Activity Sensing for Coal Unloading Detection — How Sensor Data Stops Pilferage

GPS can tell you a truck stopped for 40 minutes on NH-75. It cannot tell you whether physical unloading activity occurred during that stop.

Activity sensing solves this. By capturing sensor data from the truck body using IoT devices, a platform can detect the physical signature of an unloading event — regardless of where the truck is located.

What the IAS Module Captures

The IAS (Intugine Activity Sensing) device is mounted on the truck's tipper body. It captures physical activity data continuously using IoT sensors — signals related to physical displacement of the cargo body, sustained activity consistent with material discharge, and return-to-baseline after an unloading event completes.

The Rolling Window Algorithm

Raw sensor data is noisy. The IAS module analyses patterns across a 5–10 minute window and classifies activity as:

Transit — vehicle in motion

Loading halt — sensor signature consistent with material being loaded

Unloading halt — sensor signature consistent with material discharge

Idle halt — vehicle stopped, no significant physical activity

When an Alert Fires

Any classified unloading event outside the authorised plant geofence triggers an alert:

Alert to plant dashboard + control tower analyst queue

Analyst confirms location, duration, confidence score

Escalation call to transporter if confirmed unauthorized

Evidence log preserved: GPS, sensor data, activity classification, timestamp

Alert to analyst review: under 2 minutes.

Confidence Scoring

80+: Pattern clearly matches unloading signature. Automatic alert.

50–79: Ambiguous. Flagged for human control tower review.

Below 50: Logged, no automatic alert.

What IAS Detects in Coal Logistics

Back-unloading at en-route stops

Partial unloading — truck arrives underweight

Drive-through fraud — truck enters plant geofence but no unloading occurs at plant

Tarpaulin disturbance — sensor detects physical interference consistent with manual material removal

Coal-Specific Calibration

The IAS module is calibrated per vehicle type (single-axle, multi-axle, rear-tipper, side-tipper) using a training dataset from thousands of real unloading events across coal plants in Jharkhand, Odisha, Chhattisgarh, and Rajasthan.