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Efficient Dataset Creation for MEMS-Based Magnetic Sensor Systems in Intelligent Transportation Applications.

Michal Hodoň¹, Peter Šarafín¹, Lukáš Formanek¹

¹Department of Technical Cybernetics, Faculty of management Science and Informatics, University of Žilina, Univerzitna 8215/1, 010 26 Žilina, Slovakia.

Sensors (Basel, Switzerland)

|December 31, 2025

Summary

An advanced annotation tool streamlines dataset creation for Micro-Electro-Mechanical Systems (MEMS) sensors in intelligent transportation. This innovation boosts efficiency and accuracy in developing MEMS sensor systems for traffic monitoring.

Keywords:

data annotation data fusion intelligent transportation systems magnetic sensors vehicle detection

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Area of Science:

Engineering
Computer Science
Transportation Technology

Background:

Intelligent transportation systems rely on accurate data from Micro-Electro-Mechanical Systems (MEMS) sensors.
Developing high-quality datasets for MEMS sensor applications is time-consuming and labor-intensive.
Optimizing data annotation is crucial for enhancing the performance and reliability of MEMS-based applications.

Purpose of the Study:

To introduce and evaluate an advanced annotation tool for MEMS sensor datasets in intelligent transportation.
To demonstrate the tool's capability in improving the efficiency and accuracy of dataset creation.
To showcase the practical application of the tool using magnetometer data for traffic flow monitoring.

Main Methods:

Development of a specialized annotation tool for MEMS sensor data.
Integration of the tool into existing data processing workflows.
Testing the tool with a magnetometer-based sensor system for traffic flow monitoring.

Main Results:

Significant reduction in annotation time per event compared to manual labeling.
Increased throughput of events processed without compromising label consistency.
Demonstrated practical effectiveness and real-world applicability in traffic monitoring scenarios.

Conclusions:

The advanced annotation tool offers a substantial improvement for MEMS sensor dataset development.
The tool enhances efficiency and accuracy, benefiting engineers and researchers in sensor technology.
This innovation supports the advancement of MEMS applications in intelligent transportation systems.