Industrial IoT Hardware for Predictive Maintenance, Real-Time Location, and AI-Powered Operations

Real-Time Location Systems (RTLS) provide the essential spatial context that transforms raw sensor data into actionable operational intelligence. In an industrial environment, knowing that a gas alarm has triggered is only half the battle; knowing exactly where the leak is and which workers are in the immediate vicinity is what saves lives. Ombrulla's PETRAN platform integrates RTLS data from UWB and BLE hardware to enable three critical capabilities: (1) Automated Geofencing-triggering alerts when workers enter unauthorized or high-risk zones; (2) Emergency Mustering-instantly accounting for all personnel during an evacuation with meter-level precision; and (3) Digital Permit-to-Work-verifying that a technician is physically at the correct asset before allowing maintenance work to begin. By correlating 'Who,' 'Where,' and 'When' with asset health data, RTLS creates a comprehensive digital twin of the entire industrial operation.

IoT sensors serve as the front-line data acquisition layer for Asset Performance Management, converting physical machine states into digital signals that AI can analyze. By continuously measuring parameters such as tri-axial vibration, temperature, pressure, and motor current, these sensors detect the early-stage 'signatures' of mechanical degradation-such as bearing wear, misalignment, or cavitation-weeks before they result in a failure. When integrated with PETRAN, this sensor data is processed through custom-trained AI models that establishment a multi-modal baseline of normal behavior and provide high-confidence Remaining Useful Life (RUL) predictions. This enables a shift from reactive 'run-to-fail' maintenance to a proactive, evidence-based strategy that maximizes asset uptime while significantly reducing the total cost of maintenance and spare parts inventory.

Industrial IoT gateways are ruggedized edge-computing devices that act as the critical 'bridge' between field-level sensors and the central PETRAN platform. They perform three primary functions: (1) Protocol Translation-converting disparate industrial signals like Modbus, OPC-UA, and LoRaWAN into a unified data format; (2) Data Aggregation and Normalization-cleaning and structuring raw sensor streams before transmission; and (3) Edge Intelligence-running local AI models for sub-second anomaly detection that does not depend on cloud connectivity. Ombrulla's gateways are engineered for the harshest industrial environments, featuring IP67/ATEX certifications, extended operating temperature ranges, and local data buffering to ensure zero data loss during network outages. This edge-centric architecture ensures that critical safety and operational alerts are generated instantly at the point of detection.

Edge devices enable sub-second safety alerts (critical for gas leaks or man-down events), ensure operational resilience during network outages, and reduce bandwidth by processing high-frequency data locally. They allow immediate local response while syncing with the cloud when connectivity is restored.

Wearable devices are body-worn systems that track worker location, environmental exposure, and safety status in real time. PETRAN supports RTLS tags (UWB/BLE), gas monitors (H₂S, CO, O₂, LEL), and combined devices with SOS and man-down detection. All data is correlated, allowing safety managers to see alerts alongside worker location and exposure levels.

Emergency alert systems enable workers to request help when incapacitated, provide supervisors with precise location and context, and generate audit-ready incident records for compliance (RIDDOR, OSHA, ISO 45001). PETRAN integrates SOS alerts, GPS/RTLS data, and sensor readings into a unified response workflow.

Fall detection uses sensor fusion (accelerometer, gyroscope, barometer) to identify genuine falls. A configurable grace period allows workers to cancel false alarms; otherwise, an automatic SOS is triggered with location data. This ensures rapid response while minimising false positives.

Key industries include Manufacturing, Oil & Gas, Healthcare, Logistics, Automotive, Mining, and Construction. Applications range from worker safety and asset tracking to compliance and operational efficiency improvements.

RTLS technologies include UWB (10–30cm accuracy), BLE (1–5m), RFID (checkpoint-based), GPS (outdoor tracking), and Wi-Fi RTLS. PETRAN supports hybrid deployments combining multiple technologies for optimal accuracy and cost efficiency.

BLE provides cost-effective, low-power zone-level tracking. Beacons broadcast signals detected by tags to determine location using RSSI-based positioning. It offers lower infrastructure cost compared to UWB and supports hybrid deployments.

IoT sensors capture early physical changes in equipment (vibration, temperature, current) that precede failure. Continuous monitoring enables AI-driven anomaly detection, allowing maintenance teams to act before breakdowns occur.

LoRaWAN provides long-range (2–15km), low-power connectivity for remote sensors. It enables 5–10 year battery life and supports applications like pipeline monitoring, agriculture, and large-scale industrial sites.

Yes. PETRAN integrates with CMMS (IBM Maximo, SAP EAM), ERP systems, EHS platforms, and WMS through APIs and connectors. RTLS data enhances workflows like work orders, compliance tracking, and asset management.

UWB delivers 10-30 cm indoor accuracy for safety-critical uses like permit zones and forklift collision alerts; BLE offers 1-5 m zone-level presence at much lower infrastructure cost. Most industrial sites deploy UWB in critical zones and BLE everywhere else.

For rotating equipment the baseline is tri-axial vibration sensors, bearing-housing temperature probes, and current transformers; thermal assets need IR sensors, and process assets need pressure and flow transmitters. Retrofit wireless kits install without shutdowns.

An industrial IoT gateway translates field protocols (Modbus, OPC-UA, LoRaWAN) into a unified stream, cleans and buffers data locally, and runs edge AI for sub-second alerts - keeping monitoring alive even during cloud outages.