. It is used in a wide range of business domains such as video surveillance, healthcare, retail, entertainment and industrial. The algorithms used for video analytics perform object detection, classification, identification, counting, and tracking on the input video stream.
This Multimodal Data Visualization Micro Service SaaS visualizes the video analytics and time series analytics data using the Grafana* dashboard. The visualization microservice receives video frames via Open Edge Insights (OEI) Message Bus, WebRTC* or HTTP protocols and displays it using the dashboard, streaming multiple videos at once in the same dashboard. It can also subscribe to OEI Message Bus to receive the time series analytics data on the Grafana dashboard.
The Multimodal Data Visualization Micro Service SaaS can be used independently with Edge Video Analytics Microservice, or with the Edge Insights for Industrial (EII) microservices ecosystem.
How It Works
The Multimodal Data Visualization Microservice consists of two components packaged as Docker container images:
- Multimodal-data-visualization-streaming
- Multimodal-data-visualization
The multimodal-data-visualization-streaming container receives videos frames via HTTP, WebRTC or OEI Message Bus and streams them to a web page. The multimodal-data-visualization container, which uses Grafana*, embeds the web page in Grafana dashboard using AJAX panel to visualize the video stream in the Dashboard. It can display multiple videos in the same Grafana dashboard. Also, in addition to the videos, it can display metrics related to video analytics and time-series analytics. When the multimodal-data-visualization container starts, it loads a dashboard configuration in Grafana according to the virtualization microservice mode selected. The multimodal-data-visualization component uses Grafana service which exposes the Grafana web interface on port 3000.
The Multimodal Data Visualization Microservice can be deployed in the following three modes using an environment variable:
- Standalone mode (uses HTTP to receive the video frames)
- EVA mode (uses WebRTC to receive the video frames)
- EII mode (uses OEI Message Bus to receive the video frames)
In Standalone mode, the visualization microservices accepts video streams via HTTP and displays them on Grafana dashboard.
In EVA mode, the WebRTC framework is used to get the processed video from a microservice such as Edge Video Analytics Microservice and streams it to a web page. Edge Video Analytics Microservices sends the video frames with the inference results such as object detection bounding boxes overlaid on them. In this mode, the visualization microservice also displays video analytics metrics such as pipeline status and performance obtained by sending a REST request to the video analytics microservice.
In EII mode, the visualization microservice subscribes to the OEI Message Bus to receive the video frames and inference results and renders the video to a web page after overlaying the inference results, such as object detection bounding boxes on the video frames. In this mode, the visualization microservice also displays Time Series Dashboard for visualizing the timeseries data received from EII Message Bus from EII.
Dace IT℠with Sense Traffic Pulse Next Generation IoT Managed Services can customize the Multimodal Data Visualization Micro Service SaaS for your Use Case and we offer full-service management services and advanced infrastructure components of for secure saas cloud environments, including access, compute, development operations, monitoring, networking, security and storage.
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https://store-images.s-microsoft.com/image/apps.49452.1063565f-ee94-4a5f-b2e6-783346b2b327.97ae6f0d-bb88-4f49-a343-09a79beb1932.3f7e9d7d-ca14-44c0-a91f-154f9c9e06a7
https://store-images.s-microsoft.com/image/apps.54382.1063565f-ee94-4a5f-b2e6-783346b2b327.97ae6f0d-bb88-4f49-a343-09a79beb1932.1eac256c-4520-4194-a998-55b1fd7e5779