Pub Date : 2025-02-18DOI: 10.1016/j.autcon.2025.106065
Chenyu Liu , Jing Wu , Yunfan Gu , Luqi Xie , Gang Wu
A robot-assisted installation method, which uses a crane to bear the component's weight and two robots to control the lifted component for precise horizontal positioning, was proposed in a previous study. To enhance the capability to operate large prefabricated components, this paper designs a binocular vision-based technique for real-time localization of the end-tool during the component-pushing process. Each robot is continuously commanded to rotate and translate the end tool based on the measured difference between its current and target poses, until this difference is within an acceptable threshold. The principles and implementation details of the visual method are described in this paper. Even if the robot deforms or slips, accurate measurement and adjustment of the end tool's pose allow effective pushing of the component to the target area. Test results demonstrate that the binocular vision guidance technology is feasible and effective, improving the flexibility and practicability of the installation-assisted robot.
{"title":"Binocular vision-based guidance for robotic assembly of prefabricated components","authors":"Chenyu Liu , Jing Wu , Yunfan Gu , Luqi Xie , Gang Wu","doi":"10.1016/j.autcon.2025.106065","DOIUrl":"10.1016/j.autcon.2025.106065","url":null,"abstract":"<div><div>A robot-assisted installation method, which uses a crane to bear the component's weight and two robots to control the lifted component for precise horizontal positioning, was proposed in a previous study. To enhance the capability to operate large prefabricated components, this paper designs a binocular vision-based technique for real-time localization of the end-tool during the component-pushing process. Each robot is continuously commanded to rotate and translate the end tool based on the measured difference between its current and target poses, until this difference is within an acceptable threshold. The principles and implementation details of the visual method are described in this paper. Even if the robot deforms or slips, accurate measurement and adjustment of the end tool's pose allow effective pushing of the component to the target area. Test results demonstrate that the binocular vision guidance technology is feasible and effective, improving the flexibility and practicability of the installation-assisted robot.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106065"},"PeriodicalIF":9.6,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.autcon.2025.106073
Guangbin Wang, Yiwei Zhou, Dongping Cao
Artificial intelligence (AI) is spreading rapidly in the construction domain with high expectations and distinct innovation challenges. While many scholars have conducted literature reviews on the development status of AI in construction, patent data, which can objectively reflect technological evolution, is rarely analyzed. This paper conducted the patent analysis to reveal the application hotspots and evolutionary trends of AI in construction. Descriptive analysis showed that China held the majority of patents and the United States played a crucial role in knowledge transfer. The results further indicated that machine learning and computer vision were the most prevalent technologies, while structural health monitoring and safety management were the hottest topics. Additionally, this paper depicted the technology transfer landscape, and forecasted the evolutionary trends of AI technologies. This paper provides valuable insights into AI in construction from a new perspective of patent, and offers references to engineers, managers and policymakers in this field.
{"title":"Artificial intelligence in construction: Topic-based technology mapping based on patent data","authors":"Guangbin Wang, Yiwei Zhou, Dongping Cao","doi":"10.1016/j.autcon.2025.106073","DOIUrl":"10.1016/j.autcon.2025.106073","url":null,"abstract":"<div><div>Artificial intelligence (AI) is spreading rapidly in the construction domain with high expectations and distinct innovation challenges. While many scholars have conducted literature reviews on the development status of AI in construction, patent data, which can objectively reflect technological evolution, is rarely analyzed. This paper conducted the patent analysis to reveal the application hotspots and evolutionary trends of AI in construction. Descriptive analysis showed that China held the majority of patents and the United States played a crucial role in knowledge transfer. The results further indicated that machine learning and computer vision were the most prevalent technologies, while structural health monitoring and safety management were the hottest topics. Additionally, this paper depicted the technology transfer landscape, and forecasted the evolutionary trends of AI technologies. This paper provides valuable insights into AI in construction from a new perspective of patent, and offers references to engineers, managers and policymakers in this field.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106073"},"PeriodicalIF":9.6,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.autcon.2025.106054
Cungen Liu , Zhiwei Zhang , Xiaoping Liu , Huanqing Wang , Yang Liu
To achieve precise positioning, anti-swing control, and obstacle avoidance for tower cranes, this paper addresses the problem of coupled anti-swing and obstacle avoidance control in underactuated nonlinear systems. First, a trajectory modification method is introduced to ensure avoidance of irregular obstacles while maintaining sufficient differentiability. Then, a dynamic performance boundary is defined to constrain load angles based on low-pass filters. Finally, by coupling actuated and non-actuated states, a tracking controller is designed and applied to a laboratory tower crane. The proposed controller can not only achieve precise positioning and obstacle avoidance for loads, but also always constrain load swing angles within predefined ranges. The developed control scheme can improve the control accuracy and work efficiency of tower cranes, simultaneously. In future, the proposed controller will be applied to tower cranes for three-dimensional obstacle avoidance.
{"title":"Coupled anti-swing control strategy for underactuated tower cranes with obstacle avoidance","authors":"Cungen Liu , Zhiwei Zhang , Xiaoping Liu , Huanqing Wang , Yang Liu","doi":"10.1016/j.autcon.2025.106054","DOIUrl":"10.1016/j.autcon.2025.106054","url":null,"abstract":"<div><div>To achieve precise positioning, anti-swing control, and obstacle avoidance for tower cranes, this paper addresses the problem of coupled anti-swing and obstacle avoidance control in underactuated nonlinear systems. First, a trajectory modification method is introduced to ensure avoidance of irregular obstacles while maintaining sufficient differentiability. Then, a dynamic performance boundary is defined to constrain load angles based on low-pass filters. Finally, by coupling actuated and non-actuated states, a tracking controller is designed and applied to a laboratory tower crane. The proposed controller can not only achieve precise positioning and obstacle avoidance for loads, but also always constrain load swing angles within predefined ranges. The developed control scheme can improve the control accuracy and work efficiency of tower cranes, simultaneously. In future, the proposed controller will be applied to tower cranes for three-dimensional obstacle avoidance.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106054"},"PeriodicalIF":9.6,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-17DOI: 10.1016/j.autcon.2025.106052
Xue Yan , Xinran Liao , Shuping Cheng , Ting Wang
In bridge construction, the integration of information management technologies like BIM, blockchain, big data, and precast components shows promise but lack initial adoption motivation. Centering on BIM, this paper constructs an incentive model for collaboration between owners and construction units, thereby exploring the technology diffusion mechanisms. Utilizing a simulation on the Shenzhen-Zhongshan Bridge (SZB) in China, the paper identifies effective incentive ranges and scenarios. Results indicate that combining penalties and early completion benefits is more effective than simple subsidy in reducing costs and enhancing incentives. Further analysis reveals that incentives can encourage BIM adoption but may cause a “Matthew Effect”. These findings facilitate owners in designing compound incentive programs and assist construction units in determining the optimal technology application level to seize market opportunities. Future research should explore a broader spectrum of incentive types and combinations for a more comprehensive understanding of effective incentive strategies.
{"title":"BIM-focused incentive-driven adoption of information management technology in bridge construction","authors":"Xue Yan , Xinran Liao , Shuping Cheng , Ting Wang","doi":"10.1016/j.autcon.2025.106052","DOIUrl":"10.1016/j.autcon.2025.106052","url":null,"abstract":"<div><div>In bridge construction, the integration of information management technologies like BIM, blockchain, big data, and precast components shows promise but lack initial adoption motivation. Centering on BIM, this paper constructs an incentive model for collaboration between owners and construction units, thereby exploring the technology diffusion mechanisms. Utilizing a simulation on the Shenzhen-Zhongshan Bridge (SZB) in China, the paper identifies effective incentive ranges and scenarios. Results indicate that combining penalties and early completion benefits is more effective than simple subsidy in reducing costs and enhancing incentives. Further analysis reveals that incentives can encourage BIM adoption but may cause a “Matthew Effect”. These findings facilitate owners in designing compound incentive programs and assist construction units in determining the optimal technology application level to seize market opportunities. Future research should explore a broader spectrum of incentive types and combinations for a more comprehensive understanding of effective incentive strategies.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106052"},"PeriodicalIF":9.6,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-17DOI: 10.1016/j.autcon.2025.106070
Hao-Ruo Xu , Jia-Ning Yin , Ning Zhang
Measuring the deformation of underground structures, such as excavation and tunnels, is crucial for safe construction and operation. However, conventional methods, such as inclinometer probes and total stations, are labour-intensive and time-consuming for engineers. This paper proposes a transformer-based 3D reconstruction method using single-camera video to rapidly measure structural deformations. The proposed method extracts features from video frames to reconstruct point clouds, generating centrelines and Poisson models for deformation analysis. This allows fast and precise deformation measurement at any position, outperforming traditional methods. The proposed method has achieved sub-millimetre accuracy in small-scale inclinometer casings, and a 5 cm accuracy level in a large-scale tunnel, confirming its capability for detecting subtle deformations. Discrepancies in accuracy for larger structures were attributed to limitations in camera resolution, suggesting that employing 100-megapixel cameras could guarantee millimetre-level accuracy. The method's simplicity and adaptability demonstrate its potential as a practical supplement to existing deformation measurement methods.
{"title":"Transformer-based deformation measurement of underground structures from a single-camera video","authors":"Hao-Ruo Xu , Jia-Ning Yin , Ning Zhang","doi":"10.1016/j.autcon.2025.106070","DOIUrl":"10.1016/j.autcon.2025.106070","url":null,"abstract":"<div><div>Measuring the deformation of underground structures, such as excavation and tunnels, is crucial for safe construction and operation. However, conventional methods, such as inclinometer probes and total stations, are labour-intensive and time-consuming for engineers. This paper proposes a transformer-based 3D reconstruction method using single-camera video to rapidly measure structural deformations. The proposed method extracts features from video frames to reconstruct point clouds, generating centrelines and Poisson models for deformation analysis. This allows fast and precise deformation measurement at any position, outperforming traditional methods. The proposed method has achieved sub-millimetre accuracy in small-scale inclinometer casings, and a 5 cm accuracy level in a large-scale tunnel, confirming its capability for detecting subtle deformations. Discrepancies in accuracy for larger structures were attributed to limitations in camera resolution, suggesting that employing 100-megapixel cameras could guarantee millimetre-level accuracy. The method's simplicity and adaptability demonstrate its potential as a practical supplement to existing deformation measurement methods.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106070"},"PeriodicalIF":9.6,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-16DOI: 10.1016/j.autcon.2025.106053
Sungboo Yoon , Moonseo Park , Changbum R. Ahn
Dynamic viewpoints offer effective visual feedback in teleoperation for construction, where tasks often require precise manipulation during frequent viewpoint adjustments. However, the comparative performance of various dynamic viewpoint control techniques remains unclear. This paper investigates the impact of dynamic viewpoint control techniques on task performance and user experience during teleoperation in construction. A user study was conducted in a remote welding-at-height scenario with 20 participants, including experienced welders and university students, to compare five techniques: (1) coupled vision-motion, (2) decoupled vision-motion with hand or head motion-based control, and (3) hybrid vision-motion with manual or automatic switching. Results showed that decoupled vision-motion with head motion-based control outperformed other techniques in task efficiency and user preference. Hybrid vision-motion with manual switching was more effective than decoupled vision-motion in contexts involving occlusions, reducing physical demand and enhancing welding quality. Based on these findings, guidelines are proposed for viewpoint control in teleoperated construction robots.
{"title":"Comparing dynamic viewpoint control techniques for teleoperated robotic welding in construction","authors":"Sungboo Yoon , Moonseo Park , Changbum R. Ahn","doi":"10.1016/j.autcon.2025.106053","DOIUrl":"10.1016/j.autcon.2025.106053","url":null,"abstract":"<div><div>Dynamic viewpoints offer effective visual feedback in teleoperation for construction, where tasks often require precise manipulation during frequent viewpoint adjustments. However, the comparative performance of various dynamic viewpoint control techniques remains unclear. This paper investigates the impact of dynamic viewpoint control techniques on task performance and user experience during teleoperation in construction. A user study was conducted in a remote welding-at-height scenario with 20 participants, including experienced welders and university students, to compare five techniques: (1) coupled vision-motion, (2) decoupled vision-motion with hand or head motion-based control, and (3) hybrid vision-motion with manual or automatic switching. Results showed that decoupled vision-motion with head motion-based control outperformed other techniques in task efficiency and user preference. Hybrid vision-motion with manual switching was more effective than decoupled vision-motion in contexts involving occlusions, reducing physical demand and enhancing welding quality. Based on these findings, guidelines are proposed for viewpoint control in teleoperated construction robots.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106053"},"PeriodicalIF":9.6,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Excavators have complex structures, large load, and often works in scenarios with safety hazards. Existing methods overlook control-level safety and over-prioritize accuracy, neglecting input smoothness. To address these challenges, a Barrier Functions Adaptive Sliding Mode (BFASM) safety control method based on Kinematic Control Barrier Function (KCBF) and Sliding Mode Disturbance Observer (SMDO) is proposed. Specifically, a virtual motion trajectory tracking controller is established and CBF provides safe joint velocity inputs for system. A Barrier Function (BF)-based anti-saturation adaptive sliding mode controller is proposed. SMDO is used to estimate the lumped disturbance. BF is used to design the bounded adaptive control gain to ensure that sliding variables remain in predefined neighborhoods of zero, and its size does not depend on disturbance boundary. Simulation results demonstrate that the proposed safety controller effectively ensures safety and the tracking controller keeps errors within a predefined range of 1° with no chattering of control inputs.
{"title":"Adaptive sliding mode and safety control for excavators using Kinematic Control Barrier Function and sliding mode disturbance observer","authors":"Weidi Huang , Qi Wang , Shuwei Yang, Junhui Zhang, Bing Xu","doi":"10.1016/j.autcon.2025.106046","DOIUrl":"10.1016/j.autcon.2025.106046","url":null,"abstract":"<div><div>Excavators have complex structures, large load, and often works in scenarios with safety hazards. Existing methods overlook control-level safety and over-prioritize accuracy, neglecting input smoothness. To address these challenges, a Barrier Functions Adaptive Sliding Mode (BFASM) safety control method based on Kinematic Control Barrier Function (KCBF) and Sliding Mode Disturbance Observer (SMDO) is proposed. Specifically, a virtual motion trajectory tracking controller is established and CBF provides safe joint velocity inputs for system. A Barrier Function (BF)-based anti-saturation adaptive sliding mode controller is proposed. SMDO is used to estimate the lumped disturbance. BF is used to design the bounded adaptive control gain to ensure that sliding variables remain in predefined neighborhoods of zero, and its size does not depend on disturbance boundary. Simulation results demonstrate that the proposed safety controller effectively ensures safety and the tracking controller keeps errors within a predefined range of 1° with no chattering of control inputs.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106046"},"PeriodicalIF":9.6,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-13DOI: 10.1016/j.autcon.2025.106037
Paulo Alberto Sampaio Santos, Michele Tereza Marques Carvalho
Advances in computer vision have significantly improved bridge inspection by enabling precise damage detection and failure prediction. However, these techniques require costly datasets and specialized expertise. To overcome this, an approach combining YOLO object detection and SAM segmentation effectively identifies cracks, scaling, rust stains, exposed reinforcement, and efflorescence. Six models were fine-tuned, including the YOLOv8 architecture, three variations with modified detection layers for small, medium, and large damage, an optimized TensorRT version, and the new Yolov9-GELAN architecture. The YOLOv8l model achieved precision, recall, , and of 0.946, 0.916, 0.951, and 0.892, respectively. The model’s outputs enhanced SAM-based instance segmentation, reducing uncertainties. A publicly available COCO-format dataset with 41,132 annotated images supports further research. This paper advances bridge inspection and construction by providing a robust model for multi-class object detection and instance segmentation of structural damages, with architectures tailored to detect small, medium, and large damages for more precise inspections.
{"title":"Multi-class segmentation of structural damage and pathological manifestations using YOLOv8 and Segment Anything Model","authors":"Paulo Alberto Sampaio Santos, Michele Tereza Marques Carvalho","doi":"10.1016/j.autcon.2025.106037","DOIUrl":"10.1016/j.autcon.2025.106037","url":null,"abstract":"<div><div>Advances in computer vision have significantly improved bridge inspection by enabling precise damage detection and failure prediction. However, these techniques require costly datasets and specialized expertise. To overcome this, an approach combining YOLO object detection and SAM segmentation effectively identifies cracks, scaling, rust stains, exposed reinforcement, and efflorescence. Six models were fine-tuned, including the YOLOv8 architecture, three variations with modified detection layers for small, medium, and large damage, an optimized TensorRT version, and the new Yolov9-GELAN architecture. The YOLOv8l model achieved precision, recall, <span><math><mrow><mi>m</mi><mi>A</mi><msub><mrow><mi>P</mi></mrow><mrow><mn>50</mn></mrow></msub></mrow></math></span>, and <span><math><mrow><mi>m</mi><mi>A</mi><msub><mrow><mi>P</mi></mrow><mrow><mn>50</mn><mo>−</mo><mn>95</mn></mrow></msub></mrow></math></span> of 0.946, 0.916, 0.951, and 0.892, respectively. The model’s outputs enhanced SAM-based instance segmentation, reducing uncertainties. A publicly available COCO-format dataset with 41,132 annotated images supports further research. This paper advances bridge inspection and construction by providing a robust model for multi-class object detection and instance segmentation of structural damages, with architectures tailored to detect small, medium, and large damages for more precise inspections.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106037"},"PeriodicalIF":9.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-13DOI: 10.1016/j.autcon.2025.106020
J. Versteege, R.J.M. Wolfs, T.A.M. Salet
First-time-right manufacturing is an important step toward unlocking the full potential of digital fabrication with concrete (DFC), which can be advanced through data-driven approaches. Non-invasive in-line sensors can collect vast amounts of measurements during the manufacturing process. However, knowledge-driven feature engineering (KDFE) strategies are necessary to extract meaningful information, referred to as features, from the raw sensory data. This contribution, part of a two-part study, presents an approach to integrating KDFE with various in-line sensors in a 3D concrete printing (3DCP) facility, focusing on 2D laser scanning techniques to capture the ‘as-printed’ layer geometry during production. The geometric profiles are translated into features that quantify layer dimensions, cross-sectional area, and surface texture, reducing data complexity while enhancing relevancy. Real-world data is utilized to demonstrate the approach. A companion paper extends the methodology to other sensors, including those monitoring moisture and temperature, further advancing process monitoring in 3DCP.
{"title":"Data-driven additive manufacturing with concrete: Enhancing in-line sensory data with domain knowledge, Part I: Geometry","authors":"J. Versteege, R.J.M. Wolfs, T.A.M. Salet","doi":"10.1016/j.autcon.2025.106020","DOIUrl":"10.1016/j.autcon.2025.106020","url":null,"abstract":"<div><div>First-time-right manufacturing is an important step toward unlocking the full potential of digital fabrication with concrete (DFC), which can be advanced through data-driven approaches. Non-invasive in-line sensors can collect vast amounts of measurements during the manufacturing process. However, knowledge-driven feature engineering (KDFE) strategies are necessary to extract meaningful information, referred to as features, from the raw sensory data. This contribution, part of a two-part study, presents an approach to integrating KDFE with various in-line sensors in a 3D concrete printing (3DCP) facility, focusing on 2D laser scanning techniques to capture the ‘as-printed’ layer geometry during production. The geometric profiles are translated into features that quantify layer dimensions, cross-sectional area, and surface texture, reducing data complexity while enhancing relevancy. Real-world data is utilized to demonstrate the approach. A companion paper extends the methodology to other sensors, including those monitoring moisture and temperature, further advancing process monitoring in 3DCP.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106020"},"PeriodicalIF":9.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-13DOI: 10.1016/j.autcon.2025.106056
Anna Przewięźlikowska , Wioletta Ślusarczyk , Klaudia Wójcik , Marek Ślusarski
Large-scale mobile applications integrating social networks and GPS-based location data are increasingly utilized for professional and private purposes. This paper addresses the specific research question of how to design a low-cost, reliable, and efficient architecture for such applications. Through the Metrica application for land surveyors, an architecture utilizing affordable or free hardware and software is proposed and demonstrated. The architecture successfully enhances the speed and quality of civil engineers' work collecting and navigating geodetic control network points. This solution has been proven for civil engineers in Poland and can benefit other Virtual Communities of Practice (VCoPs) in similar contexts. The approach inspires future research on scalable and reusable solution stacks for location-based applications in diverse environments.
{"title":"Efficient and scalable architecture for location-based mobile applications using metrica","authors":"Anna Przewięźlikowska , Wioletta Ślusarczyk , Klaudia Wójcik , Marek Ślusarski","doi":"10.1016/j.autcon.2025.106056","DOIUrl":"10.1016/j.autcon.2025.106056","url":null,"abstract":"<div><div>Large-scale mobile applications integrating social networks and GPS-based location data are increasingly utilized for professional and private purposes. This paper addresses the specific research question of how to design a low-cost, reliable, and efficient architecture for such applications. Through the Metrica application for land surveyors, an architecture utilizing affordable or free hardware and software is proposed and demonstrated. The architecture successfully enhances the speed and quality of civil engineers' work collecting and navigating geodetic control network points. This solution has been proven for civil engineers in Poland and can benefit other Virtual Communities of Practice (VCoPs) in similar contexts. The approach inspires future research on scalable and reusable solution stacks for location-based applications in diverse environments.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"172 ","pages":"Article 106056"},"PeriodicalIF":9.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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