> ## Documentation Index
> Fetch the complete documentation index at: https://documentation.kodelabs.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Trends
> Chart historical point data with multi-point trending to monitor system performance, diagnose faults, and compare equipment behavior.
Trends is a building-level module. Select a building from the [sites list](/products/kode-os/sites-and-map) to access its trends.
Trends display historical time-series data for one or more points on a single chart. Multi-point trending allows you to overlay data from multiple devices, compare system behavior across time, and investigate anomalies. The feature supports customizable time ranges, zoom, interpolation, and data export.
## Access trends
You can access trends from two locations:
* **Device details** -- open a device's details page and click the `Trends` tab to see historical data for that device's points. From the summary bar, click `Faults` to open the [FDD Faults panel](/products/kode-os/devices/devices#view-faults-from-trends) for that device.
* **Trends module** -- click `Trends` in the left sidebar menu to access the standalone multi-point trending interface
## Add points to a trend chart
Click **`Trends`** in the left navigation bar to open the multi-point trending interface.
Use the left panel to filter points by **Area**, **Type**, **Point Field**, and **Device**. Search for specific points by name. Check the points you want to plot -- selected points appear on the chart immediately.
Click **`Show Selected`** to view only the checked points grouped by device, or **`Clear Selection`** to reset.
Use the date picker at the top right of the chart to select the analysis period. Available presets include **Last 2 Days**, **Last 7 Days**, and custom ranges. The granularity indicator (for example, `at 1 minute`) shows the current data resolution.
## Chart layout
The trend chart divides data into two visual sections:
* **Upper section** displays numeric data (temperature, pressure, flow rate, valve position) as line charts. Switch between **Combined**, **Line**, and **Bar** tabs to change chart style.
* **Lower section** displays binary or enumerated data (on/off status, mode selections) as colored bar charts
## Interact with the chart
### Zoom
Use the zoom bar or your mouse scroll wheel to zoom into a specific time period. As you zoom in, the data resolution increases and more detailed readings become visible.
### Hover for values
Hover over any point on the chart to see the exact data value and timestamp for all plotted points at that moment.
### Customize the Y-axis
Configure two Y-axes to display different measurement types simultaneously. For example, show temperature on the left axis and flow rate on the right axis.
### Clickable legend
Click any point name in the chart legend to hide or show that data series. This helps you focus on specific points without removing them from the chart.
## Data granularity
Granularity adjusts automatically based on the selected time range:
| Time Range | Granularity |
| ---------- | ------------------ |
| 2 days | 2-minute intervals |
| 7 days | 1-hour intervals |
| 30 days | Daily intervals |
Granularity applies only to the line chart and adjusts based on the selected date range.
The system uses interpolation to fill gaps between data points, providing a smooth continuous trend line even when readings are not collected every minute.
## Chart configurations
Open the **Configurations** panel from the right side of the chart to adjust display settings, aggregate functions, and Y-axis assignments.
### Settings
* **Show tooltip** -- toggle the tooltip that appears when you hover over data points on the chart
* **Interpolation** -- toggle interpolation to smooth the trend line between data points
### Aggregate functions
When viewing trend data at lower resolutions, you can set the aggregate function per point field. Available options:
* **Average** calculates the mean value over each interval
* **Sum** totals the values within each interval
* **Max** shows the highest value in each interval
* **Min** shows the lowest value in each interval
* **Count** shows the number of readings in each interval
### Y-axis assignment
Assign each point field to the **Left** or **Right** Y-axis. Use separate axes when plotting different measurement types (for example, temperature on the left and flow rate on the right) so each series scales independently.
## Save and share trend views
Click the **three-dot** menu at the top right of the chart to access **Save View**, **Copy link to Trends**, and **Export Point Timeseries**.
### Save a view
Select **`Save View`** from the menu. Enter a **Name** for the view and check **`Public`** if you want to share it with other users. Click **`Save`** to store the configuration.
Saved views can be accessed by everyone assigned on the building if they are public.
Saved views preserve selected points, time range, filters, Y-axis settings, and aggregation preferences. Views support two time range modes:
* **Dynamic** (for example, "Last 7 Days") always shows recent data relative to the current date
* **Static** preserves a specific date range for consistent review
### Share a view
Select **`Copy link to Trends`** from the menu to copy a shareable URL. Recipients see the same chart configuration and data.
### Export trend data
Select **`Export Point Timeseries`** from the menu to download trend data as a CSV file. The export includes all plotted points with their timestamps and values for the selected time range.
## Use cases for multi-point trending
The following scenarios demonstrate how building operators use multi-point trending to diagnose issues and optimize performance.
### Chilled water system optimization
**Scenario:** The chilled water system comprises chillers, chilled water pumps, and sensors monitoring temperature and flow at key points. The building's energy manager wants to optimize chiller efficiency but notices inconsistent cooling throughout the building.
**What to trend:** Plot the chilled water supply temperature (primary loop leaving temp), return temperature (primary loop entering temp), and run status for each chiller module. Include the AHU discharge air temperature and outside air temperature to see how efficiently cold water is distributed across zones.
| Devices | Points |
| ----------------------- | ----------------------------------------------------- |
| Chilled water loop | Primary loop entering temp, primary loop leaving temp |
| HRV 1, HRV 2 | Discharge air temp, outside air temp, run status |
| Chiller modules 1, 2, 3 | Run status |
**What to look for:** Compare supply and return temperature differential against chiller run status. A narrowing delta-T while chillers are running indicates reduced heat transfer efficiency. Correlate AHU discharge temperatures with chilled water supply to identify distribution imbalances.
### Condenser water system monitoring
**Scenario:** A large commercial building has a condenser water system with a cooling tower, condenser pumps, and temperature and pressure sensors. The operators notice the cooling tower is not maintaining the required condenser water temperature, leading to cooling inefficiencies.
**What to trend:** Plot the condenser water return temperature, supply temperature, and condenser pump speed alongside outside air temperature and cooling tower fan percentage.
| Devices | Points |
| ----------------------- | ----------------------------------------------------- |
| Condenser water loop | Primary loop leaving temp, primary loop entering temp |
| Cooling towers 1, 2 | Condenser fan percent, condenser fan status |
| Chiller modules 1, 2, 3 | Run status |
| HRV 1 | Outside air temp |
**What to look for:** A rising return temperature despite adequate fan speed and favorable outdoor conditions suggests fouling or mechanical issues. By plotting these variables on a single chart, you can see how the return temperature fluctuates relative to outside air temperature and pump operation without switching between multiple views.
### Fan and AHU coordination
**Scenario:** The building has multiple AHUs and fans providing ventilation across different floors. Energy usage spikes during peak occupancy hours, and the operations team wants to determine if fans and AHUs are operating efficiently.
**What to trend:** Plot fan speeds, building static pressure, AHU discharge air temperatures, VAV discharge damper commands, discharge airflow, and zone temperatures. Include effective occupancy status for VAVs and FCUs to correlate with load patterns.
| Devices | Points |
| -------- | -------------------------------------------------------------------------- |
| HRV 2 | Outside air temp, discharge air temp, building static pressure, run status |
| SVAV 2-1 | Discharge damper percent command, discharge airflow |
| FCU 14-2 | Zone temp |
| VAV, FCU | Effective occupancy |
**What to look for:** Compare fan speed and static pressure against zone temperatures and damper positions. If static pressure drops while dampers are fully open, the AHU may be undersized for the current load. Correlate occupancy status with energy patterns to identify over-conditioning of unoccupied zones.
When plotting multiple points, start with related data from a single system. Adding unrelated points creates cluttered charts. Use the legend to toggle individual series on and off as you analyze different aspects of system behavior. If two points overlap on the chart, hover over the desired point in the legend to isolate it.
## Next steps
Use trend data to evaluate and optimize equipment schedules.
Access device details and view trends for specific equipment.