Optimized Real-Time Decision Making with EfficientNet in Digital Twin-Based Vehicular Networks

Electronics, Journal Year: 2025, Volume and Issue: 14(6), P. 1084 - 1084

Published: March 9, 2025

Real-time decision-making is vital in vehicular ad hoc networks (VANETs). It essential to improve road safety and ensure traffic efficiency flow. Integrating digital twins within VANET (DT-VANET) creates virtual replicas of physical vehicles, allowing in-depth analysis effective decision-making. Many network applications now use convolutional neural (CNNs). However, the growing model size latency make implementing them real-time systems challenging, most previous studies focusing on using CNNs still face significant challenges. Some models with sustainable performances have recently been proposed. One advanced among EfficientNet. may consider it a family significantly fewer parameters computational costs. This paper proposes EfficientNet-based optimized DT-VANET architecture. investigates performance EfficientNet digital-based networks. Extensive experiments proved that outperforms CNN (ResNet50, VGG16) accuracy, latency, efficiency, convergence time, which proves its effectiveness DT-VANET.

Language: Английский

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Secure lightweight digital twin (DT) technology for seamless wireless communication in vehicular ad hoc network

Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 123, P. 110291 - 110291

Published: April 1, 2025

Language: Английский

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Mel-Scale Frequency Extraction and Classification of Dialect-Speech Signals With 1D CNN Based Classifier for Gender and Region Recognition

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 102962 - 102976

Published: Jan. 1, 2024

Humans communicate and interact through natural languages, such as American English (AE), Taiwanese, Italian, numerous variants of Spanish. Through automatic speech analysis recognition technologies, human-machine interaction systems (HMISs) can be used for language learning in query systems, smart devices, healthcare applications, emphasizing the need to enhance user across different sectors. Because people differ their basic attributes (e.g., gender, age group, spoken dialect), an HMIS must able identify speaker's regional dialect on basis signals. To achieve recognition, we analyzed distinguished feature patterns using a extraction method identified gender region convolutional neural network (CNN)-based classifier. Mel-frequency cepstral coefficients were extract Mel-scale frequencies (MSF) from dialect-sentence signals conversion into specific patterns. Subsequently, one-dimensional CNN-based classifier was these features by dialect. The proposed rigorously trained, tested, validated corpora AE, Italian (IT), Spanish (SP) acoustic-phonetic continuous database. experimental results indicate that model with MSF perform accurate recognition. evaluated metrics precision (%), recall F1 score, accuracy (%).

Language: Английский

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One Health Ecological Approach to Sustainable Wireless Energy Transfer Aboard Electric Vehicles for Smart Cities

Energies, Journal Year: 2024, Volume and Issue: 17(17), P. 4349 - 4349

Published: Aug. 30, 2024

This investigation is part of a topical situation where wireless equipment gradually being used for energy transfer, particularly autonomous systems and the use decarbonized energies. A characteristic example linked to substitution thermal engine vehicles electric (EVs) equipped with storage batteries. response was considered in an ecological context reducing air pollution defending planetary biodiversity, which are currently vital. These EVs ultimately operate thanks charging their batteries when stationary or running. By changing long-established means transport that have become threat it necessary ensure innovative replacement solutions protect this biodiversity. In addition, construction power transfer (WPT) battery chargers these must offer optimal ecology clean saving. such context, two concepts One Health (OH) Responsible Attitude (RA) will find place design control WPT tools EVs. contribution aims illustrate analyze roles green non-wasteful OH RA approaches embedded smart city (SC) environment. paper, first introduced. The EV then examined. biological effects on living tissues due electromagnetic field (EMF) radiation analyzed. phenomena equations governing EMF exposed. SC afterward protection against unsafe environment consequently explored. analyses followed paper supported by examples from literature. explorations proposed made possible highlight certain notions, allowing more in-depth understanding rechargeable SCs. Thus, analysis fusion topics at heart contribution.

Language: Английский

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