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Release 2025.2.0-rc1

07 Nov 20:03
@xwu2intel xwu2intel
v2025.2.0-rc1
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Release 2025.2.0-rc1 Pre-release
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avinash-palleti, saratpoluri, and 64 other contributors
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Edge AI Suites v1.2.0

25 Aug 14:26
@sys-siv-oep sys-siv-oep
v1.2.0
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Edge AI Suites

Release Overview

Edge AI Suites v1.2.0 delivers enhancements across intelligent video analytics, multimodal sensor fusion, and edge AI deployment. This release supports scalable, real-time AI solutions for smart cities, transportation, safety and security, industrial, robotics, and retail environments. Key improvements include unified sample applications, GenAI integrations, expanded hardware support, and streamlined developer experiences.

Suite-Specific Updates

Metro AI Suite

The Metro AI Suite in version 1.2.0 introduces a comprehensive set of enhancements aimed at accelerating the development and deployment of intelligent edge AI solutions for urban environments, particularly in smart city, transportation, and public safety domains. This release focuses on improving modularity, scalability, and real-time analytics capabilities through updated sample applications, SDKs, and developer tools.

Smart NVR Sample Application

  • A newly released sample application that functions as a next-generation Network Video Recorder (NVR)
  • Leverages Generative AI-powered vision analytics to enable advanced event detection, summarization, and automation
  • Reduces bandwidth and storage requirements by performing video processing and analysis directly at the edge
  • Integrates with existing video analytics pipelines such as:
    • Video Search and Summarization
    • Image-based Video Search
  • Uses Frigate, a third-party open-source NVR, as a reference implementation
  • Deployment is supported via Docker Compose on Ubuntu

Metro Vision AI App Recipe

    • Provides a unified architectural framework for building Smart Transportation applications
      • Includes curated deployment packages and improved tutorial guidance
  • Introducing the Smart Intersection sample application:
    • Combines analytics from multiple traffic cameras to create a unified intersection view
    • Enables object tracking across multiple viewpoints, motion vector analysis (e.g., speed and heading), and 3D object interaction understanding
    • Demonstrates how existing camera infrastructure can be repurposed for real-time, multi-camera scene analytics
    • Highlights a shift from traditional frame-based analysis to integrated, edge AI-driven traffic management
    • Ingests output from DL Streamer Smart Parking pipeline, which includes:
      • License Plate Recognition
      • Optical Character Recognition
      • 3D object detection using third party/commercial models from DeepScenario
  • Tutorials cover:
    • Building an AI-powered Tolling System
    • Customizing applications for specific use cases
  • Enhancements to previously released sample applications:
    • Loitering Detection
    • Smart Parking

Metro AI Suite SDK

  • A modular and comprehensive toolkit designed to accelerate development of visual AI solutions.
  • Includes updated versions of:
    • Intel® Distribution of OpenVINO Toolkit
    • DL Streamer
    • FFmpeg
    • OpenCV (with OneVPL support)
  • Refreshed documentation and tutorials.
  • New tutorial added to demonstrate running inference pipelines using DL Streamer.
  • SDK image now includes the latest version of the DL Streamer Pipeline Server.

Visual Pipeline and Platform Evaluation Tool

  • Introduces the Simple Video Structurization pipeline, a flexible and use-case-agnostic solution.
  • Supports:
    • License Plate Recognition
    • Vehicle Detection with Attribute Classification
    • Other object detection and classification tasks
  • Adaptable based on selected models
  • Adds live output support, allowing users to view real-time results directly in the UI
  • Includes new pre-trained models:
    • YOLO v8 License Plate Detector
    • PaddleOCR
    • Vehicle Attributes Recognition Barrier 0039

Edge System Qualification Tool

  • Designed for device and equipment manufacturers
  • Enables verification and benchmarking of hardware performance
  • Generates system qualification reports
  • This release includes high-priority bug fixes for improved user experience, including:
    • iGPU ID resolution
    • Media runner stability

Video Search & Summarization

  • Provides intelligent video search and summarization capabilities.
  • Supports:
    • Video Summary for longform videos
    • Agentic Video Search using a Visual Data Management System
  • Validated on Intel® AI Edge systems with:
    • Intel® Arc™ Graphics B580
    • Intel® Arc™ Graphics A770
  • Deployment supported via:
    • Helm
    • Docker Compose on Ubuntu
    • Edge Microvisor Toolkit (limited support)

Video Processing Platform (VPP)

  • Enables evaluation and optimization of video processing workflows for NVR use cases.
  • Supports a wide range of hardware platforms including:
    • Intel® Core™ 13th and 14th Gen
    • Intel® Core™ Ultra Series 1 processors
  • Addresses performance and compatibility improvements based on user feedback.

Sensor Fusion for Traffic Management

  • Adds support for multiple sensor fusion configurations:
    • 2 Camera + 1 Radar on Intel® Celeron™ Processor 7305E
    • 4 Camera + 4 Radar on Intel® Core™ Ultra 7 Processor 165H
    • 16 Camera + 4 Radar on Intel® Core™ i7-13700 with Intel® Arc™ Graphics A770/A750E

Interactive Digital Avatar Platform Blueprint

  • Now supports 2D Digital Avatars with:
    • English and Chinese language capabilities
    • Integration of QWen 2 and LLM RAG models
    • Enhanced multimodal intelligence

Visual Search Question and Answering (Q&A) Sample Application

  • Combines a multimodal search engine and a visual Q&A assistant.
  • Integrates models such as:
    • CLIP
    • CN-CLIP
    • QWen2.5-VL
  • Includes a persistent vector database for improved multimodal search and question answering.

Image-Based Video Search Sample Application

  • Includes bug fixes and component upgrades to improve stability and performance.

Manufacturing AI Suite

The Manufacturing AI Suite in version 1.2.0 delivers a robust set of tools and sample applications designed to streamline the development, deployment, and scaling of AI solutions in industrial environments. This release emphasizes configurability, real-time integration, and support for edge-native deployment scenarios, enabling developers and system integrators to build intelligent manufacturing applications with greater efficiency and precision.

HMI Augmented Worker Application

  • Introduces a new Retrieval-Augmented Generation (RAG)-enabled Human-Machine Interface (HMI) application.
  • Designed for deployment in virtualized environments, specifically for evaluation in conjunction with Edge Microvisor Toolkit.
  • Architecture includes:
    • A Windows VM hosting the HMI application
    • A watcher service that monitors the knowledge base for updates
    • A RAG pipeline running in the Linux environment, enabling dynamic response generation based on updated knowledge.
  • Optimized recipe for Intel® Core™ 13th generation CPU + virtualized setup.
  • Showcase how AI can enhance operator interfaces by integrating real-time data, contextual awareness, and intelligent assistance

Predictive Maintenance for Wind Turbines Sample Application

  • Introduces a new predictive analytics application for wind turbine anomaly detection
  • Includes time series data ingest (Telegraf), data storage (InfluxDB), analytics (Kapacitor), visualization (Grafana), and publishing (Kapacitor)

Customizable Basic Application Architecture

  • Migrate to a modular and configurable application framework tailored for common industrial use cases
  • Supports easy customization through variable configuration, allowing developers to adapt the architecture to specific deployment needs
  • Deployable through Docker and Helm charts for simplified evaluation and streamlined adoption.
    • A deployment package for Edge Management Framework (EMF) will be released alongside the future EMF 2025.2 release.
  • Supported use cases include:
    • Pallet Defect Detection (PDD): Detects structural or surface-level defects in pallets using vision-based AI
    • Weld Porosity Detection: Identifies porosity and inconsistencies in welds, improving quality assurance in metal fabrication
    • Anomaly Detection on PCB: Uses AI to detect irregularities in printed circuit boards, aiding in electronics manufacturing
    • Worker Safety: Monitors worker behavior and environment to identify safety violations or hazardous conditions
  • Added support for diverse accelerators including integrated-GPU, discrete-GPU, and NPU in addition to broad CPU support.

DL Streamer Pipeline Server Enhancements

  • The DL Streamer Pipeline Server now supports enhancements to improve interoperability with existing industrial data platforms and robotic control systems, facilitating closed-loop automation and monitoring.
    • Metadata publishing to InfluxDB, a time-series database commonly used in industrial monitoring systems
    • ROS2 publisher, enabling real-time metadata transmission to robotic systems and middleware
  • These enhancements improve interoperability with existing industrial data platforms and robotic control systems, facilitating closed-loop automation and monitoring.
  • Support MQTT trigger for image processing and inference.
  • Configurable OPCUA in REST API.

Retail AI Suite

The Retail AI Suite in version 1.2.0 introduces a set of targeted enhancements designed to support edge-native AI workloads in retail environments. This suite helps solution builders evaluate hardware configurations, optimize AI pipelines, and deploy intelligent retail applications that improve operational efficiency, custome...

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Edge AI Suites v1.0.0

28 Apr 09:38
@saikiransayabugari saikiransayabugari
v1.0.0
4214862
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Edge AI Suites v1.0.0

Edge AI Suite v1.0.0 (Initial Release)

Release Overview

The Edge AI Suite v1.0.0 marks our first public release, delivering collections of open, industry-specific AI software development kits (SDKs), microservices, and sample applications for independent software vendors (ISVs), system integrators, and solutions builders.

Key Goals

  • The Metro AI Suite accelerates the development of solutions for Edge AI video, safety and security, smart city, and transportation use cases.
  • The Manufacturing AI Suite enhances output quality and volume with automated defect detection, asset tracking, software-defined controls, and other capabilities, empowering smart factories with Vision, Time Series, and Generative AI capabilities.
  • The Retail AI Suite accelerates hardware decisions for Retail AI workloads at the edge, featuring use cases such as self-checkout and loss prevention.
  • The Media & Entertainment AI Suite provides libraries and sample applications to accelerate solution development for high-performance, high-quality, live video production, helping improve the viewer experience.

Key Components

The Edge AI Suites project hosts a collection of sample applications organized as follows:

Suite Sample Application Get Started Developers Docs
Metro AI Suite Loitering Detection Link Customize the Application
Metro AI Suite Image-Based Video Search Link Build and Deployment instructions
Metro AI Suite Smart Parking Link Customize the Application
Manufacturing AI Suite Pallet Defect Detection Link Customize the Application
Manufacturing AI Suite Weld Porosity Link Customize the Application
Retail AI Suite Automated Self Checkout Link Advanced Guide
Retail AI Suite Loss Prevention Link Advanced Guide

Highlighted Features

The Metro AI Suite includes the following tools and toolkits:

  • Metro AI Suite SDK: Provides a comprehensive and modular toolkit for accelerated media processing and AI inference, designed to fast-track the development of visual AI solutions.
  • Visual Pipeline and Performance Evaluation Tool: Assess Intel® hardware options, benchmark performance, and analyze key metrics to optimize hardware selection for AI workloads.
  • Device qualification tool For device and equipment manufacturers, the suite includes a device qualification tool to verify and benchmark hardware performance and create system qualification reports. See the recommended hardware catalog for a list of qualified system configurations.

The Suite also provides a collection of visual analytics sample applications, using deep learning and large models (GenAI):

  • Image Search by Text: A reference implementation using multi-modal large language models to perform image search with text query
  • Visual Q&A: A reference implementation using multi-model large language models to perform Q&A on image data
  • Loitering Detection: Effortlessly monitor and manage areas with AI-driven video analytics for real-time insights and enhanced security
  • Image Based Video Search: Performs near real-time analysis and image-based search to detect and retrieve objects of interest in large video datasets.
  • Smart Parking: Effortlessly manage parking spaces with AI-driven video analytics for real-time insights and enhanced efficiency.

The Manufacturing AI Suite helps you develop solutions for:

  • Production Workflow: Efficiency optimizations, product quality (detect anomalies, defects, or variations)
  • Workplace Safety: AI-based safety insights to help reduce risks
  • Real-Time Insights: Improve the production process (local data processing, integration with existing manufacturing execution systems, tracking defect rates, identifying trends)
  • Automation: Correct problems almost immediately (instant alerts, implementation of corrective actions)

The important components from Edge AI Libraries that help you develop such pipelines for industrial and manufacturing AI use cases are:

  • Deep Learning Streamer Pipeline Server: Built on top of GStreamer, a containerized microservice for development and deployment of video analytics pipeline.
  • Model Registry: Providing capabilities to manage lifecycle of an AI model.
  • Time Series Analytics: Ability to build time-series based AI pipeline utilizing Kapacitor and Telegraf containers, with InfluxDB for data storage.
  • Object Store Microservice: MinIO based object store microservice to build generative AI pipelines.
  • Intel® Geti™ SDK: A python package containing tools to interact with an Intel® Geti™ server via the REST API, helping you build a full MLOps for vision based use cases.

The Retail AI Suite is an open-source software framework designed to accelerate AI workload evaluation and hardware selection for point-of-sale use cases at the edge. It helps retail solution builders assess device configurations across Intel® product generations to enhance decision-making and reduce the total cost of ownership. Key use cases include:

  • Automated Self-Checkout: Product recognition (detection, classification, and tracking), full pipeline (product, weight, text, and barcode), age verification
  • Loss Prevention: Fake scans, items in basket, multi-product identification, product switching, shopper behavior (obscuring/hiding an item), event video summation

Known Issues

None

Breaking Changes

None — this is the initial release.

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