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Vehicle Classification Based on FBG Sensor Arrays Using Neural Networks.

Michal Frniak1, Miroslav Markovic1, Patrik Kamencay1

  • 1Faculty of Electrical Engineering and Information Technology, University of Zilina, 01026 Zilina, Slovakia.

Sensors (Basel, Switzerland)
|August 14, 2020
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Summary
This summary is machine-generated.

This study introduces an AI-powered system using fiber Bragg grating sensor arrays and neural networks for automatic vehicle classification. The system accurately identifies trucks and categorizes vehicles, aiding in traffic data analysis.

Keywords:
FBGartificial intelligencesmart sensorsvehicle classification

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Area of Science:

  • Engineering
  • Computer Science
  • Transportation Science

Background:

  • Increasing data from sensor systems necessitates advanced solutions.
  • Artificial intelligence (AI) offers a promising approach for data analysis and classification.
  • Automatic vehicle classification is crucial for traffic management and data verification.

Purpose of the Study:

  • To develop and evaluate an AI-based system for automatic vehicle classification using optical sensor arrays.
  • To verify sensor data with AI-driven visual classification.
  • To propose a novel neural network for vehicle classification from sensor array datasets.

Main Methods:

  • An experimental platform with horizontally and vertically oriented fiber Bragg grating (FBG) sensor arrays was established in pavement layers.
  • Interrogators measured pavement deformation caused by passing vehicles.
  • A neural network was employed for visual vehicle classification using closed-circuit television (CCTV) camera data.
  • A new neural network was developed for classifying vehicles based on FBG sensor data.

Main Results:

  • The proposed neural network achieved 94.9% accuracy in separating trucks from other vehicles.
  • The system classified vehicles into three distinct classes with 70.8% accuracy.
  • AI-driven classification effectively verified data from the FBG sensor arrays.

Conclusions:

  • The developed AI system demonstrates high accuracy in vehicle classification, particularly for trucks.
  • Extending the use of FBG sensor arrays is recommended for enhanced traffic monitoring.
  • This approach offers a progressive solution for handling large volumes of sensor data in transportation.