{ "api_version": "1", "kind": "dse_post", "self": "https://update.dsesecurity.com/api/v1/posts/separate-axis-live-queue-counts-from-historical-queue-durations/", "item": { "id": "https://update.dsesecurity.com/updates/separate-axis-live-queue-counts-from-historical-queue-durations/", "slug": "separate-axis-live-queue-counts-from-historical-queue-durations", "url": "https://update.dsesecurity.com/updates/separate-axis-live-queue-counts-from-historical-queue-durations/", "alternate_urls": { "markdown": "https://update.dsesecurity.com/updates/separate-axis-live-queue-counts-from-historical-queue-durations.md", "json": "https://update.dsesecurity.com/api/v1/posts/separate-axis-live-queue-counts-from-historical-queue-durations/" }, "title": "Separate Axis live queue counts from historical queue durations", "summary": "Use live queue people, historical average people and historical minutes-in-level data for their respective questions. Preserve units before comparing or presenting an exported queue value.", "format": { "slug": "guide", "name": "Guide" }, "priority": { "slug": "advisory", "name": "Advisory" }, "featured": false, "image": { "theme": "physical-security", "label": "Physical security", "alt": "Integrated video surveillance and controlled entry at a modern commercial facility.", "card_url": "https://update.dsesecurity.com/assets/editorial/physical-security-card.webp?v=1.8.20", "hero_url": "https://update.dsesecurity.com/assets/editorial/physical-security-hero.webp?v=1.8.20", "social_url": "https://update.dsesecurity.com/assets/editorial/physical-security-social-v2.jpg?v=1.8.20", "width": 2400, "height": 1350 }, "topics": [ { "slug": "it", "name": "IT", "url": "https://update.dsesecurity.com/topic/it/" }, { "slug": "video-surveillance", "name": "Video Surveillance", "url": "https://update.dsesecurity.com/topic/video-surveillance/" } ], "author": { "name": "DSE Security Editorial Team", "url": "https://update.dsesecurity.com/#editorial-team", "type": "Organization" }, "publisher": { "name": "Detection Systems & Engineering", "url": "https://dsesecurity.com/" }, "published_at": "2026-10-30T06:05:02+00:00", "modified_at": "2026-10-30T06:05:13+00:00", "reviewed_on": "2026-10-30", "reading_minutes": 3, "word_count": 524, "potentially_affected": "Deployments exposing the documented Axis Queue monitor API; application availability, counting accuracy and retention are outside this article’s acceptance scope.", "dse_recommendation": "DSE recommends a report contract naming the output type, region, interval and units before queue data is used in a decision.", "primary_source": { "name": "Axis Communications — Queue monitor API", "url": "https://developer.axis.com/vapix/applications/queue-monitor-api/", "published_on": null, "authority": "Axis Communications" }, "publishing_principles": "https://update.dsesecurity.com/updates/dse-updates-editorial-methodology/", "usage_info": "https://update.dsesecurity.com/usage/", "copyright_notice": "Copyright © 2026 Detection Systems & Engineering. All rights reserved.", "content_html": "

Bottom line: Choose the measure before choosing the report. Keep a current count, an average people value and time spent at a queue level clearly labeled rather than presenting them as interchangeable head counts.

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Source fact: documented behavior

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The Queue monitor API describes live JSON data with the number of people standing in each region and a timestamp expressed in the camera’s time.

\n

Its historical minute CSV reports the number of minutes spent at a High, Mid or Low queue level for a region.

\n

The historical people CSV instead reports the average number of people in a region of interest.

\n

What the source does not establish

\n

This article reviews report interpretation, not the accuracy of a people-counting deployment. It does not establish retained history, complete occupancy, configured queue-level thresholds or support on an unnamed camera. Keep application and scene acceptance separate from choosing the documented output type.

\n

Applicability questions

\n\n

DSE recommendation: controlled next steps

\n

The following steps are DSE recommendations based on the cited source.

\n

DSE recommends a report contract naming the output type, region, interval and units before queue data is used in a decision.

\n
    \n
  1. Write the operational question in ordinary language. For a proposed current-status display, identify the live region count that answers it. For a historical staffing review, decide whether the required measure is average people or time spent at configured queue levels. Keep those questions separate instead of choosing whichever export already opens in a spreadsheet.
    2. \n
  2. Inspect the actual returned headers and region identities before building a chart or threshold. Label a duration as minutes and an average as average people. Preserve the selected reporting interval and camera time context beside the value. Do not rename a High-level duration column to people waiting or sum unlike measures into a visually convenient total.
    3. \n
  3. Use a proposed desk fixture with one live-count record, one minute-level row and one historical-average row. Ask the report owner to assign the correct label to each. Make the required output choice explicit in the report definition, then review one permitted real output without clearing history or altering counting parameters merely to produce a demonstration.
    4. \n
\n

Verification and evidence

\n

Proposed verification: have a second analyst reconstruct the report from the retained output type, region, interval and units. Compare a small set of displayed values with their original fields. Keep missing data or ambiguous time context visible instead of filling the interval with an unlabeled assumption.

\n

Present the proposed minute-level row to a reviewer who has not seen the report design and ask what its number means. Reject a display that encourages a head-count reading of that duration. Retain the corrected label and source field mapping. No queue was counted, reporting interval measured or analytics accuracy tested for this article.

\n

Official references

\n\n

Source review completed October 30, 2026. Recheck the official source and deployment-specific applicability before changing production settings.

\n", "content_text": "Bottom line: Choose the measure before choosing the report. Keep a current count, an average people value and time spent at a queue level clearly labeled rather than presenting them as interchangeable head counts.\nSource fact: documented behavior\nThe Queue monitor API describes live JSON data with the number of people standing in each region and a timestamp expressed in the camera’s time.\nIts historical minute CSV reports the number of minutes spent at a High, Mid or Low queue level for a region.\nThe historical people CSV instead reports the average number of people in a region of interest.\nWhat the source does not establish\nThis article reviews report interpretation, not the accuracy of a people-counting deployment. It does not establish retained history, complete occupancy, configured queue-level thresholds or support on an unnamed camera. Keep application and scene acceptance separate from choosing the documented output type.\nApplicability questions\n\nDoes the question ask how many people are present or how long a queue level persisted?\nWhich region and interval should the report represent?\nIs the value current, averaged or a duration?\nWhat camera time reference and output labels will travel with the evidence?\n\nDSE recommendation: controlled next steps\nThe following steps are DSE recommendations based on the cited source.\nDSE recommends a report contract naming the output type, region, interval and units before queue data is used in a decision.\n\nWrite the operational question in ordinary language. For a proposed current-status display, identify the live region count that answers it. For a historical staffing review, decide whether the required measure is average people or time spent at configured queue levels. Keep those questions separate instead of choosing whichever export already opens in a spreadsheet.\nInspect the actual returned headers and region identities before building a chart or threshold. Label a duration as minutes and an average as average people. Preserve the selected reporting interval and camera time context beside the value. Do not rename a High-level duration column to people waiting or sum unlike measures into a visually convenient total.\nUse a proposed desk fixture with one live-count record, one minute-level row and one historical-average row. Ask the report owner to assign the correct label to each. Make the required output choice explicit in the report definition, then review one permitted real output without clearing history or altering counting parameters merely to produce a demonstration.\n\nVerification and evidence\nProposed verification: have a second analyst reconstruct the report from the retained output type, region, interval and units. Compare a small set of displayed values with their original fields. Keep missing data or ambiguous time context visible instead of filling the interval with an unlabeled assumption.\nPresent the proposed minute-level row to a reviewer who has not seen the report design and ask what its number means. Reject a display that encourages a head-count reading of that duration. Retain the corrected label and source field mapping. No queue was counted, reporting interval measured or analytics accuracy tested for this article.\nOfficial references\n\nQueue monitor API — Axis Communications; official VAPIX documentation.\n\nSource review completed October 30, 2026. Recheck the official source and deployment-specific applicability before changing production settings.", "content_markdown": "Bottom line: Choose the measure before choosing the report. Keep a current count, an average people value and time spent at a queue level clearly labeled rather than presenting them as interchangeable head counts.\n\n## Source fact: documented behavior\n\nThe [Queue monitor API](https://developer.axis.com/vapix/applications/queue-monitor-api/) describes live JSON data with the number of people standing in each region and a timestamp expressed in the camera’s time.\n\nIts historical minute CSV reports the number of minutes spent at a High, Mid or Low queue level for a region.\n\nThe historical people CSV instead reports the average number of people in a region of interest.\n\n## What the source does not establish\n\nThis article reviews report interpretation, not the accuracy of a people-counting deployment. It does not establish retained history, complete occupancy, configured queue-level thresholds or support on an unnamed camera. Keep application and scene acceptance separate from choosing the documented output type.\n\n## Applicability questions\n\n- Does the question ask how many people are present or how long a queue level persisted?\n\n- Which region and interval should the report represent?\n\n- Is the value current, averaged or a duration?\n\n- What camera time reference and output labels will travel with the evidence?\n\n## DSE recommendation: controlled next steps\n\nThe following steps are DSE recommendations based on the cited source.\n\nDSE recommends a report contract naming the output type, region, interval and units before queue data is used in a decision.\n\n- Write the operational question in ordinary language. For a proposed current-status display, identify the live region count that answers it. For a historical staffing review, decide whether the required measure is average people or time spent at configured queue levels. Keep those questions separate instead of choosing whichever export already opens in a spreadsheet.\n\n- Inspect the actual returned headers and region identities before building a chart or threshold. Label a duration as minutes and an average as average people. Preserve the selected reporting interval and camera time context beside the value. Do not rename a High-level duration column to people waiting or sum unlike measures into a visually convenient total.\n\n- Use a proposed desk fixture with one live-count record, one minute-level row and one historical-average row. Ask the report owner to assign the correct label to each. Make the required output choice explicit in the report definition, then review one permitted real output without clearing history or altering counting parameters merely to produce a demonstration.\n\n## Verification and evidence\n\nProposed verification: have a second analyst reconstruct the report from the retained output type, region, interval and units. Compare a small set of displayed values with their original fields. Keep missing data or ambiguous time context visible instead of filling the interval with an unlabeled assumption.\n\nPresent the proposed minute-level row to a reviewer who has not seen the report design and ask what its number means. Reject a display that encourages a head-count reading of that duration. Retain the corrected label and source field mapping. No queue was counted, reporting interval measured or analytics accuracy tested for this article.\n\n## Official references\n\n- [Queue monitor API](https://developer.axis.com/vapix/applications/queue-monitor-api/) — Axis Communications; official VAPIX documentation.\n\nSource review completed October 30, 2026. 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Preserve units before comparing or presenting an exported queue value.", "articleBody": "Bottom line: Choose the measure before choosing the report. Keep a current count, an average people value and time spent at a queue level clearly labeled rather than presenting them as interchangeable head counts.\nSource fact: documented behavior\nThe Queue monitor API describes live JSON data with the number of people standing in each region and a timestamp expressed in the camera’s time.\nIts historical minute CSV reports the number of minutes spent at a High, Mid or Low queue level for a region.\nThe historical people CSV instead reports the average number of people in a region of interest.\nWhat the source does not establish\nThis article reviews report interpretation, not the accuracy of a people-counting deployment. It does not establish retained history, complete occupancy, configured queue-level thresholds or support on an unnamed camera. Keep application and scene acceptance separate from choosing the documented output type.\nApplicability questions\n\nDoes the question ask how many people are present or how long a queue level persisted?\nWhich region and interval should the report represent?\nIs the value current, averaged or a duration?\nWhat camera time reference and output labels will travel with the evidence?\n\nDSE recommendation: controlled next steps\nThe following steps are DSE recommendations based on the cited source.\nDSE recommends a report contract naming the output type, region, interval and units before queue data is used in a decision.\n\nWrite the operational question in ordinary language. For a proposed current-status display, identify the live region count that answers it. For a historical staffing review, decide whether the required measure is average people or time spent at configured queue levels. Keep those questions separate instead of choosing whichever export already opens in a spreadsheet.\nInspect the actual returned headers and region identities before building a chart or threshold. Label a duration as minutes and an average as average people. Preserve the selected reporting interval and camera time context beside the value. Do not rename a High-level duration column to people waiting or sum unlike measures into a visually convenient total.\nUse a proposed desk fixture with one live-count record, one minute-level row and one historical-average row. Ask the report owner to assign the correct label to each. Make the required output choice explicit in the report definition, then review one permitted real output without clearing history or altering counting parameters merely to produce a demonstration.\n\nVerification and evidence\nProposed verification: have a second analyst reconstruct the report from the retained output type, region, interval and units. Compare a small set of displayed values with their original fields. Keep missing data or ambiguous time context visible instead of filling the interval with an unlabeled assumption.\nPresent the proposed minute-level row to a reviewer who has not seen the report design and ask what its number means. Reject a display that encourages a head-count reading of that duration. Retain the corrected label and source field mapping. No queue was counted, reporting interval measured or analytics accuracy tested for this article.\nOfficial references\n\nQueue monitor API — Axis Communications; official VAPIX documentation.\n\nSource review completed October 30, 2026. 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All rights reserved.", "citation": { "@type": "CreativeWork", "name": "Axis Communications — Queue monitor API", "url": "https://developer.axis.com/vapix/applications/queue-monitor-api/" } } ] } }