IoT Fleet Health Monitor | mysimulator.uk

Fleet Health Monitor

Fleet size 144 devices

Alert threshold 30%

Failure sensitivity 1.0×

Recovery time 6 s

Online

–

Degraded

–

Offline

–

Avg battery

–

How it works

Each tile in the grid is one connected device with its own battery level and accumulated runtime (age). Battery drains steadily and each device rolls a random dropout check every tick — the check succeeds more often the older and more heavily used a device gets, mirroring how real IoT hardware (batteries, radios, flash storage) wears out. A device that fails or hits zero battery goes offline (red) and stays dark for the recovery window, then comes back online (green) as if replaced or serviced.

P(drop | tick) = failSensitivity · (age / lifetime)²
status = offline           if battery ≤ 0 or drop roll succeeds
       = degraded (⚠)      if online and battery < alertThreshold
       = online            otherwise

Fleet size — how many devices are being watched at once; a larger fleet makes rare failures visible as a steady background rate instead of isolated events.
Alert threshold — the battery percentage below which a still-connected device is flagged degraded (yellow) so it can be serviced before it actually drops offline.
Failure sensitivity — scales how quickly age turns into dropout risk; higher values simulate cheaper or more failure-prone hardware.
Recovery time — how long an offline device stays dark before it is treated as replaced/serviced and rejoins the fleet with a fresh battery.

Real-world relevance: this is the core loop behind any IoT fleet dashboard — smart-city sensor networks, industrial asset trackers, or fleet telematics — where the operational question is never "is one device broken" but "what fraction of the fleet is healthy right now, and which units need attention before they fail."

Online Degraded Offline

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