Mining operation at dusk with conveyor infrastructure

AI-Powered Operational Intelligence for Mining

Using existing CCTV, operational data and lightweight sensors to improve safety and prevent costly operational failures.

Aerial view of mining site infrastructure

The operational intelligence opportunity

Mining sites already generate the data. The opportunity lies in using it while operations are still underway.

CCTV + Cameras

Videos across all operational areas

Operational Systems

Check-in, Oracle and facility maps

Machine Sensors

Vibration, weight and magnetic data

Lumirithmic Intelligence Layer

Detect
Verify
Alert
Action
  • Miners use existing badges or tags, while ruggedised cameras cover entrances and high-risk areas.
  • Existing CCTV provides coverage across operational areas. Oracle and facility maps add operational context.
  • Vibration, weight and magnetic sensors support wear & tear detection.
  • A secure on-site edge server analyses camera, sensor and operational data against site-specific safety rules.
  • Verified events trigger alerts, notify supervisors and create records, even during connectivity interruptions.

Improved Safety

Improved compliance via AI powered verification

Reduced Downtime

Earlier intervention due to language tuned ops logic

Faster Response

Faster investigation by asking questions

Greater Visibility

Query operational history for incident reports

Aerial view of mining site infrastructure

Query intelligence data for precise information

Operational logic translates site procedures, safety rules and equipment thresholds into AI-readable decision rules. Field data from cameras, sensors and operational systems is continuously evaluated against this logic.

Supervisors can then ask questions in natural language—such as "What caused the media alert?"—and receive a concise, evidence-backed answer with relevant events, trends, confidence levels and recommended action.

Supervisor questions and AI responses showing verified event summaries, charts and recommended actions
Mine worker wearing PPE on the operational floor

Case 1: Real-time PPE compliance

Check-in data provides the context. CCTV shows whether required PPE remains visible on the operational floor.

1

Check-in

Assign required PPE rules by ingesting Compliance docs

2

Camera Routing

Activate the relevant camera feeds

3

Vision + Rules

Continuously report visible PPE and zone compliance

Multi-frame confirmation and supervisor response panels for a PPE compliance event

Multi-frame confirmation reduces alerts caused by brief occlusion

Grinding media fragment on a mineral conveyor

Case 2: Grinding media and mill failure detection

Fragments can enter processed material, force an inspection stop and damage downstream equipment.

Bespoke model training can detect these events.

Live fragment detection feed and media classification breakdown

Camera Data

Shape, movement, classification and volume cues

Machine Sensor Data

Vibration, magnetic and weight thresholds

Historical Data

Failure baselines, degradation and maintenance history

Pre-downstream alert and event details panels for a broken media event
Aerial view of mining site infrastructure

Case 3: One dashboard, every signal

Zone breaches, shift compliance and anomaly trends all resolve into a single live dashboard, so supervisors see risk the moment it appears rather than after the fact.

1

Zone Alert

Geofenced restricted-zone entries are flagged the instant they happen.

2

Compliance by Shift

Verified events roll up into live compliance scores for every shift.

3

Anomaly Trend

Statistical baselines catch drift before it crosses a threshold.

Live operations panel 1 of 3 Live operations panel 2 of 3 Live operations panel 3 of 3
Mine worker wearing PPE on the operational floor

Case 4: PPE compliance in production

The rollout validated one use case across one zone at one mine location before scaling.

Deployment Scope

  • 3-5 CCTV feeds in the same area
  • 1-2 worker categories with distinctive uniforms
  • 3-5 PPE attributes selected on training complexity
  • Existing check-in or equivalent integration
  • Inference runs on site using prosumer class inference hardware
Live PPE compliance dashboard showing a compliant worker detection, active alerts and accuracy metrics

Live PPE compliance dashboard

Validation Methodology

Each gate resolved a specific technical risk before scaling to the next phase

Discovery

Confirmed cameras, zones, sensors and integration constraints

Offline Proof

Tested real samples and synthetic edge cases

Site Trial

Connected live feeds and tuned alert thresholds

Rollout

Scaled across zones and equipment to maximise coverage

Haul truck on a mine site at dusk

Additional modules

Preview thumbnails for autonomous haul-truck hazard detection, restricted area monitoring, worker behaviour and safety events, and operational bottleneck detection
  • PPE compliance across more uniforms
  • Equipment anomaly detection
  • Autonomous haul-truck hazard detection
  • Restricted area monitoring
  • Worker behaviour and safety events
  • Operational bottleneck detection.
  • Guassian Splats with Drone

The same integration layer supports additional camera and sensor use cases as the platform expands.