Research Article
Deep Learning-based Prediction of Lifespan Degradation in Concrete Bridges Due to Iron Oxidation
Hetkumar Patel
,
Wisam Bukaita*
Issue:
Volume 10, Issue 5, October 2025
Pages:
96-108
Received:
2 September 2025
Accepted:
13 September 2025
Published:
26 September 2025
DOI:
10.11648/j.ajtte.20251005.11
Downloads:
Views:
Abstract: This study presents a comprehensive multimodal deep learning framework for predicting lifespan degradation in concrete bridges caused by iron oxidation. The proposed system integrates YOLOv8 for surface-level crack detection and ResNet50 for deep image feature extraction, combined with structurally significant tabular data such as crack geometry, material composition, environmental factors, and corrosion indicators. Addressing limitations in current approaches-including dataset scarcity, lack of multimodal integration, and high cost of sensor-based inspection-the framework employs a hybrid architecture to estimate three critical outputs: degradation score, condition class, and remaining life of the bridge. To overcome data limitations, synthetic tabular features were generated using AI-based simulations aligned with visual inputs. The system was trained with extensive resources: 200 epochs for YOLOv8 and 50+ epochs for the tabular model, followed by k-fold cross-validation (MAE: 3.48, R²: 0.89) to validate generalization. Despite challenges in detection accuracy (mAP@0.5: 0.0101), the classification component achieved an AUC of 0.98, confirming robustness in condition prediction. Comparative evaluations demonstrate that YOLOv8 and ResNet50 provide the best trade-off between accuracy, efficiency, and deployment readiness. The proposed model, further enhanced with attention mechanisms and future transformer-based extensions, offers a scalable, low-cost alternative to traditional sensor-driven monitoring and contributes to more proactive, data-driven maintenance of aging bridge infrastructure.
Abstract: This study presents a comprehensive multimodal deep learning framework for predicting lifespan degradation in concrete bridges caused by iron oxidation. The proposed system integrates YOLOv8 for surface-level crack detection and ResNet50 for deep image feature extraction, combined with structurally significant tabular data such as crack geometry, m...
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Research Article
Analytical Study of Efficiency of Smart Ports
Hossain Khandakar Akhter*
Issue:
Volume 10, Issue 5, October 2025
Pages:
109-119
Received:
13 July 2025
Accepted:
31 July 2025
Published:
26 September 2025
DOI:
10.11648/j.ajtte.20251005.12
Downloads:
Views:
Abstract: Ports serve as vital hubs for global trade, facilitating the import and export of a vast range of commodities. As the primary interface between nations, ports are integral to the worldwide economy, with over 75% of the world’s trade by value passing through them. Today, ports are regarded as essential capital infrastructure, closely connected with a broad spectrum of economic activities.Smart ports are increasingly transitioning into automated facilities, leveraging advanced digital technologies to boost operational efficiency, transparency, sustainability, and overall competitiveness. These smart and automated ports integrate tools such as sensors, big data analytics, artificial intelligence (AI), machine learning (ML), deep learning (DL), augmented reality (AR), digital twins, and various automation systems to restructure cargo movement, minimize environmental impact, and offer improved services to stakeholdersincluding shipping companies, customs agencies, local communities, and other relevant parties.Furthermore, smart ports often incorporate eco-friendly features such as renewable energy sources, electric vehicle charging stations, onshore power supply, and smart logistics infrastructure. These innovations significantly boost the functionality and responsiveness of port operations, thereby playing a critical role in strengthening national competitiveness.The objective of this study is to develop a conceptual framework to evaluate the effectiveness of smart port in the context of technological advancement. Smart ports will be narrated in contest of how they are utilizing cutting-edge technologies such as AI, ML, DL, blockchain, and data science to enhance efficiency, optimize operations, and maximize profitability. It is an analytical study of smart port.
Abstract: Ports serve as vital hubs for global trade, facilitating the import and export of a vast range of commodities. As the primary interface between nations, ports are integral to the worldwide economy, with over 75% of the world’s trade by value passing through them. Today, ports are regarded as essential capital infrastructure, closely connected with ...
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