Estimate how many inspection, monitoring, or detection tasks a predictive sensor can complete during a shift. The model accounts for sampling time, analysis time, communication overhead, availability, and the number of sensors operating in parallel, turning technical cycle assumptions into a practical daily capacity plan.
Capacity is the maximum number of whole tasks the sensor group can process under the entered timing and availability assumptions. It is a planning limit, not a guarantee that every event will arrive evenly.
Sampling and analysis are treated as sequential stages on each sensor. If they overlap in your architecture, enter the measured end-to-end cycle instead.
With 24 sensors, an 8-hour window, 3 minutes of sampling, 1.5 minutes of analysis, 10% overhead, and 92% availability, the effective cycle is 5 minutes. Available time is 10,598.4 sensor-minutes, supporting 2,119 whole tasks.
The calculator divides productive cycle time by one minus the overhead rate, so higher overhead lengthens each effective task cycle and lowers capacity.
This model treats them as sequential. If your system pipelines those stages, use a measured end-to-end cycle time that reflects the overlap.
A partially completed task is not counted as usable capacity, so the main result rounds down to the nearest whole task.
Yes. Include expected charging, calibration, maintenance, connectivity loss, and other planned or typical downtime.
No. It estimates aggregate capacity over the work window; use a lower availability or extra buffer when events arrive unevenly.
| Variable | Meaning | Unit |
|---|---|---|
| Sampling time | Time spent acquiring one observation | minutes/task |
| Analysis time | On-device or assigned processing time | minutes/task |
| Overhead | Share of cycle lost to communication and coordination | percent |
| Availability | Share of the window sensors can work | percent |