Floor occupancy refers to the number of people detected on a specific floor at a given time. There are two ways to measure floor 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 floor-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 Floor Occupancy
If traffic sensors are installed at the floor entrances, you can use the sample queries below to retrieve the estimated floor occupancy counts. This measurement aggregates the counts from all main-entrance traffic sensors on the floor.
Query the peak hourly occupancy of a floor with main entrance(s) traffic sensor installed:
Use the sample queries below to retrieve the total occupancy for areas covered by presence sensors on the floor. Keep in mind that the sensor coverage area influences the count and may not represent the floor's actual occupancy.
Query the peak or average hourly occupancy of a floor with presence sensors installed:
