An implementation of sensor network to assess near real-time digital twin fidelity

This study presents a pilot bidirectional Wireless Sensor Network (WSN) architecture designed to measure the fidelity of Digital Twins (DTw). Unlike standard systems that simply collect data, this approach creates a feedback loop from the digital to the physical twin, ensuring tighter synchronisation. We combined edge-enabled WSNs with IoT interfaces to track orientation and position with minimal delay. While Inertial Measurement Units (IMUs) proved reliable for orientation, we employed sensor fusion to correct positional drift. Achieving a maximum relative error of just 2.1%, this method provides a quantifiable baseline for predictive maintenance across the aerospace, manufacturing, and energy industries.