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

This article describes the innovative use of an advanced annotation tool designed specifically for creating datasets tailored to MEMS (Micro-Electro-Mechanical Systems) sensor systems for the intelligent transportation domain. By optimizing the data annotation process, this tool significantly enhances the efficiency and accuracy of dataset development, which is critical for the optimal performance and reliability of MEMS-based applications. The tool was tested with a specialized sensor system based on magnetometers for traffic flow monitoring, demonstrating its practical applications and effectiveness in real-world scenarios. The proposed approach offered a clear improvement over manual labelling by reducing the time needed per event and increasing the number of events that could be processed, without compromising the consistency of the assigned labels. The discussion includes a detailed overview of the tool's features, its integration into existing workflows, as well as the benefits it offers engineers and researchers in the field of sensor technology.

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Publication Details

Journal
Sensors
Published
2025-12-05
DOI
https://doi.org/10.3390/s25247407
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Michal Hodoň, Andrea Kociánová, Lukáš Formanek, Peter Šarafín
Sensors
Traffic Prediction and Management Techniques
article

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

Michal Hodoň, Andrea Kociánová, Lukáš Formanek, Peter Šarafín
article en

Abstract

This article describes the innovative use of an advanced annotation tool designed specifically for creating datasets tailored to MEMS (Micro-Electro-Mechanical Systems) sensor systems for the intelligent transportation domain. By optimizing the data annotation process, this tool significantly enhances the efficiency and accuracy of dataset development, which is critical for the optimal performance and reliability of MEMS-based applications. The tool was tested with a specialized sensor system based on magnetometers for traffic flow monitoring, demonstrating its practical applications and effectiveness in real-world scenarios. The proposed approach offered a clear improvement over manual labelling by reducing the time needed per event and increasing the number of events that could be processed, without compromising the consistency of the assigned labels. The discussion includes a detailed overview of the tool's features, its integration into existing workflows, as well as the benefits it offers engineers and researchers in the field of sensor technology.

SensorsVol. 25(24)
University of Žilina (SK)
Openalex Percentile: Top 59%
Traffic Prediction and Management Techniques
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Efficient Dataset Creation for MEMS-Based Magnetic Sensor Systems in Intelligent Transportation Applications — Michal Hodoň, Andrea Kociánová, et al. · Sensors (2025) | TGRS Research Map | TGRS