Room occupancy refers to the number of people detected in a specific roomat a given time. There are two ways to measure room occupancy: traffic-based or presence-based. Each method uses a different approach depending on the available sensor data and the type of insights required.
Below are sample queries for retrieving room-level occupancy data to analyze peak, and average within a selected time range.
Recommended Practices
Function Selection for Occupancy Metrics:
Use the max function to capture peak values within the specified time window.
Use the mean function to capture average values within the specified time window.
Avoid Relative Time Queries: Do not use relative time functionality (e.g., -5m) as it may result in missing data depending on query timing. Always specify absolute start and stop times.
Timezone Configuration: Always provide a timezone when querying traffic-based occupancy
Include Zero Values in Output: To ensure zero values are included in the results, add the filter:
"filter": { "value": { "gte": 0 } }
Traffic-based Room Occupancy
If traffic sensors are installed at the room entrance(s), you can use the sample queries below to retrieve the estimated room occupancy counts.
Query the peak hourly occupancy of a room with traffic sensor installed:
Use the sample queries below to retrieve the total occupancy for areas covered by presence sensors in the room. Keep in mind that the sensor coverage area influences the count and may not represent the room's actual occupancy.
Query the peak hourly occupancy of a room with presence sensors installed:
