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Applications of Artificial Intelligence Enhanced Drones in Distress Pavement, Pothole Detection, and Healthcare Monitoring with Service Delivery
2022
Journal of Engineering
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Nowadays, computer vision techniques are commonly used in this area utilizing images and videos of construction sites. ...
The distress detection on pavement and roads and delivering healthcare and medical services need to be monitored through state-of-the-art technology, i.e., drone technology. ...
One may also see the segmentation based on a deep learning algorithm and may compare the method with OTSU. ...
doi:10.1155/2022/7733196
fatcat:qwzdd22nwvhzlm6efj6nphaxae
Road Condition Monitoring Using Smart Sensing and Artificial Intelligence: A Review
2022
Sensors
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The majority of these technologies employ next-generation distributed sensors and vision-based artificial intelligence (AI) methodologies to evaluate, classify and localize pavement distresses using the ...
With advancements in computer vision and data mining techniques along with high computing resources, several innovative pavement distress evaluation systems have been developed in recent years. ...
This research is also supported by the Ontario Ministry of Colleges and Universities' Early Researcher Award funding provided to the corresponding author. ...
doi:10.3390/s22083044
pmid:35459034
pmcid:PMC9029655
fatcat:pqrm3lcihzfv5n6ojjvxg7plkq
An Exploration of Recent Intelligent Image Analysis Techniques for Visual Pavement Surface Condition Assessment
2022
Sensors
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We listed approaches focusing on crack segmentation and methods concentrating on distress detection and identification using object detection and classification. ...
More recently, academic research has pivoted toward deep learning, given that image data is now available in some form. ...
Image Processing Techniques Techniques using decision-based rules and image processing mainly focus on crack segmentation and identification. ...
doi:10.3390/s22229019
pmid:36433612
pmcid:PMC9697233
fatcat:lueci4ynijhsfpnwsbks6ysw7e
Research and applications of artificial neural network in pavement engineering: A state-of-the-art review
2021
Journal of Traffic and Transportation Engineering (English ed. Online)
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Three mainstream ANN architectures for different application scenarios were summarized. Five research challenges and prospects of ANN application in pavement engineering were analyzed. ...
h i g h l i g h t s Frontiers of artificial neural network (ANN) in pavement design, construction, inspection and maintenance were reviewed. ...
Acknowledgments This study is supported by the National Natural Science Foundation of China (No. 52078049), Fundamental Research Funds for the Central Universities, CHD (Nos. 300102210302, 300102210118), and ...
doi:10.1016/j.jtte.2021.03.005
fatcat:ocvt2vx5xzgqhfp3udmxog6glq
Asphalt Pavement Potholes Localization and Segmentation using Deep RetinaNet and Conditional Random Fields
2022
International Journal of Innovations in Science and Technology
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To solve this problem, we have proposed a deep learning methodology to automatically detect and segment the pothole region within the asphalt pavement images. ...
There are three steps in our methodology, image preprocessing, Pothole region localization, and Pothole segmentation. ...
ACKNOWLEDGMENT The authors would like to thank Department of Computer Science, University of Engineering and Technology Taxila for R&D support and Christian Koch [1] for providing the dataset. ...
doi:10.33411/ijist/2021030510
fatcat:n3qyb6awhbbljhja6ecyocp7vi
Automatic joint damage quantification using computer vision and deep learning
[article]
2020
arXiv
pre-print
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A framework for the accurate, autonomous, and rapid quantification of joint damage with a low-cost camera is proposed using a computer vision technique with a deep learning (DL) algorithm. ...
The effectiveness of the framework was validated through inspecting joint damage at four transverse contraction joints in Illinois, USA, including three acceptable joints and one unacceptable joint by ...
image with a deep learning (DL) model. ...
arXiv:2010.15303v1
fatcat:pwkkjgdhqfdaxhrzr6eumtxab4
Road pavement crack detection using deep learning with synthetic data
2021
IOP Conference Series: Materials Science and Engineering
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The present work is based on deep learning approach with the use of synthetic generated training data for segmentation of cracks in driver-view image. ...
The relevance of the research is emphasized by processing of wide-view images in which heterogeneous pixel intensity, complex crack topology, different illumination condition and complexity of background ...
Acknowledgment This research was supported by Tomsk Polytechnic University Competitiveness Enhancement Program and was funded by RFBR according to the research project № 18-08-00977 А. ...
doi:10.1088/1757-899x/1019/1/012036
fatcat:es6twr7ernaxvhkn26e5tnjwt4
Bibliometric Analysis and Review of Deep Learning-Based Crack Detection Literature Published between 2010 and 2022
2022
Buildings
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The evolution and state-of-the-art approaches to crack detection using deep learning are reviewed and analyzed based on datasets, network architecture, domain, and performance of each study. ...
To achieve a better understanding of the research work on crack detection using DL approaches, this paper aims to provide a bibliometric analysis and review of the current literature on DL-based crack ...
In [39] , the authors combined deep learning techniques with traditional image processing algorithms for crack detection, localization, and measurement in tunnels. ...
doi:10.3390/buildings12040432
fatcat:mvxp5hte2nab3ah3udjmxgf3ba
Deep Learning in Data-Driven Pavement Image Analysis and Automated Distress Detection: A Review
2018
Data
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While pavement image analysis has been extensively researched over the past three decades or so, recent ground-breaking achievements of deep learning algorithms in the areas of machine translation, speech ...
2D and 3D pavement images. ...
Segmented Grid Based Pavement Crack Classification with DL and PCA Wang and Hu [42] proposed a CNN-based pavement crack classification method by first segmenting the pavement image into grids of different ...
doi:10.3390/data3030028
fatcat:u2g4mniiajgz7ohpeylsrsrsvm
Road Surface Defect Detection – From Image-based to Non-image-based: A Survey
[article]
2024
arXiv
pre-print
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Additionally, we review recently proposed non-image-based methods and discuss several challenges and open problems associated with these techniques. ...
Despite their popularity, image-based methods share the distinct limitation of vulnerability to weather and lighting changes. ...
We then categorise these methods based on their underlying methodologies, including image processing-based, machine learning-based, and deep learning-based methods. ...
arXiv:2402.04297v1
fatcat:ku3aha6lfvc7fe2xxsjonwbkiq
Pavement Crack Detection Method Based on Deep Learning Models
2021
Wireless Communications and Mobile Computing
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Object detection based on the deep learning model has achieved good results in many fields. As a result, those models have become possible for pavement crack detection. ...
model based on machine learning. ...
Paper [22] detected crack pavement by processing the binary image obtained by the connected domain algorithm (directional segmentation expansion algorithm) and got good results. ...
doi:10.1155/2021/5573590
fatcat:qmdmt46po5hfjioxc7vebilbmq
Multiscale and Adversarial Learning Based Semi-Supervised Semantic Segmentation Approach for Crack Detection in Concrete Structures
2020
IEEE Access
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A typical example of this technique is the use of segmentation neural networks based on the auto-encoder type algorithm. ...
Based on the image data, a deep neural network was designed, and skeleton images were generated to measure the crack length. ...
doi:10.1109/access.2020.3022786
fatcat:egjazqmnbrgyfnmljge562czfi
Review of Intelligent Road Defects Detection Technology
2022
Sustainability
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This study focuses on the intelligent detection of road disease and summarizes the commonly used detection equipment in the intelligent detection technology of road diseases, which include cameras, GPR ...
, LiDAR, and IMU. ...
To improve the recognition speed and recognition rate of highway pavement crack automatic detection and recognition technology based on digital image processing technology, Xiao et al. ...
doi:10.3390/su14106306
fatcat:ok2syuobirgojbjkyihczexiw4
Crack45K: Integration of Vision Transformer with Tubularity Flow Field (TuFF) and Sliding-Window Approach for Crack-Segmentation in Pavement Structures
2022
Buildings
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Recently, deep-learning (DL)-based crack-detection systems have proven to be the method of choice for image processing-based inspection systems. ...
The experimental results show that ViT equipped with a sliding-window and the TuFF algorithm can enhance real-world crack classification, localization, and segmentation performance. ...
[49] proposed TuFF, a technique for segmenting filamentous structures in digital images. The TuFF algorithm generates segmentation maps by using a level set. ...
doi:10.3390/buildings13010055
fatcat:5q63vzvzcbfxlie4umqxjudbnq
Infrastructure BIM Platform for Lifecycle Management
2021
Applied Sciences
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The lifecycle management methodology, after infrastructure construction, is then completed and is developed using state-of-the-art techniques using unmanned robots, scan-to-BIM, and deep learning networks ...
inspection database based on an infrastructure BIM platform. ...
Hoang et al. also confirmed that deep learning-based pavement crack detection performs better than image processing methods [49] . ...
doi:10.3390/app112110310
fatcat:3z2igcebuvfmvjibwxma3kvxoa
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