MOVCTX - Wireless Monitoring Node

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MOVCTX detects and documents mechanical events on vehicles, machines, and infrastructure—precisely, reliably, and traceably.

In addition to continuously evaluating mechanical stress, MOVCTX is particularly suitable for detecting events such as collisions and impact events, abrupt movements or changes in position, unusual vibration patterns, or structural stress peaks. Detected events are stored with a time stamp and transmitted via LoRaWAN.

MOVCTX uses modern, neural network-enabled sensor systems for local evaluation of complex movement patterns. This allows not only simple limit value exceedances to be detected, but also characteristic impact signatures, recurring stress patterns, or abnormal movement sequences.

Preprocessing takes place directly in the device. Only relevant events and condensed context information are transmitted.

High-precision calibration with the RET measurement system

For demanding applications, MOVCTX can be trained using the RET measurement system.

This reference calibration enables high-precision measurements of defined load profiles, reproducible threshold values, and precise event classification.

This allows for a significant increase in measurement accuracy in safety- or liability-related applications.

Typical areas of application

• Wheel-rail monitoring
• Vehicle fleets (construction sites, mining, special vehicles)
• Transport and logistics monitoring
• Transport infrastructure
• Energy and telecom cabinets
• Machines and industrial installations

The RET8000 is fully integrated into the RET measurement system and works with other RET measuring devices to collect and analyze comprehensive measurement data. The RET analysis software provides detailed insights into network performance, enabling operators to identify and optimize network problems in a targeted manner.

• 3-axis motion and shock sensors - High-resolution detection of impacts, vibrations, and movements.
• Event-based incident detection - Automatic detection of impacts, position changes, and stress peaks.
• Time-stamped event storage - Local storage of relevant events with precise timestamps.
• Neural network-enabled edge sensor platform - Support for local pattern recognition and complex event classification.
• LoRaWAN connectivity (Class A) - Energy-efficient radio transmission for distributed infrastructure and fleets.
• Ultra-low-power design - Optimized for long-term battery operation and low-maintenance installations.
• Trainable with RET reference measurement system - High-precision calibration and application-specific thresholds.
• Cloud integration for analysis and reporting - Damage risk score, fleet comparison, alarm management, and API connection.

• Early detection instead of damage – Detects mechanical stress before it leads to failures.
• Clear event documentation – Incidents are automatically detected and stored with a time stamp.
• Intelligent evaluation in the device – Relevant events instead of unnecessary raw data.
• Optimized for distributed systems - LoRaWAN-ready for vehicles, fleets, and infrastructure.
• Precisely calibratable - Can be trained with the RET measurement system for high-precision applications.