One Operational Picture
Across Pit, Plant & Tailings
How KP Iron Pvt. Ltd. moved four sites and 1,284 sensors off three vendor portals and weekly spreadsheets onto MineSense IoT by Andolasoft: one live view for safety, compliance and uptime.
- 1,284
- Sensors live across pit, plant and tailings
- 98.2%
- Device uptime over two quarters
- 4
- Sites in one control room
- <8wks
- From kick-off to live dashboards
Production figures from the KP Iron deployment. Detailed case material is available under NDA.
The client
KP Iron Pvt. Ltd. is an Indian iron-ore producer running a multi-pit mine, an on-site beneficiation circuit and a tailings storage facility. Like most producers in the eastern iron-ore belt, it works under tightening DGMS and CPCB scrutiny, growing investor demand for ESG transparency, and throughput targets that leave no room for unplanned downtime on fixed plant.
Iron-ore mining
Pit-to-port operation with on-site beneficiation, run-of-mine stockpiles and one tailings storage facility.
4 active sites
Open pit, underground exploratory levels, beneficiation plant and TSF, previously on three vendor portals.
DGMS · CPCB · MoEFCC
Mines Act 1952 obligations, ambient and stack emission limits, EIA conditions and tailings disclosure.
ESG and uptime together
Defend safety, environmental and production performance with the same rigour, in real time.
From three portals and weekly spreadsheets to one live picture
Plenty of sensors were already in the ground. The problem was that their data never reached a decision-maker in time, or in one place.
Where KP Iron started
- Three sensor vendors, three portals, three definitions of “online”
- Underground gas readings depended on manual rounds, leaving hours between readings
- Conveyor and crusher failures surfaced only at hard-threshold alarms, too late to avoid a stoppage
- Tailings data sat in a separate portal and was reviewed weekly in spreadsheets
- DGMS and CPCB inspections took days of paperwork rebuilt across maintenance, HSE and environment teams
- New “smart” sensors stalled because each spoke a different protocol with no shared view
Where KP Iron is today
- One live picture: the GM, HSE officer and maintenance head see the same number for the same sensor at the same second
- Continuous CH₄, CO, H₂S and O₂ telemetry replaces manual gas rounds, with alerts routed and acknowledgements tracked
- Models on bearing temperature, vibration, current draw and belt load flag failures days ahead, not minutes
- Piezometers, settlement pins, freeboard and pond cameras in one GISTM-aligned TSF dashboard
- DGMS Form-IV registers and CPCB monthly returns generated from live data
- Edge gateways speak Modbus, OPC-UA, MQTT, LoRaWAN, BLE and 4G, so existing sensors plug in
The approach
We started with the risks that cost the most if missed: underground gas and the beneficiation conveyor. Everything else was planned to follow once those two were live and signed off by HSE and operations.
Nothing in the field was ripped out. A ruggedised edge gateway at each site reads the sensors KP Iron already owned, whatever their protocol, and stores readings locally when the network drops so no data is lost between the pit and the control room.
Above the gateways sits one platform: a single time-series history with an audit trail, threshold rules and predictive models on top, and alarm routing that sends each alert to the person who owns it. Reports for DGMS, CPCB and the board are built from the same data, so the number in the inspection file is the number the control room saw.
How it fits together
Every site keeps its existing sensors. A ruggedised edge gateway at each location collects them, buffers through network drops, and forwards to one platform that alerts, predicts and reports for the whole operation.
Five modules live, more to come
KP Iron began with the modules that retired the largest current risks. Further expansion is decided in quarterly value reviews with operations and finance.
Underground & opencast gas
Gas dashboards by zone, supervisor alerts within seconds, and a closed loop with the ventilation team.
Vibration & bearing health
Predictive interventions on the conveyor and crusher circuits, catching bearing wear and belt slip early.
TSF integrity
One GISTM-aligned TSF dashboard, replacing a third-party portal and a weekly spreadsheet roll-up.
Air quality & perimeter
CPCB-formatted monthly returns generated automatically; perimeter exceedances open an exception workflow.
Fleet telemetry
Haul-cycle visibility, idle-time analysis and a Scope 1 emissions feed for the quarterly ESG pack.
Mapped to the frameworks auditors use
Each reading, alarm and acknowledgement is tied to the obligation it serves under DGMS, CPCB, MoEFCC and ICMM GISTM.
Inside the control room
The GM, the HSE officer and the maintenance head open the same view. Four headline numbers sit on top; below them, each module has its own screen. Pick one to see what it shows.
- 17:02Threshold crossed on L3-ZB-001; shift supervisor and ventilation team alerted by SMS
- 17:04Alert acknowledged in the control room; auxiliary fan boosted for Zone B
- 17:41Reading back under 0.6 %LEL; incident closed with the full timeline logged
| Zone | CH₄ | CO ppm | O₂ % | Status |
|---|---|---|---|---|
| L1 Zone A | 0.18 | 6 | 20.8 | OK |
| L2 Zone A | 0.31 | 9 | 20.7 | OK |
| L3 Zone B | 0.84 | 14 | 20.5 | Watch |
| L3 Zone C | 0.27 | 7 | 20.8 | OK |
- CriticalCH₄ sensor L3-ZB-001UG L3 Zone B · 4 min
- WarningBearing temp · Crusher 2Plant · 12 min
- ResolvedBelt load · Conveyor NorthPlant · 31 min
From kick-off to live dashboards in under eight weeks
A four-phase, ROI-gated rollout, so leadership saw measurable value before it was scaled across the operation.
- 01Weeks 1–2
Discover & map
Site walks across pit, plant and TSF. Sensor inventory, regulatory pain points and an ROI baseline before any hardware was touched.
- 02Weeks 3–8
Pilot: gas & conveyor
MineSense live on underground gas and one beneficiation conveyor, with success criteria signed by HSE and operations leadership.
- 03Weeks 9–18
Scale across sites
Templated edge deployment at the remaining locations, SAP PM integration, crew training and progressive activation of analytics.
- 04Continuous
Optimise
Monthly value reviews with operations and finance, a quarterly compliance pack for the board, and model retraining with reliability engineers.
Hybrid edge + cloud
Edge gateways with local store-and-forward at each site; a control-room cloud, with an on-premise option kept for sensitive data.
SAP PM · DCS · CCTV · email/SMS
SAP Plant Maintenance for work orders, Modbus to the beneficiation DCS, the existing CCTV grid for visual context, and email and SMS escalation.
Roles, audit, model lifecycle
Role-based access for mine manager, HSE, electrical, mechanical and environment teams, an immutable audit trail, and model versioning with drift monitoring.
Outcomes
From production operation of MineSense IoT at KP Iron across pit, plant and TSF.
- 1,284
- active sensors monitored across pit, plant and TSF
- 98.2%
- average device uptime over two consecutive quarters
- 4
- sites unified into one dashboard for the GM and HSE leadership
- 0
- DGMS-reportable gas excursions undetected since go-live
- <8 wks
- from kick-off to the first live dashboards in production
- 3 → 1
- vendor portals consolidated into one control-room view
- SAP PM
- work orders opened automatically from predictive alerts on conveyors and crushers
- 1-click
- DGMS Form-IV and CPCB monthly returns from live data
Beyond the numbers
A shared dataset
Operations, HSE and reliability teams now meet against the same numbers. Disagreements are about what to do, not whose figure is right.
Faster, defensible decisions
Predictive alerts arrive with the operating profile, the top contributing signals and a recommended action, so maintenance triage takes seconds.
Audit-ready by default
Every reading, alarm and acknowledgement is recorded and mapped to DGMS, CPCB and ICMM frameworks. Inspection prep is an export, not a project.
We needed one place where the GM, the safety officer and the maintenance head saw the same number for the same sensor, at the same second. MineSense gave us that, and the predictive layer paid for itself in the first quarter.
What’s next at KP Iron
The next phases take the platform from monitoring and prediction towards closed-loop control and ESG-grade reporting.
Worker proximity & collision avoidance
RFID/UWB tags and AI-camera analytics for pedestrian-vehicle separation, no-go zones and tag-in/tag-out across the open pit.
Water balance & discharge
pH, turbidity, conductivity, dissolved oxygen and flow across the mine-water circuit, checked against consent limits.
Energy intensity per tonne
kWh and diesel by asset, shift and ore type, feeding Scope 1 and 2 emissions reporting.
Closed-loop ventilation
Ventilation on demand, driven by live gas and personnel data, to save power while keeping statutory air quality.
Slope & pit-wall stability
Slope radar and prism feeds correlated with rainfall, blast vibration and pore pressure for early bench-instability warning.
Lender & insurer disclosure pack
A quarterly tailings, water and emissions pack generated from live data for board, lender and insurer reviews.
Could your mine run on one operational picture?
Book a working session with our mining IoT team. We will walk a live control-room dashboard against your top three risks, whether gas, fixed plant or tailings, and share an ROI model built around your operation.
A detailed KP Iron case study and a reference call are available on request under NDA.