SSSoubhagya SahooFOUNDER • BUILDER • ARCHITECT
INDUSTRIAL IOT & MINING TELEMETRY • GLOBAL SUPPLY CHAIN

Rio Tinto — Autonomous Pit-to-Port Asset & Fleet Telemetry Blueprint

Principal Systems & Telemetry Strategist (Independent Case Study)
Autonomous Pit-to-Port Asset & Fleet Telemetry Blueprint
Executive Context

Heavy mineral operations span remote pits, hundreds of kilometres of heavy-haul rail and bulk marine terminals—an environment where connectivity is patchy and an hour of unplanned downtime is extraordinarily expensive.

The Challenge

Unify fragmented fleet, rail and port data into one continuous chain of custody for ore batches, while predicting failures on autonomous haulage before they stop production.

Architected an end-to-end industrial IoT, satellite-LoRaWAN mesh, and predictive fleet telemetry model for Rio Tinto's heavy mineral extraction and rail-to-port corridors. Modeled ore-grade batch tracking from pit crushers to bulk marine terminals and vibration-based predictive maintenance for autonomous haulage fleets.
4-Stage Architecture Explorer · Click any node

Vibration, GNSS and payload sensing on haul trucks and crushers.

  • ▸Tri-axial vibration accelerometers
  • ▸GNSS + payload telemetry
  • ▸Crusher ore-grade sampling
  • ▸RFID batch tags at stockpiles
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Unplanned Downtime Reduction
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Pit-to-Port Asset Visibility
Zero-Blindspot
Hybrid Mesh