Article
Construction & Building Technology
Raheb Hafezzadeh, Federico Autelitano, Felice Giuliani
Summary: This study focuses on the evaluation of the performance of cold mix patching materials (CMPMs) by proposing innovative solutions derived from pre-existing methodologies. The research identifies several parameters indicative of CMPMs' structural and functional performance, optimizing the mix design and quality assurance/ quality control (QA/QC) process. The findings suggest that new testing methods, such as Hubbard-Field and indentation stability tests, provide more accurate stability assessments for CMPMs. Additionally, customized test methods for raveling potential, bonding properties, and workability enhance the relevance of laboratory findings to practical applications.
CASE STUDIES IN CONSTRUCTION MATERIALS
(2023)
Article
Green & Sustainable Science & Technology
Sharaf AlKheder
Summary: This study aims to investigate the feasibility of using recycled asphalt pavement in hot mix asphalt design. Through questionnaires and laboratory tests, it was found that the recycled mixture has high stability and flow, and a lower rutting depth compared to the regular mixture. The recycled mixture also has lower voids filled with asphalt and voids in mineral aggregate, saving costs and improving maintenance activities for potholes.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2022)
Article
Chemistry, Analytical
Nengsheng Bao, Yuchen Fan, Zihao Ye, Alessandro Simeone
Summary: This paper proposes an automatic inspection system based on machine vision for detecting colorless fluid effusion in industrial pipework maintenance. By utilizing the reflective characteristics and lower temperature of the effusion, the system achieves a classification accuracy of up to 99%, demonstrating excellent suitability for industrial requirements.
Article
Engineering, Electrical & Electronic
Shubham Aggarwal, Shreyas Pranav, Mukund Lahoti, Ajit Pratap Singh, Nishant Roy
Summary: This article discusses an improved model based on CNN for pothole recognition, introducing a new neural architecture called LPS-CNN. By learning a sparse neural network architecture, the proposed model achieves exceptional accuracy while maintaining reasonable processing time.
JOURNAL OF ELECTRONIC IMAGING
(2022)
Article
Engineering, Multidisciplinary
J. Eastwood, R. K. Leach, S. Piano
Summary: This paper presents a method to autonomously remove the background from photogrammetric images, resulting in lower data processing times, reduced memory usage, and increased point density on the object surface. Experimental results show that the reconstructions with the background removed have a lower standard deviation in point to mesh distance, indicating improved measurement accuracy.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2023)
Article
Construction & Building Technology
Xiaolong Wu, Jun Zhang, Yize Xie, Ming Yao, Zhiguo Jiang
Summary: Timely repair of potholes is important to control pavement deterioration and minimize traffic adverse impacts. In this study, a series of fast-curing two-component polyurethane (PU) binders with varying hard segment content (HSC) were prepared and used to prepare PU mixtures (PUMs) through mixing with aggregates. The results showed that the prepared PUs had good mechanical properties and water resistance, with increased tensile strength and stability with higher HSC content. However, the raveling resistance deteriorated with increasing HSC.
JOURNAL OF MATERIALS IN CIVIL ENGINEERING
(2023)
Article
Construction & Building Technology
Penghui Wang, Qingyi Xiang, Yongbiao Hu, Mingrui Tian
Summary: A contour-guided zigzag path planning method based on depth image was proposed for automated pavement pothole spraying repair. The results showed that the method achieved high path planning accuracy and fast speed, making it suitable for repairing potholes with different shapes.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2023)
Article
Materials Science, Multidisciplinary
Nithinan Hemnithi, Preeda Chaturabong
Summary: Moisture is a significant problem in pavements, causing deterioration of asphalt mixtures due to poor water permeability. The relationship between permeability and aggregate contact length is believed to be inverse. This study used laboratory experiments and IPAS to assess water permeability performance and moisture damage, and found that AC60/70, AC60/70+Carbon Black, and AC60/70+SBS combinations with coconut peat filler had the lowest permeability coefficient. The number of contact points and contact length strongly influenced the permeability of the asphalt mixtures.
Article
Automation & Control Systems
Andrii Hrechuk, Mikael Horndahl, Fredrik Schultheiss
Summary: This paper develops a research solution for automatic analysis of the hole quality in drilled fiber-reinforced materials. The proposed solution includes a vacuum table, robot arm with high-speed camera, developed lightning systems, and Image Processing algorithms. The results show that the developed solution can achieve an efficiency of 5 seconds per hole including drilling and full cycle of measurements, with a measurement error of 1-3%.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Chemistry, Multidisciplinary
Abdullah Al-Mansour, Kang-Won Wayne Lee, Abdulraaof H. Al-Qaili
Summary: Predicting pavement performance over time is crucial for pavement maintenance management system. This study developed an expert system based on pavement performance models to aid in selecting the most effective and efficient maintenance strategies. The regression models showed that routine maintenance and reconstruction have greater effects in low traffic, while overlay is more effective in high traffic. Further improvement can be achieved using the machine learning technique.
APPLIED SCIENCES-BASEL
(2022)
Review
Construction & Building Technology
Nima Sholevar, Amir Golroo, Sahand Roghani Esfahani
Summary: This study reviews the latest techniques in pavement condition data evaluation using machine learning methods, specifically focusing on the application of image classification, object detection, and segmentation in pavement distress assessment. The study also evaluates pavement automated data collection tools and condition indices from the perspective of machine learning applications. The review concludes that the overall trend in pavement condition evaluation is to apply machine learning techniques, although there are some limitations in detecting certain pavement distresses with complex patterns and indicating the severity and density of distresses, which warrant further research.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Engineering, Civil
Ahmed Abed, Mujib Rahman, Nick Thom, David Hargreaves, Linglin Li, Gordon Airey
Summary: This study analyzes the formation of potholes and their relationship with other distress types and severity, and develops a simple tool to predict the number of potholes that might appear in a road network based on the network condition. The results demonstrate that potholes are significantly concentrated in sections with deteriorated conditions and it is possible to predict the number of potholes using spatial density as a function of different condition indicators.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Engineering, Multidisciplinary
Fengjun Zhao, Yuhang Tang, Jianjun Wu, Zhi Huang, Mingyue Gao, Yanliang Long
Summary: This paper determines the most unfavorable loading position in pothole repair on asphalt pavement using a finite element model, and analyzes the stress conditions on patch materials, joint filling materials, and leveling layers at these positions, providing a basis for overcoming difficulties in asphalt pavement maintenance.
JOURNAL OF ENGINEERING
(2021)
Article
Environmental Sciences
Danyu Wang, Zhen Liu, Xingyu Gu, Wenxiu Wu, Yihan Chen, Lutai Wang
Summary: In this study, an improved YOLOv3 object detection model was proposed for intelligent and accurate measurement of pavement surface potholes. By combining data augmentation and structure optimization, the proposed model showed significant improvement compared to the original YOLOv3 model and demonstrated good robustness.
Article
Construction & Building Technology
Zihang Weng, Hui Xiang, Yuchao Lin, Chenglong Liu, Difei Wu, Yuchuan Du
Summary: Texture depth, a fundamental indicator for pavement performance, is traditionally obtained by time-consuming measurements. This study applies the image-based multiscale features for texture depth estimation and proposes two new features, maximum particle size distribution (MPSD) and relative energy distribution (RED). The random forest model yields the best results in terms of performance.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Engineering, Electrical & Electronic
Senthan Mathavan, Kanapathippillai Vaheesan, Akash Kumar, Chanjief Chandrakumar, Khurram Kamal, Mujib Rahman, Martyn Stonecliffe-Jones
JOURNAL OF ELECTRONIC IMAGING
(2017)
Article
Engineering, Mechanical
T. Zafar, K. Kamal, Z. Sheikh, S. Mathavan, U. Ali, H. Hashmi
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
(2017)
Article
Engineering, Civil
Maher Mahmood, Mujib Rahman, Senthan Mathavan
PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-TRANSPORT
(2019)
Article
Computer Science, Artificial Intelligence
Maher Mahmood, Senthan Mathavan, Mujib Rahman
SWARM AND EVOLUTIONARY COMPUTATION
(2018)
Article
Engineering, Electrical & Electronic
Muhammad Uzair Ul Haq, Moeez Ashfaque, Senthan Mathavan, Khurram Kamal, Adeel Ahmed
IEEE SENSORS JOURNAL
(2019)
Article
Engineering, Civil
Adeel Ahmed, Moeez Ashfaque, Muhammad Uzair Ulhaq, Senthan Mathavan, Khurram Kamal, Mujib Rahman
Summary: Machine vision based evaluation systems for automated quality inspection of roads are gaining attention. A novel approach using Structure from Motion 3D reconstruction algorithm and laser triangulation to generate 3D point clouds of potholes, as well as a low-cost system, has been proposed. Scale ambiguity is solved using the principle of triangulation with a laser pointer.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Agriculture, Multidisciplinary
S. Imran Moazzam, Umar S. Khan, Waqar S. Qureshi, Mohsin I. Tiwana, Nasir Rashid, Amir Hamza, Faraz Kunwar, Tahir Nawaz
Summary: This study aims to use drone-assisted autonomous spraying to prevent weed-induced yield reduction in sesame crops. An intelligent convolutional neural network and a patch image-based classification method are used to identify weeds and crops in the sesame fields. Through dataset grouping and patch-based model ensemble, this approach improves classification accuracy and outperforms traditional methods in terms of time efficiency.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Computer Science, Information Systems
S. Imran Moazzam, Umar S. Khan, Waqar S. Qureshi, Mohsin Tiwana, Nasir Rashid, Waleed S. Alasmary, Javaid Iqbal, Amir Hamza
Summary: Weeds can affect crop health by reducing yield, but using airborne multispectral camera sensors can aid in weed detection in sugar beet crops. A new VGG-Beet CNN model was developed for classifying crop and weed patches, showing higher accuracy compared to semantic segmentation networks.
Proceedings Paper
Automation & Control Systems
Syed I. Moazzam, Umar Shahbaz Khan, Mohsin Islam Tiwana, Javed Iqbal, Waqar S. Qureshi, Syed Irfan Shah
2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION IN INDUSTRY (ICRAI)
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
M. Usman, K. Kamal, R. Qayyum, S. Akram, S. Mathavan
2017 IEEE 2ND INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP)
(2017)
Article
Computer Science, Artificial Intelligence
K. Kamal, R. Qayyum, S. Mathavan, T. Zafar
ADVANCED ENGINEERING INFORMATICS
(2017)
Proceedings Paper
Engineering, Manufacturing
Chanjief Chandrakumar, Asela K. Kulatunga, Senthan Mathavan
SUSTAINABLE DESIGN AND MANUFACTURING 2017
(2017)
Proceedings Paper
Green & Sustainable Science & Technology
H. M. M. M. Jayawickrama, A. K. Kulatunga, S. Mathavan
14TH GLOBAL CONFERENCE ON SUSTAINABLE MANUFACTURING, GCSM 2016
(2017)
