Unauthorized Unloading Detection for Coal Trucks — IoT Sensor Solution

Unauthorized unloading is the single highest-risk pilferage method in Indian coal logistics. A truck stops at a pre-arranged location, raises its tipper body, and discharges 2–5 tonnes. The driver continues to the plant. The material is gone.

GPS alone will never catch this. Without activity sensing using sensors, there is no alert, no evidence, and no recourse.

How the Detection Works

Intugine's IAS (Intugine Activity Sensing) module uses IoT sensors to capture physical activity data from the truck body. The platform analyses this sensor data using a rolling window algorithm to classify every halt as idle, transit, loading, or unloading.

When an unloading classification is confirmed outside an authorised plant geofence, an alert fires immediately.

The Alert Flow

T+0: IAS module classifies event as unauthorized unloading

T+30 sec: Alert pushed to plant dashboard and control tower analyst queue

T+2 min: Analyst reviews — confirms location, duration, sensor confidence

T+5 min: Driver contact placed

T+10 min: If unreachable — transporter escalation

T+15 min: If unresolved — plant security notified with full evidence package

The truck is still en route. The plant can direct it to special sampling on arrival.

Why Indian Coal Routes Are High-Risk

Jharkhand / Odisha to Maharashtra / Gujarat: 1,000–1,500 km routes through corridors with established informal coal markets.

Chhattisgarh mines to nearby power plants: 100–300 km routes, 100–300 trucks/day — surveillance without automation is impossible.

Port-to-plant for imported coal: Dense corridors from Kandla, Mundra, Vizag, or Paradip with multiple halt opportunities.

Evidence Package for Dispute Resolution

Every detected event creates an immutable evidence package:

GPS coordinates and timestamp

Sensor data and activity classification

Confidence score

Satellite imagery of halt location

Driver phone status and call log

Analyst notes and escalation record

Sufficient for transporter penalty enforcement, FIR filing, and insurance claims.

Deterrence Effect

In deployments where drivers know IoT activity sensing is active, unauthorized unloading attempts drop 60–80% within 30 days. The risk of being caught with sensor evidence is qualitatively different from being suspected from a weight shortfall.