Advanced Transportation Systems in the Field of Engineering and Technology

Volume 1
1. Auflage 2026
ISBN: 978-1-032-98369-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 532 Seiten, Format (B × H): 210 mm x 280 mm, Gewicht: 453 g

This book explores the latest advancements in transportation systems through the lens of engineering and technology. It covers innovative solutions that enhance the safety, efficiency, sustainability, and connectivity of modern transportation networks. From intelligent transportation systems and autonomous vehicles to smart infrastructure and high-speed rail, this book offers a comprehensive overview of the technologies shaping the future of mobility worldwide.

The book delves into key areas such as Intelligent Transportation Systems (ITS), autonomous and connected vehicles, electric and alternative fuel technologies, and smart infrastructure. It examines how these innovations contribute to reducing traffic congestion, enhancing road safety, and minimizing environmental impact. Detailed chapters discuss the integration of IoT and AI for real-time data analysis and predictive maintenance, as well as the development of high-speed rail and maglev systems for efficient long-distance travel. Case studies highlight successful implementations worldwide, demonstrating tangible benefits like improved traffic flow, lower emissions, and increased accessibility. The book also addresses challenges including cybersecurity, regulatory frameworks, and infrastructure investment, offering insights into overcoming these barriers to enable widespread adoption of advanced transportation technologies.

This book is designed for engineers, researchers, policymakers, and technology professionals involved in transportation and infrastructure development.

Zielgruppe

Academic and General

Autoren/Hrsg.

Kannadhasan, S.

Sivakumar, P.

Ferede, Anegagregn Gashaw

Tedesse, Abraham Melkie

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Technische Wissenschaften Bauingenieurwesen Bauingenieurwesen
• Technische Wissenschaften Bauingenieurwesen Verkehrsingenieurwesen, Verkehrsplanung
• Technische Wissenschaften Verkehrstechnik | Transportgewerbe Verkehrstechnologie: Allgemeines

Inhaltsverzeichnis

Artificial Intelligence and Machine Learning A fine grained and light weight data access control model for mobile cloud computing; A Predictive analytics approach for pregnant women’s health monitoring using machine learning; A Real-Time Driver Drowsiness Detection System using Eye Aspect Ratio and machine learning; Advancements in 3D spatial intelligence for AI systems; Adversarial Machine Learning for cybersecurity threat detection; AI-Based heart disease progression predictor; AI-driven data integration for mapping and managing habitable environments; AI assistants in computer science education: Instructor perspectives; AI-based real time traffic management system using adaptive traffic light system; AI-controlled water valve based on root zone moisture; AI-driven chicken health monitoring and temperature control; AI for climate change and environmental modeling; AI-based battery thermal monitoring and anomaly detection for electric vehicles; AI-based predictive maintenance in industrial systems; AI-driven cyber risk assessment and insurance models; AI-enhanced personalized learning systems in education; AI-powered cyber attack detection in Industrial IoT using Deep Belief Networks and Convolutional Neural Networks; AI-powered threat detection systems in cybersecurity; Artificial intelligence-based chat bot for patient health care; Autonomous system to enhance urban cleanliness using AI and machine learning; Blockchain technology for supply chain transparency; Blockchain-based secure data sharing in healthcare; Blockchain-based secure voting systems; Brain tumor segmentation and classification on 3D images using deep learning approach; Brain-inspired computing for enhanced human–computer interaction; Brain-inspired computing: Enhancing human–computer interaction; CAD-LC: Deep learning framework using vision transformers and clinical data for lung cancer detection; Convolutional neural network approach for oil spill detection in SAR images; Deep learning for object detection in medical imaging; Deep learning techniques for medical image analysis; Deep learning-driven MRI analysis for accurate Alzheimer’s disease detection; Deep learning-driven seizure prediction using convolutional; Deep neural network optimization for audio and image analysis; Design and development of IoT-enabled AI smart system for roof gardening; Design and testing the prediction of vehicle crash using hybrid ensemble machine learning algorithm; Detecting online payment fraud with machine learning; Developing an intelligent framework for maternal diabetes prediction via machine learning model; Efficient Lightweight Integrated Blockchain (ELIB) for IoT security and privacy; Emotion recognition systems using machine learning; Enhancing AI reasoning through modular architectures; Enhancing CKD diagnosis with machine learning: A predictive approach; Environmental monitoring system empowering users to enhance air quality using smart sensing; Ethical AI and algorithmic fairness in decision-making systems; Evaluating AI models: Towards improved measurement science; Explainable AI: Bridging the gap between models and interpretability; Exploring the role of AI assistants in computer science education; Human-centered responsible AI: Trends and future directions; Innovative approaches to food fusion using AI and machine learning; Investigation of vision transformer algorithm in classification of brain tumor using deep learning; Item enhanced diversification in recommendation systems using graph neural networks; Leveraging smart trolleys and AI for streamlined shopping and intelligent billing; Location-aware retail inventory and product discovery system; Machine learning-based chatbot for bus scheduling in unfamiliar routes; Natural language programming with AI-based no-code platforms; Optimization enabled deep learning technique for lung disease detection and classification; Optimized deep neural network model for analysis and classification of bone marrow biopsies; Optimized machine learning approach for early disease diagnosis: Enhancing precision and healthcare outcomes; Personalised learning path recommendation system using AI and collaborative filtering; Prediction of chronic renal disease using chi-squared relevance vector machine learning classification; Privacy-preserving decentralized identity management on blockchain; Quantum machine learning frameworks for data analysis; Quantum machine learning: Accelerating data processing and pattern recognition; Redefining computer science education with AI-based no-code platforms; Reinforcement-based smart irrigation system; Rice varieties classification using deep learning: A comprehensive analysis; Sales forecasting for optimized supply chain management; Scalable and energy-efficient blockchain systems; Secure authentication and key generation using device ID and blockchain-inspired cryptographic techniques; Smart solar-powered seed sprayer for sustainable framing; StrokeSage deep learning-powered CT stroke classification for clinical insight; The object detection using artificial intelligence; Wellnessworks: An AI-based reward system for employee health and productivity; Cybersecurity and Quantum Technologies Decentralized finance (DeFi) platforms: Security and scalability; Google’s willow: A leap in quantum computing capabilities; Post-quantum cryptography: Preparing for the quantum era; Quantum algorithms for optimization problems in logistics; Quantum computing breakthroughs and renewed investments; Quantum computing simulations for complex system modeling; Quantum computing: Revolutionizing drug discovery and battery development; Quantum cryptography: Enhancing data security in communication networks; Quantum-inspired chaotic image encryption (QICIE) for securing IoT-based surveillance systems; Understanding quantum computing: Principles and applications; Zero trust security models in cloud computing environments; Zero-knowledge proofs: Enhancing data privacy; Healthcare and Biomedical Applications 3D MRI image segmentation using ensemble models; Advanced unmanned aerial vehicle (UAV) with lora communication for combat and tactical warfare; AgroDiagnosis: Plant disease detection and treatment advisor; Automatic testing and inspection system for cable integrity and performance; Crop scarcity risk prediction using LSTM; Efficient real-time object detection with YOLO: Innovations and future directions; Enhancing deepfake detection through hybrid mobilenet: LSTM model with real time image and video analysis; Farm tractor: A mobile application for efficient tractor service management in rural agriculture; Federated learning in healthcare: Collaborative research without data compromise; FieldPlant disease detection and classification using YOLOv8; Gas leakage detection for home and industrial safety; Grasserie disease detection in sericulture using Deeplabv3+ and Resnet-18; Home-based wearable technologies in healthcare and voice assist for stroke patients; Human–Computer Interaction (HCI) in augmented reality environments; Impact of Decentralized Autonomous Organizations (DAO) on society 5.0; Landslide and flood-detection and emergency notification system; Natural language processing for human–computer interaction; Real-time analysis of student engagement in co-curricular and extracurricular activities by proctors; Transfer learning for low-shot object recognition in remote sensing; Underwater acoustic signal denoising using Double Tunable Q-Factor Wavelet Transform (DTQWT); Voice-activated assistants for accessibility in computing; IoT and Smart Systems A multi-camera monitoring system to measuring chicken activity; A real-time road surface monitoring system using mobile sensors and image processing for urban safety; A Smart ADAS system for hazard mitigation and road safety enhancement; Adaptive resource allocation for IoT devices; Agrifreshnet: A smart agriculture E-Marketplace for direct farmer to consumer vegetable trade; Big data analytics in industrial IoT environments; Design and development of personal safety monitoring system for palm plantation workers; Design and development of smart IoT-based health monitoring system for elderly; Edge computing for enhanced web application performance; Edge–cloud collaboration for low latency mobile applications; Feasible IoT device to monitor ECG and PPG signal; Federated edge learning for intelligent IoT systems; Fog computing for real-time IoT analytics; Fog computing models for low-latency data processing; Fuzzy logic-based cluster head selection for wireless sensor networks; Implementing IoT to detect and manage drought in agricultural fields; IoT-based electricity energy monitoring meter; IoT-based energy management in smart grid; IoT-based load control in smart home via mobile app; IoT-based smart water controller for apartment; IoT-based tyre monitoring system; IoT-based smart agriculture systems for precision farming; IoT-Enabled system for smart car parking management; MediBot-IoT-driven healthcare for remote communities; Prescription dispense using smart contracts in Saudi Arabia; Real-time video analytics at the edge; Secure and reliable IoT-based smart grid systems; Smart battery management system for efficient monitoring and performance enhancement; Smart contracts for automated legal agreements; Smart home automation: A comprehensive guide to using blynk for enhanced control and connectivity; Updating point cloud layer of High Definition (Hd) map based on crowdsourcing of multiple vehicles installed lidar; Special Topics Adaptive user interfaces based on real-time user feedback; Advancements in psychophysiological user modeling for real-time adaptable systems; Asset tracking in warehouse using Blu-Fi gateway; Augmented Reality (AR) applications in educational simulations; Biglip: A pipeline for building data sets for lip-reading; Design and deployment of a long-range UAV communication system for battlefield applications; Develop a portal for alumni of college; Enhancing SAP spare parts and materials management through Component-Based Test Automation (CBTA); Fast router in convergent LTE networks using software defined networks based Dynamic Path Optimization Algorithm (DPOA) and Load-Aware Routing Algorithm (LARA); Generative Adversarial Networks (GANs) for image synthesis; Generative models for image synthesis and editing; HRM IN IT: A PHP-based solution for streamlined human resource management; Movie zone reservation system; Multi-control robot vehicle using arduino; Online car rental portal; Optimized decision making for efficient journeys; Optimized single precision floating point multiplier for area and delay efficiency; Optimizing surgery scheduling with a relational database and automated notification; Stablecoins: Financial inclusion and price stability; Vehicle to vehicle communication using image processing and RF technology; Virtual Reality (VR) systems for remote collaboration

Über Autor(innen)

S. Kannadhasan works as an Associate Professor and HoD in the Department of Electronics and Communication Engineering at Study World College of Engineering, Coimbatore, Tamil Nadu, India. He completed his Ph.D. in the field of smart antennas at Anna University in 2022. He has thirteen years of teaching and research experience. He obtained his B.E. in ECE from Sethu Institute of Technology, Kariapatti, in 2009 and his M.E. in Communication Systems from Velammal College of Engineering and Technology, Madurai, in 2013. He obtained his M. B.A. in Human Resources Management from Tamil Nadu Open University, Chennai. He has published around 110 papers in the reputed international journals indexed by SCI, Scopus, Web of Science, and Major Indexing, and more than 250 papers have been presented or published in national and international journals and conferences. Besides, he has also contributed a book chapter. He also serves as a board member, reviewer, speaker, session chair, and member of the advisory and technical committees of various colleges and conferences. He is also to attend the various workshops, seminars, conferences, faculty development programs, STTP, and online courses. His areas of interest are smart antennas, digital signal processing, wireless communication, wireless networks, embedded systems, network security, optical communication, microwave antennas, electromagnetic compatibility and interference, wireless sensor networks, digital image processing, satellite communication, cognitive radio design, and soft computing techniques. He is a member of SMIEEE, ACM, IET, ISTE, FIEI, FIETE, CSI, IAENG, SEEE, IEAE, INSC, IARDO, ISRPM, IACSIT, ICSES, SPG, SDIWC, IJSPR, and the EAI Community.

P. Sivakumar is currently serving as a Professor in the Department of Computer Science and Engineering at Al-Ameen Engineering College. He holds a Ph.D. in Web Mining from Anna University, awarded in 2013. With over fifteen years of experience in teaching and research, Dr. Sivakumar has contributed extensively to the academic community. He earned his B.E. in Information Technology from Sri Ramakrishna Engineering College, Coimbatore, in 2004, followed by an M.E. in Computer Science and Engineering from Annai Mathammal Sheela Engineering College, Namakkal, in 2007. Dr. Sivakumar has published approximately 50 research papers in reputed international journals indexed in SCI, Scopus, and Web of Science. Additionally, he has presented and published more than 40 papers in various national and international conferences and journals.

Anegagregn Gashaw Ferede is an Associate Professor of Teaching English as a Foreign Language at Debre Tabor University, Ethiopia. His research focuses on English pronunciation instruction, second language acquisition, and the influence of learners’ first language—particularly Amharic—on English language learning. Dr. Gashaw’s work contributes to addressing pronunciation challenges faced by Ethiopian EFL learners, with emphasis on both segmental and suprasegmental features of English. Among his notable publications is “Rhythm in Ethiopian English: Implications for the Teaching of English Prosody” (2017), which has been cited for its insights into the prosodic differences between Amharic and English. He has also explored perceptual difficulties in segmental phonemes, consonant cluster acquisition, and problematic pronunciation areas for Amharic-speaking learners. His recent collaborative studies, including “The Effect of Using Google Docs on Ethiopian EFL Students’ Collaborative Writing Improvement” (2025) and “The Effects of Oral Communication Strategy Training to Enhancing Students’ Oral Communication Skills” (2023), reflect his interest in technology-assisted language learning and communicative competence. Dr. Gashaw is committed to enhancing the quality of English language education in Ethiopia through both research and practice, and his work continues to inform teacher training and curriculum development in EFL contexts.

Abraham Melkie Tedesse is an academic administrator and scholar currently serving as the Director of International Relations at Debre Tabor University (DTU), Ethiopia. In this role, he is responsible for coordinating global partnerships, international collaborations, academic exchange programs, and institutional cooperation with universities and research organizations worldwide. He has played an important role in strengthening international academic relations for the university, including facilitating collaborations with international institutions such as Indian Institute of Technology Roorkee and other global universities for research and educational cooperation. Dr. Abraham Melkie has also been involved in research, teaching, and scholarly activities, contributing to studies in language, literature, and cultural research. One of his known academic works is a thesis titled “Thematic and Technical Analysis of Oral Poetry in and around Debre Tabor,” which explores cultural heritage and oral traditions in Ethiopia.