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A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: closed (28 October 2024) | Viewed by 35836

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Special Issue Editors

Dr. Sungjin Kim

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Guest Editor

Department of Architectural Engineering, Hanbat National University, Daejeon 34158, Korea
Interests: smart construction; robotics and automation; sustainable infrastructure; human technology interaction; building information modeling; data-driven decision making; impact and performance assessment

Dr. Javier Irizarry

E-Mail Website
Guest Editor

School of Building Construction, Georgia Institute of Technology, 280 Ferst Dr., Atlanta, GA 30332, USA
Interests: construction safety; HCI issues in mobile applications for AEC information access; situation-awareness-driven information system design; interactive visualization systems for AEC education; role-based decision support systems; unmanned aerial systems applications in AEC

Special Issue Information

Dear Colleagues,

Unmanned aircraft systems (UASs), commonly called “drones”, have been widely used in the construction jobsite. In the workspace, construction or project managers are in charge of managing the construction tasks in terms of time, money, quality, and safety. They usually monitor and inspect site conditions and situations for completing the project successfully. The UAS can help managers to make decisions more efficiently by flying over the site and collecting and transferring visual data. Since UASs can carry various sensors (e.g., camera, GPS, Lidar), they can provide various types of visual data through pre-/post-data processing (e.g., image processing or computer vision techniques). Since UASs produce visual data, they can be integrated with other technologies (e.g., robots, augmented/virtual realities) or building information modeling (BIM) for enhancing the level of autonomy, productivity, efficiency, and safety in the construction environment.

In this context, this Special Issue invites research papers demonstrating innovative developments in applying UASs to construction management tasks. Papers are welcome in the field of computer vision and image processing with UASs, navigation systems, integrating with the BIM, simulations, and decision making and process mapping with the UAS in any type of construction domains (e.g., road, bridge, buildings).

Dr. Sungjin Kim
Dr. Javier Irizarry
Guest Editors

Manuscript Submission Information

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Keywords

unmanned aircraft system (UAS)
unmanned aerial vehicle (UAV)
drone
computer vision
image processing
construction management
built environment
building information modeling (BIM)

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Published Papers (10 papers)

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Research

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22 pages, 4422 KiB

Open AccessArticle

CrackScopeNet: A Lightweight Neural Network for Rapid Crack Detection on Resource-Constrained Drone Platforms

by Tao Zhang, Liwei Qin, Quan Zou, Liwen Zhang, Rongyi Wang and Heng Zhang

Drones 2024, 8(9), 417; https://doi.org/10.3390/drones8090417 - 23 Aug 2024

Viewed by 996

Abstract

Detecting cracks during structural health monitoring is crucial for ensuring infrastructure safety and longevity. Using drones to obtain crack images and automate processing can improve the efficiency of crack detection. To address the challenges posed by the limited computing resources of edge devices in practical applications, we propose CrackScopeNet, a lightweight segmentation network model that simultaneously considers local and global crack features while being suitable for deployment on drone platforms with limited computational power and memory. This novel network features a multi-scale branch to improve sensitivity to cracks of varying sizes without substantial computational overhead along with a stripe-wise context attention mechanism to enhance the capture of long-range contextual information while mitigating the interference from complex backgrounds. Experimental results on the CrackSeg9k dataset demonstrate that our method leads to a significant improvement in prediction performance, with the highest mean intersection over union (mIoU) scores reaching 82.12%, and maintains a lightweight architecture with only 1.05 M parameters and 1.58 G floating point operations (FLOPs). In addition, the proposed model excels in inference speed on edge devices without a GPU thanks to its low FLOPs. CrackScopeNet contributes to the development of efficient and effective crack segmentation networks suitable for practical structural health monitoring applications using drone platforms. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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21 pages, 11858 KiB

Open AccessFeature PaperArticle

Evaluation of Fissures and Cracks in Bridges by Applying Digital Image Capture Techniques Using an Unmanned Aerial Vehicle

by Eric Forcael, Oswal Román, Hayan Stuardo, Rodrigo F. Herrera and Jaime Soto-Muñoz

Drones 2024, 8(1), 8; https://doi.org/10.3390/drones8010008 - 30 Dec 2023

Cited by 2 | Viewed by 2097

Abstract

The evaluation of cracks and fissures in bridge structures is essential to ensure the long-term safety, durability, and functionality of these infrastructures. In this sense, processing grayscale images and adjusting brightness and contrast levels can improve the visibility of cracks and fissures in bridge structures. These techniques, complemented by professional expertise and efficient inspection tools such as Unmanned Aerial Vehicles (UAVs), allow for a comprehensive and accurate structural integrity assessment. This study used the edge detection technique to analyze photographs obtained with a low-cost UAV as a means of image capture. This tool was used to reach hard-to-reach areas where there could be damage, thus making it easier to detect fissures or cracks. To capture the failures, two case studies, a small bridge and a large bridge, were selected, both located in Concepción City in southern Chile. During both inspections, cracks were detected that could affect the structure of the bridges in the future. To analyze these findings, ImageJ software 1.54h was used, which allowed the length and thickness of the cracks to be measured and evaluated. In addition, to validate the procedure proposed, real values manually measured on-site were compared with those delivered by the software analyses, where no statistically significant differences were found. With the method presented in this study, it was possible to quantify the damage, following the bridge maintenance standards established by the Ministry of Public Works of Chile, whose inspection criteria can be applied to other projects worldwide. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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17 pages, 7171 KiB

Open AccessFeature PaperArticle

Automated Pavement Construction Inspection Using Uncrewed Aerial Systems (UAS)—Hot Mixed Asphalt (HMA) Temperature Segregation

by Reihaneh Samsami, Amlan Mukherjee and Colin N. Brooks

Drones 2023, 7(7), 419; https://doi.org/10.3390/drones7070419 - 24 Jun 2023

Cited by 2 | Viewed by 1701

Abstract

Temperature segregation in Hot Mixed Asphalt (HMA) pavement construction leads to performance problems, such as reduced fatigue life. During construction, Quality Assurance (QA) inspection procedures are required to evaluate the pavement condition and detect the segregated areas. In traditional HMA highway construction inspection processes, temperature differences are investigated manually, by sampling the HMA behind the paver. In these processes, inspectors are required to work adjacent to traffic and alongside moving or backing equipment. These processes do not provide a complete temperature profile of the mat, endanger the inspectors’ safety, and require on-site experienced inspectors. An Uncrewed Aerial System (UAS) enables HMA pavement construction inspection to be conducted within a remote, non-destructive, safe, and efficient framework. The objective of this research is to design an automated UAS imaging workflow for HMA pavement construction inspection, mainly locating temperature segregation. The primary contribution of this paper is to provide Departments of Transportations (DOTs) and contractors with workflows for creating enhanced remote inspection procedures and detailed thermal profiles of the placed HMA mat. The application of the proposed workflow is illustrated using an HMA construction project in Michigan. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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22 pages, 4649 KiB

Open AccessArticle

Developing the Framework of Drone Curriculum to Educate the Drone Beginners in the Korean Construction Industry

by Seojin Moon and Jongho Ock

Drones 2023, 7(6), 356; https://doi.org/10.3390/drones7060356 - 28 May 2023

Cited by 4 | Viewed by 2542

Abstract

Both drones and laser scanners digitally take the as-built context of an object into the computer, and the data taken are transmitted to a Building Information Modeling (BIM) world to create accurate 3D models. Although the laser scanner is the leading method of the Scan-to-BIM procedure, many professionals indicate drawbacks of the technology and point out the drone is an alternative that can improve the shortcomings, leading to the UAV-to-BIM process. The Korean construction industry plans to implement drone technology for scrutinizing as-built construction quality by 2025. However, drones are not popular in construction projects. Korean universities where Construction Engineering and Management programs have been implemented have requested to develop a drone curriculum for construction professionals. Since the majority of the professionals are not familiar with drone operation, in order for the schools to be successful in developing the curriculum, it is very necessary to perform a preliminary experimental study for identifying the essential education contents that are appropriate for drone beginners. The main objective of this paper is to perform a study for drone beginners and recognize the recommendations and the framework of a drone curriculum that will be beneficial for the schools to develop a comprehensive curriculum later on. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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23 pages, 2306 KiB

Open AccessArticle

Impediments to Construction Site Digitalisation Using Unmanned Aerial Vehicles (UAVs)

by Adetayo Olugbenga Onososen, Innocent Musonda, Damilola Onatayo, Motheo Meta Tjebane, Abdullahi Babatunde Saka and Rasaki Kolawole Fagbenro

Drones 2023, 7(1), 45; https://doi.org/10.3390/drones7010045 - 9 Jan 2023

Cited by 11 | Viewed by 4558

Abstract

Utilising emerging innovative technologies and systems to improve construction processes in an effort towards digitalisation has been earmarked as critical to delivering resilience and responsive infrastructure. However, successful implementation is hindered by several challenges. Hence, this study evaluates the challenges facing the adoption of unmanned aerial vehicles towards the digitalisation of the built environment. The study adopted a quantitative survey of built environment stakeholders in developed and developing economies. A total of 161 completely filled forms were received after the survey, and the data were analysed using descriptive analysis and inferential statistics. The study’s findings show that there are different barriers experienced between developed and developing countries in the adoption of drones towards digitalising construction processes in the built environment. Moreover, economic/cost-related factors were identified as the most critical barriers to the adoption of drones, followed by technical/regulatory factors and education/organisation-related factors. The findings can assist the built environment in reducing the impact of these barriers and could serve as a policy instrument and helpful guidelines for governmental organisations, stakeholders, and others. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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21 pages, 7909 KiB

Open AccessArticle

Automatic Volume Calculation and Mapping of Construction and Demolition Debris Using Drones, Deep Learning, and GIS

by Yuhan Jiang, Yilei Huang, Jingkuang Liu, Dapeng Li, Shuiyuan Li, Weijing Nie and In-Hun Chung

Drones 2022, 6(10), 279; https://doi.org/10.3390/drones6100279 - 27 Sep 2022

Cited by 20 | Viewed by 4358

Abstract

This paper presents a time- and cost-efficient method for the management of construction and demolition (C&D) debris at construction sites, demolition jobsites, and illegal C&D waste dumping sites. The developed method integrates various drone, deep learning, and geographic information system (GIS) technologies, including C&D debris drone scanning, 3D reconstruction with structure from motion (SfM), image segmentation with fully convolutional network (FCN), and C&D debris information management with georeferenced 2D and 3D as-built. Experiments and parameter analysis led us to conclude that (1) drone photogrammetry using top- and side-view images is effective in the 3D reconstruction of C&D debris (stockpiles); (2) FCNs are effective in C&D debris extraction with point cloud-generated RGB orthoimages with a high intersection over union (IoU) value of 0.9 for concrete debris; and (3) using FCN-generated pixelwise label images, point cloud-converted elevation data for projected area, and volume measurements of C&D debris is both robust and accurate. The developed automatic method provides quantitative and geographic information to support city governments in intelligent information management of C&D debris. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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12 pages, 6251 KiB

Open AccessArticle

Compact and Efficient Topological Mapping for Large-Scale Environment with Pruned Voronoi Diagram

by Yao Qi, Rendong Wang, Binbing He, Feng Lu and Youchun Xu

Drones 2022, 6(7), 183; https://doi.org/10.3390/drones6070183 - 21 Jul 2022

Cited by 8 | Viewed by 2558

Abstract

Topological maps generated in complex and irregular unknown environments are meaningful for autonomous robots’ navigation. To obtain the skeleton of the environment without obstacle polygon extraction and clustering, we propose a method to obtain high-quality topological maps using only pure Voronoi diagrams in three steps. Supported by Voronoi vertex’s property of the largest empty circle, the method updates the global topological map incrementally in both dynamic and static environments online. The incremental method can be adapted to any fundamental Voronoi diagram generator. We maintain the entire space by two graphs, the pruned Voronoi graph for incremental updates and the reduced approximated generalized Voronoi graph for routing planning requests. We present an extensive benchmark and real-world experiment, and our method completes the environment representation in both indoor and outdoor areas. The proposed method generates a compact topological map in both small- and large-scale scenarios, which is defined as the total length and vertices of topological maps. Additionally, our method has been shortened by several orders of magnitude in terms of the total length and consumes less than 30% of the average time cost compared to state-of-the-art methods. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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16 pages, 8367 KiB

Open AccessArticle

Large-Scale Earthwork Progress Digitalization Practices Using Series of 3D Models Generated from UAS Images

by Jin-Woo Cho, Jae-Kang Lee and Jisoo Park

Drones 2021, 5(4), 147; https://doi.org/10.3390/drones5040147 - 12 Dec 2021

Cited by 15 | Viewed by 4497

Abstract

Since the Fourth Industrial Revolution, existing manpower-centric manufacture has been shifting towards technology and data-centric production in all areas of society. The construction sector is also facing a new paradigm called smart construction with a clear purpose of improving productivity and securing safety by applying site management using information and communications technology (ICT). This study aims to develop a framework for earthwork process digitalization based on images acquired by using the unmanned aerial system (UAS). The entire framework includes precise UAS data acquisition, cut-and-fill volume estimation, cross-section drawing, and geo-fencing generation. To this end, homogeneous time-series drone image data were obtained from active road construction sites under earthwork. The developed system was able to generate precise 3D topographical models and estimate cut-and-fill volume changes. In addition, the proposed framework generated cross-sectional views of each area of interest throughout the construction stages and finally created geo-fencing to assist the safe operation of heavy equipment. We expect that the proposed framework can contribute to smart construction areas by automating the process of digitizing earthwork progress. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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Review

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11 pages, 1544 KiB

Open AccessReview

A Synthetic Review of UAS-Based Facility Condition Monitoring

by Kyeongtae Jeong, Jinhyuk Kwon, Sung Lok Do, Donghoon Lee and Sungjin Kim

Drones 2022, 6(12), 420; https://doi.org/10.3390/drones6120420 - 15 Dec 2022

Cited by 1 | Viewed by 1751

Abstract

Facility inspections are mainly carried out through manual visual inspections. However, it is difficult to determine the extent of damages to facilities, and it depends on the subjective opinion of the manager in charge of the monitoring. Additionally, when inspectors inspect facilities that cannot be safely accessed, such as high-rise buildings, there are high risks of fatal accidents. For this reason, the construction industry conducts research into unmanned aircraft system (UAS)-based facility inspections. These studies have been focusing on developing the technologies or processes for using UAS in facility condition monitoring, ranging from infrastructure systems to commercial buildings. This study conducted extensive and synthetic reviews of the recent studies in UAS-based facility monitoring using a preferred reporting items for systematic reviews and meta-analysis (PRISMA) method. A total of 32 papers were selected and classified through the types of facilities and the technologies addressed in the studies. This paper analyzes the trends of recent studies by synthesizing the selected papers and consolidates the further directions of UAS applications and studies in facility monitoring domains. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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20 pages, 1150 KiB

Open AccessReview

A Review on UAV-Based Remote Sensing Technologies for Construction and Civil Applications

by Shanyue Guan, Zhen Zhu and George Wang

Drones 2022, 6(5), 117; https://doi.org/10.3390/drones6050117 - 6 May 2022

Cited by 57 | Viewed by 7845

Abstract

UAV-based technologies are evolving and improving at a rapid pace. The abundance of solutions and systems available today can make it difficult to identify the best option for construction and civil projects. The purpose of this literature review is to examine the benefits and limitations of UAV-based sensing systems in the context of construction management and civil engineering, with a focus on camera-based and laser-based systems. The risk factors associated with UAV operations at construction sites are also considered. Full article

(This article belongs to the Special Issue Application of UAS in Construction)

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