{"id":71778,"date":"2025-06-23T09:16:29","date_gmt":"2025-06-23T12:16:29","guid":{"rendered":"https:\/\/a3aengenharia.com\/en-us\/content\/technical-articles\/intelligent-cctv-cameras-ai-and-metadata-for-vms\/"},"modified":"2026-04-26T21:02:09","modified_gmt":"2026-04-27T00:02:09","slug":"intelligent-cctv-cameras-ai-and-metadata-for-vms","status":"publish","type":"articles","link":"https:\/\/a3aengenharia.com\/en-us\/content\/technical-articles\/intelligent-cctv-cameras-ai-and-metadata-for-vms\/","title":{"rendered":"Intelligent CCTV Cameras: AI and Metadata for VMS"},"content":{"rendered":"\n

Intelligent CCTV cameras with AI and metadata for VMS<\/strong> are transforming security systems by combining advanced video analytics, automatic data generation, and efficient integration with management platforms. This evolution enables more accurate monitoring, faster responses, and greater operational efficiency.<\/p>\n\n\n\n

In this article<\/strong>, we examine in depth the principles, technologies, and architecture related to the generation and transmission of metadata by CCTV cameras with artificial intelligence, as well as their system-level integration with video management platforms (VMS), including technical considerations on communication standards such as ONVIF Profile M, edge analytics models, information filtering, intelligent search mechanisms, and application scenarios in corporate and industrial environments.<\/p>\n\n\n\n

Let’s dive in.<\/p>\n\n\n

[elementor-template id=”24446″]<\/p>\n\n\n\n

AI, Metadata, and Intelligence in Monitoring<\/h2>\n\n\n\n

The evolution of electronic security systems now depends on the use of cameras with built-in Artificial Intelligence (AI)<\/strong>. Unlike conventional cameras, this equipment functions as a true intelligent sensor<\/strong>, capable of mapping the scene and analysing images in real time directly at the edge (edge processing)<\/strong>, without requiring external servers to process data.<\/p>\n\n\n\n

The Artificial Intelligence embedded in cameras such as the PNO-A9081R performs advanced analytics<\/strong> that include:<\/p>\n\n\n\n

    \n
  • Object detection and classification:<\/strong> identifies people, faces, vehicles, and licence plates.<\/li>\n\n\n\n
  • Recognition of detailed attributes such as gender, clothing colour, presence of luggage, age, use of face masks, and vehicle type and colour.<\/li>\n\n\n\n
  • Intelligent behavioural analytics<\/strong>, such as:\n
      \n
    • Face mask detection.<\/li>\n\n\n\n
    • Social distancing monitoring.<\/li>\n\n\n\n
    • Slip & Fall detection.<\/li>\n\n\n\n
    • Intrusion analytics, loitering, and entry to or exit from defined virtual areas.<\/li>\n<\/ul>\n<\/li>\n\n\n\n
    • Business Intelligence (BI)<\/strong>:\n
        \n
      • People, vehicle, and crowd counting.<\/li>\n\n\n\n
      • Queue management.<\/li>\n\n\n\n
      • Heatmap generation for traffic flow and occupancy analysis.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n

        Metadata Generation<\/h3>\n\n\n\n

        All these functions generate rich metadata<\/strong>, which consists of structured information extracted from images, such as the object type, its characteristics, or the detected event. This metadata is sent directly to the VMS (Video Management System)<\/strong>, such as Genetec, Milestone, or Hanwha SSM, where it is stored and integrated into the system database. This enables:<\/p>\n\n\n\n

        ✅ Fast searches by specific characteristics, such as \u201cperson wearing a red shirt\u201d or \u201cblue vehicle.\u201d
        ✅ Generation of intelligent reports.
        ✅ Creation of dynamic alerts based on attributes or behaviours.
        ✅ Drastic reduction in event investigation time<\/strong>, optimising security operations.<\/p>\n\n\n\n

        This built-in intelligence turns a monitoring system into a proactive rather than merely reactive tool, raising the level of security and operational efficiency. Integrating and transmitting analytics data directly to the VMS delivers accuracy, response speed, and valuable insights for decision-making<\/strong>.<\/p>\n\n\n\n

        In practice, this capability is what differentiates high-performance professional solutions, such as those tested and demonstrated in A3A Engenharia’s<\/strong> showroom, from conventional video monitoring solutions.<\/p>\n\n\n\n

        Forensic Search<\/h2>\n\n\n\n

        In the image, we show the BriefCam Protect user interface displaying the results of a forensic video analysis<\/strong> based on video analytics algorithms powered by Artificial Intelligence. The software specifically filters red vehicles using metadata generated by intelligent cameras such as the Hanwha PNO-A9081R. This metadata, processed directly in the camera (AI on edge) or on a dedicated server, includes attributes such as object class, colour, direction, speed, and time spent in the scene. Once integrated with the VMS, it enables precise searches and data correlation for fast and accurate investigations.<\/p>\n\n\n\n

        The demonstration, conducted in A3A Engenharia’s showroom, illustrates practical applications of advanced analytics to significantly reduce analysis time in electronic security operations.<\/strong><\/p>\n\n\n\n

        \"AI
        FORENSIC SEARCH<\/strong> BRIEFCAM PROTECT<\/strong>
        TECHNICAL COLLECTION: A3A ENGENHARIA<\/strong><\/figcaption><\/figure>\n\n\n\n

        In high-performance electronic security projects, Forensic Search<\/strong> represents a crucial advance, especially when combined with artificial intelligence embedded in cameras. In the past, investigating incidents in monitoring systems meant reviewing hours or days of recordings in search of a specific event, a time-consuming process subject to human error and heavy time consumption.<\/p>\n\n\n\n

        \n

        Expert Commentary \u2014 Eng. Altair Galv\u00e3o<\/strong><\/p>\n\n\n\n

        \u201cIn the past, searching for an incident in a monitoring system literally meant \u2018binge-watching the CCTV system\u2019 \u2014 reviewing hours or even days of footage, an exhausting task that was highly prone to human error. Today, with video analytics based on Artificial Intelligence, it is possible to locate specific events in seconds, making the system far more accurate and efficient.\u201d<\/em><\/p>\n\n\n\n

        Eng. Altair Galv\u00e3o is a specialist in video analytics, certified by BriefCam, a global reference in forensic video analysis, with certification completed at the Axis Experience Center in Fort Lauderdale. He also holds certification in SAFR Facial Recognition, obtained at RealNetworks HQ in Seattle. With 29 years of experience in electronic security projects, he leads A3A Engenharia’s team, bringing practical and strategic vision to intelligent monitoring solutions<\/em>.<\/em><\/strong><\/p>\n<\/blockquote>\n\n\n\n

        With AI-based video analytics<\/strong>, this scenario has changed radically. Technologies such as object recognition, physical attributes, suspicious behaviour, and metadata generation transform every video frame into structured information. This means that data such as:<\/p>\n\n\n\n