> For the complete documentation index, see [llms.txt](https://docs.buildings.ability.abb/collection/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.buildings.ability.abb/collection/suites/energy-and-sustainability-intelligence/energy-anomaly-detection/anomaly-detection-analytic-type.md).

# Anomaly detection analytic type

### Overview

In [*Insight Analytics*](/collection/platform/insight-analytics.md), you can use the analytic type *Anomaly detection* to visualize detected anomalies for a selected attribute.

This analytic type can also be used in [Platform](/collection/overview/mandatory-base-platform-suites-and-modules/platform.md).

If you save the configured analytic in [*Insight Analytics*](/collection/platform/insight-analytics.md), you can reuse it in dashboards, Smart Views, and [reports](/collection/platform/analytics-and-reports/use-reports.md).

This view lets you:

* select an attribute with anomalies
* display anomalies in the chart
* inspect the anomaly time range
* review the anomalies currently visible in the chart

Navigate to: [*Insight Analytics*](/collection/platform/insight-analytics.md) **\[1]**.\
▷ The *Insight Analytics* page opens.

### Elements of the *Anomaly detection* view

<figure><img src="/files/rGS9xPv0QR9dqKLeojrf" alt=""><figcaption></figcaption></figure>

<table data-header-hidden><thead><tr><th width="72.20001220703125">Marker</th><th width="185.00006103515625">Element</th><th>Description</th></tr></thead><tbody><tr><td><strong>[1]</strong></td><td><em>Insight Analytics</em></td><td>Opens the analytics interface.</td></tr><tr><td><strong>[2]</strong></td><td>Analytics type</td><td>Lets you select the analytic type <strong>Anomaly detection</strong>.</td></tr><tr><td><strong>[3]</strong></td><td>Attribute selection</td><td>Lets you select an attribute for which anomalies exist.</td></tr><tr><td><strong>[4]</strong></td><td>Visible anomalies list</td><td>Shows the anomalies that are currently visible in the chart.</td></tr><tr><td><strong>[5]</strong></td><td>Anomaly chart</td><td>Shows the selected attribute together with the anomaly visualization.</td></tr></tbody></table>

### Open the *Anomaly detection* analytic type

1. Open *Insight Analytics* **\[1]**.\
   ▷ The analytics interface opens.
2. In the **Analytics type** selector **\[2]**, select **Anomaly detection**.\
   ▷ The analytics view switches to anomaly visualization.
3. In the asset tree, select an attribute with anomalies under **\[3]**.\
   ▷ The chart is updated.

◈ In the general analytics interface, the analytics type, location tree, chart options, and time period can be configured from the analytics page .

### Understand the anomaly chart

The chart **\[5]** shows the selected attribute in the chosen timeframe.

Anomalies are visualized as follows:

* **Light blue line**: The measured data
* **Red background**: The time range in which the anomaly occurred
* **Red dot**: The detected anomaly point
* **Green range**: The healthy value range predicted by the model

### Understand the anomaly tooltip

When you hover over a red anomaly dot in the chart, a tooltip opens.

The tooltip shows detailed information about the selected anomaly.

<figure><img src="/files/1gVL7tZ2wtNhzPqMdjbm" alt=""><figcaption></figcaption></figure>

<table><thead><tr><th width="183.59991455078125">Field</th><th>Description</th></tr></thead><tbody><tr><td><strong>Financial impact</strong></td><td>The estimated financial impact of the anomaly. A negative value means financial loss. A positive value means financial gain.</td></tr><tr><td><strong>Time range</strong></td><td>The start and end time of the anomaly.</td></tr><tr><td><strong>Predicted</strong></td><td>The value predicted by the model for healthy behavior.</td></tr><tr><td><strong>Actual</strong></td><td>The measured value.</td></tr><tr><td><strong>Deviation</strong></td><td>The difference between the predicted and actual value.</td></tr><tr><td><strong>Severity</strong></td><td>The severity level of the anomaly.</td></tr><tr><td><strong>Validity</strong></td><td>The current validation status of the anomaly, for example <strong>Confirmed</strong>.</td></tr><tr><td><strong>Diagnostics</strong></td><td>A rule-based diagnostic summary of the anomaly.</td></tr><tr><td><strong>AI Explanation</strong></td><td>An AI-generated explanation of the likely cause of the anomaly.</td></tr><tr><td><strong>Recommended action</strong></td><td>An AI-generated recommendation for what to check or do next.</td></tr></tbody></table>

◈ The tooltip helps you review the anomaly directly in the chart without opening the anomaly detail page.

### Important note about aggregation and interval

The anomaly time range is highlighted by the red background.

To also see:

* the **red anomaly dot**
* and the **green predicted healthy range**

the selected **aggregation mode** and **interval** must match the aggregation at which the anomaly was detected.

If the aggregation or interval does not match, the anomaly can still be marked by its red background, but the anomaly point and the predicted range may not be shown.

{% hint style="info" %}
For many energy attributes, **Sum** is typically the useful aggregation function.
{% endhint %}

### Review visible anomalies

The table **\[4]** shows the anomalies that are currently visible in the chart.

The list helps you review the anomalies within the displayed timeframe without leaving the analytics page.

### Notes

* The *Anomaly detection* analytic type is part of the *Insight Analytics* interface .
* The analytics interface provides chart options such as chart type, aggregation mode, function, interval, normalization, and unit conversion .
* If required, adjust the time period and chart options until the anomaly is shown in the desired level of detail .


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