# FAQs

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<summary><strong>Why do I see different numbers between <code>traffic_floor_occupancy/floor_occupancy</code> , and <code>traffic_room_occupancy/room_occupancy</code>?</strong></summary>

The difference between `traffic` and `occupancy` base metrics stems from the type of sensors used and how they calculate occupancy:

* **`traffic_floor_occupancy`** is calculated using traffic sensors at main floor entrances, tracking people as they enter and exit the floor.
* **`floor_occupancy`** aggregates counts from presence sensors that cover specific areas on the floor, providing a snapshot of occupancy only within those monitored areas.

**Traffic Mode**

In [**traffic mode**](https://docs.butlr.io/spatial-metrics#id-1.-traffic-mode), sensors track **entries and exits** at designated floor entrances to estimate occupancy. This mode effectively monitors overall movement trends but does not directly capture occupancy across all areas of the floor. Missing even a single entry or exit can introduce drift, causing compounding inaccuracies over time. To manage this, the occupancy count resets to zero at midnight daily.

**Presence Mode**

In [**presence mode**](https://docs.butlr.io/spatial-metrics#id-2.-presence-mode), sensors detect **activity within defined spaces** by counting individuals within their field of view. This gives a real-time snapshot of occupancy in areas covered by presence sensors, though it does not account for people outside these areas. Counts may also fluctuate slightly if individuals move between sensors within a short period (e.g., walking through multiple spaces within a minute).

**Why Traffic and Presence Counts Differ**

Due to these different methods, `traffic_floor_occupancy/floor_occupancy` and `traffic_room_occupancy/room_occupancy` counts will inherently vary:

* **Limited Presence Coverage**: Where presence sensors cover only part of a floor (e.g., 10%), traffic counts at main entrances will typically show higher occupancy.
* **High Coverage Floors**: With 80%+ coverage by presence sensors, counts tend to align more closely, though minor fluctuations and occasional missed entries/exits can still create discrepancies.

These differences mean that `traffic_floor_occupancy/floor_occupancy` and `traffic_room_occupancy/room_occupancy` will not match perfectly.

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