The system of headlights operation recognition using the digital twin method

Virtual digital representation of a physical object or system, created with precision through computer simulations, data analysis, and various digital technologies can be used as training set for real life situations. The principal aim behind creating a virtual representation is to furnish a dynamic...

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Main Authors: Aleksander Dawid, Paweł Buchwald
Format: Article
Language:English
Published: Polish Academy of Sciences 2024-03-01
Series:International Journal of Electronics and Telecommunications
Subjects:
Online Access:https://journals.pan.pl/Content/130643/PDF/7-4450-Dawid-sk1.pdf
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author Aleksander Dawid
Paweł Buchwald
author_facet Aleksander Dawid
Paweł Buchwald
author_sort Aleksander Dawid
collection DOAJ
description Virtual digital representation of a physical object or system, created with precision through computer simulations, data analysis, and various digital technologies can be used as training set for real life situations. The principal aim behind creating a virtual representation is to furnish a dynamic, data-fueled, and digital doppelgänger of the physical asset. This digital counterpart serves multifaceted purposes, including the optimization of performance, the continuous monitoring of its well-being, and the augmentation of informed decision-making processes. Main advantage of employing a digital twin is its capacity to facilitate experimentation and assessment of diverse scenarios and conditions, all without impinging upon the actual physical entity. This capability translates into substantial cost savings and superior outcomes, as it allows for the early identification and mitigation of issues before they escalate into significant problems in the tangible world. Within our research endeavors, we've meticulously constructed a digital twin utilizing the Unity3D software. This digital replica faithfully mimics vehicles, complete with functioning headlamp toggles. Our lighting system employs polygons and normal vectors, strategically harnessed to generate an array of dispersed and reflected light effects. To ensure realism, we've meticulously prepared the scene to emulate authentic road conditions. For validation and testing, we integrated our model with the YOLO (You Only Look Once) neural network. A specifically trained compact YOLO model demonstrated impressive capabilities by accurately discerning the status of real vehicle headlamps. On average, it achieved an impressive recognition probability of 80%, affirming the robustness of our digital twin.
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spelling doaj.art-cea4e967ff2d4908be7a3b99698ad6bc2024-03-27T08:10:09ZengPolish Academy of SciencesInternational Journal of Electronics and Telecommunications2081-84912300-19332024-03-01vol. 70No 15158The system of headlights operation recognition using the digital twin methodAleksander DawidPaweł BuchwaldVirtual digital representation of a physical object or system, created with precision through computer simulations, data analysis, and various digital technologies can be used as training set for real life situations. The principal aim behind creating a virtual representation is to furnish a dynamic, data-fueled, and digital doppelgänger of the physical asset. This digital counterpart serves multifaceted purposes, including the optimization of performance, the continuous monitoring of its well-being, and the augmentation of informed decision-making processes. Main advantage of employing a digital twin is its capacity to facilitate experimentation and assessment of diverse scenarios and conditions, all without impinging upon the actual physical entity. This capability translates into substantial cost savings and superior outcomes, as it allows for the early identification and mitigation of issues before they escalate into significant problems in the tangible world. Within our research endeavors, we've meticulously constructed a digital twin utilizing the Unity3D software. This digital replica faithfully mimics vehicles, complete with functioning headlamp toggles. Our lighting system employs polygons and normal vectors, strategically harnessed to generate an array of dispersed and reflected light effects. To ensure realism, we've meticulously prepared the scene to emulate authentic road conditions. For validation and testing, we integrated our model with the YOLO (You Only Look Once) neural network. A specifically trained compact YOLO model demonstrated impressive capabilities by accurately discerning the status of real vehicle headlamps. On average, it achieved an impressive recognition probability of 80%, affirming the robustness of our digital twin.https://journals.pan.pl/Content/130643/PDF/7-4450-Dawid-sk1.pdfdigital twinroad safetyheadlamps operation detectionlighting modelunity 3dyolov7
spellingShingle Aleksander Dawid
Paweł Buchwald
The system of headlights operation recognition using the digital twin method
International Journal of Electronics and Telecommunications
digital twin
road safety
headlamps operation detection
lighting model
unity 3d
yolov7
title The system of headlights operation recognition using the digital twin method
title_full The system of headlights operation recognition using the digital twin method
title_fullStr The system of headlights operation recognition using the digital twin method
title_full_unstemmed The system of headlights operation recognition using the digital twin method
title_short The system of headlights operation recognition using the digital twin method
title_sort system of headlights operation recognition using the digital twin method
topic digital twin
road safety
headlamps operation detection
lighting model
unity 3d
yolov7
url https://journals.pan.pl/Content/130643/PDF/7-4450-Dawid-sk1.pdf
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