Vol 14 Issue 1 April 2026-September 2026

Abstract: Accurate, continuous vehicle traffic data is fundamental to evidence-based road pavement design, yet conventional manual counting methods remain incapable of meeting this need in high-density traffic corridors such as the Nsukka–Enugu Road in southeastern Nigeria. This paper presents the design, implementation, and evaluation of an end-to-end Vehicle and Number Plate Recognition (VNPR) system that integrates YOLOv8 Convolutional Neural Network detection, EasyOCR optical character recognition (OCR), OpenCV-based image preprocessing, and Supabase PostgreSQL cloud database management to automate real-time vehicle identification and traffic logging. The system was trained on a combined dataset of 12,746 annotated images (Kaggle open repository and field-collected images from the Nsukka–Enugu Road corridor) and validated using Levenshtein distance-based character accuracy metrics. The complete software pipeline — from frame acquisition and preprocessing through bounding-box detection, plate cropping, OCR extraction, and database insertion — is described in architectural detail. OCR evaluation on standard test images yielded perfect exact-match accuracy (1.0) in optimal conditions, with systematic character confusion errors (0/O, 1/I, 5/S) identified as the dominant failure mode under live traffic conditions. Traffic records collected through the system were applied to compute Average Daily Traffic (ADT) and Equivalent Single Axle Loads (ESALs) per the Nigerian Highway Manual, yielding a 20-year cumulative ESAL of 10,974 and informing a three-layer pavement specification comprising lime-stabilised subgrade, 200 mm granular base, and 100 mm dense-graded asphalt. A companion mobile application supporting real-time tracking, cross-checking, and database interaction completes the system. The architecture and findings presented are directly transferable to road infrastructure planning in Nigeria and similarly resource-constrained traffic environments.

Keywords: YOLOv8; EasyOCR; OpenCV; vehicle number plate recognition; deep learning; Supabase PostgreSQL; road pavement design; ESAL; Nsukka–Enugu Road; Nigeria.

Title: An Integrated System for Vehicle and Number Plate Identification Using Deep Learning and Database Management for Enhanced Road Pavement Design: Architecture, Implementation, and Evaluation on the Nsukka–Enugu Road, Nigeria

Author: Oyesanya Oluwatosin Gabriel

International Journal of Civil and Structural Engineering Research  

ISSN 2348-7607 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 46-56

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Published Date: 15-June-2026

Abstract: Traffic congestion in urban and regional transportation networks represents a critical challenge affecting economic productivity, environmental sustainability, and quality of life. Recent advances in spatiotemporal deep learning have enabled sophisticated predictive models capable of capturing complex dependencies in traffic data across both spatial and temporal dimensions. This paper provides a comprehensive examination of spatiotemporal deep learning methodologies applied to predictive congestion management, synthesizing recent developments in graph neural networks, recurrent architectures, attention mechanisms, and hybrid frameworks. The analysis encompasses architectural innovations including spatiotemporal graph convolutional networks, graph attention networks, temporal point processes, and physics-guided neural networks. Empirical evidence from benchmark datasets demonstrates that these approaches achieve substantial improvements in prediction accuracy compared to traditional methods, with mean absolute percentage errors frequently below 5% for short-term forecasting horizons. However, significant challenges persist, including performance degradation during congested periods, computational complexity for large-scale networks, and limited model interpretability. The synthesis reveals that hybrid architectures combining multiple spatiotemporal modeling paradigms consistently outperform single-method approaches. Future research directions include enhanced interpretability mechanisms, real-time deployment optimization, integration of multimodal transportation data, and development of adaptive models capable of maintaining accuracy during extreme congestion events.

Keywords: spatiotemporal deep learning, traffic congestion prediction, graph neural networks.

Title: Spatiotemporal Deep Learning for Predictive Congestion Management in Urban and Regional Transportation Networks

Author: Oghenerunor Angel Ederewhevbe, Ejemen Obozokhae

International Journal of Civil and Structural Engineering Research  

ISSN 2348-7607 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 35-45

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Website: www.researchpublish.com

Published Date: 03-June-2026

Abstract: The growing demand for durable, high-performance, and sustainable infrastructure has driven the development of advanced construction materials and intelligent systems. This paper examines the role of smart materials in civil engineering, with a particular focus on self-healing concrete, structural health monitoring (SHM) systems, and conductive cement-based composites. It explores the theoretical foundations behind these technologies, highlighting their ability to enhance structural performance, extend service life, and reduce maintenance requirements. Self-healing concrete is analyzed in terms of its biological inspiration and mechanisms such as microbial activity, microcapsules, and autogenous healing processes. In parallel, SHM systems are discussed as a shift from traditional reactive maintenance to predictive, data-driven approaches through the integration of advanced sensors and real-time analysis. Additionally, the paper reviews conductive cement composites and their self-sensing capabilities based on the piezoresistive effect. Overall, the study demonstrates how the integration of smart materials and intelligent monitoring systems contributes to the evolution of adaptive and resilient infrastructure, while also identifying current challenges related to long-term performance and practical implementation.

Keywords: sustainable infrastructure, intelligent systems, civil engineering, structural health monitoring (SHM).

Title: Advanced Technologies and Smart Materials for Enhancing Structural Durability and Lifecycle Performance in Construction

Author: JUMAH EID BIN OBAID, Jasem Bouarki

International Journal of Civil and Structural Engineering Research  

ISSN 2348-7607 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 29-34

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Website: www.researchpublish.com

Published Date: 25-April-2026

Abstract: This study explores the use of Carbon Fiber Reinforced Polymer (CFRP) in strengthening concrete structures. It highlights CFRP’s high strength-to-weight ratio, corrosion resistance, and ease of application, making it an effective solution for enhancing structural performance and extending the lifespan of concrete elements

Keywords: Carbon Fiber Reinforced Polymer (CFRP), strengthening concrete structures.

Title: Diagnosis and Treatment of Structural Defects in Reinforced Concrete Structures and Their Role in Achieving Sustainability and Extending Service Life

Author: JUMAH EID BIN OBAID, Jasem Bouarki

International Journal of Civil and Structural Engineering Research  

ISSN 2348-7607 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 21-28

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Website: www.researchpublish.com

Published Date: 24-April-2026

Abstract: This study examines the effectiveness of carbon fiber reinforced polymer (CFRP) in strengthening reinforced concrete elements. It highlights the material’s high tensile strength, lightweight properties, and resistance to corrosion, which improve overall structural performance. The results show that CFRP significantly enhances flexural and shear capacity, reduces crack propagation, and increases load-bearing capacity while providing a more ductile and safer failure mode. Overall, CFRP is an effective solution for extending the service life of concrete structures.

Keywords: carbon fiber reinforced polymer (CFRP), high tensile strength, concrete structures.

Title: Effectiveness of Using Carbon Fiber in Strengthening Concrete Elements

Author: JUMAH EID BIN OBAID, Jasem Bouarki

International Journal of Civil and Structural Engineering Research  

ISSN 2348-7607 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 15-20

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Website: www.researchpublish.com

Published Date: 24-April-2026

Abstract: Soil properties are the main determinants of the safety and sustainability of any structure that is built.  This article explores the definition, objectives, importance, methods and the effects of soil testing on construction. The main soil testing techniques discussed are field testing (e.g. manual and mechanical boring), laboratory testing (e.g. particle size analysis) and geophysical testing (e.g. seismic wave testing).These tests influence the selection of the type of foundations used, the special processing methods that may be required to improve the safety and sustainability of the building, the identification of environmental risks (e.g. groundwater). The two case studies discussed in this article showcase the significance of soil testing which juxtaposes the preparation of the Burj Khalifa prior to construction with the lack of preparedness in the India case study where the building fell due to the presence of groundwater. This article will also illustrate the different challenges (e.g. limited availability of expertise) in soil testing and compare them to possible solutions (raising awareness for soil testing).  The article concludes by advocating the necessity of implementing soil testing techniques prior to construction.

Keywords: soil testing; foundation design; bearing capacity; construction safety; building collapse.

Title: The Importance of Soil Testing Prior to Construction

Author: JUMAH EID BIN OBAID, Jasem Bouarki

International Journal of Civil and Structural Engineering Research  

ISSN 2348-7607 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 12-14

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Website: www.researchpublish.com

Published Date: 24-April-2026

Abstract: Concrete foundations are among the most important elements used in stabilizing structures, as they transfer loads to the soil layer, ensuring the stability of the structure over long periods. However, this is influenced by numerous environmental and geotechnical factors, the most significant of which is groundwater, considered the most influential and problematic factor in foundation engineering.

According to recent studies, groundwater not only affects the physical properties of the soil but also influences chemical reactions within the concrete, negatively impacting its mechanical properties over time.

Keywords: groundwater, Concrete foundations, stabilizing structures, geotechnical factors.

Title: The effect of groundwater on concrete foundations

Author: Jumah Eid BinObaid, MESHAL ALBZAIE

International Journal of Civil and Structural Engineering Research  

ISSN 2348-7607 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 7-11

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Website: www.researchpublish.com

Published Date: 23-April-2026

Abstract: Cement is a fundamental building material used in concrete production to bind various components such as sand and gravel. It is characterized by its ability to react with water to form a solid material that gives structures strength and rigidity. Various types of cement are used in different applications depending on the required properties, such as ordinary cement, sulfate-resistant cement, and others. With technological advancements, it has become possible to produce new types of cement that contribute to reducing environmental impacts and improving performance. This research will review the definition of cement, its types, components, manufacturing methods, the challenges facing the industry, and future innovations that may contribute to its development.

Keywords: future innovations, cement industry, fundamental building material.

Title: Future challenges and innovations in the cement industry

Author: Jumah Eid BinObaid, MESHAL ALBZAIE

International Journal of Civil and Structural Engineering Research  

ISSN 2348-7607 (Online)

Vol. 14, Issue 1, April 2026 - September 2026

Page No: 1-6

Research Publish Journals

Website: www.researchpublish.com

Published Date: 23-April-2026