Article
Computer Science, Interdisciplinary Applications
Xingyu Tao, Peter Kok-Yiu Wong, Yuqing Xu, Yuhan Liu, Xingbo Gong, Chengliang Zheng, Moumita Das, Jack C. P. Cheng
Summary: This paper proposes a blockchain-aided solution for secure and efficient BIM versioning by introducing a two-layer container common data environment (TLCCDE) model, a smart contract swarm (SCS), and a novel multi-branch structure (MBS), which together achieve the secure and efficient management of BIM versions in a distributed environment.
COMPUTERS IN INDUSTRY
(2023)
Article
Chemistry, Analytical
Joonseok Park, Sumin Jeong, Keunhyuk Yeom
Summary: In this paper, a smart contract broker is proposed to enhance the reusability of smart contracts in a blockchain environment. The lack of a standardized approach for sharing and managing smart contracts on current blockchain platforms impedes developers' ability to reuse them, leading to inefficiency. The proposed smart contract broker utilizes tags to identify and organize smart contracts, offering a platform for comparison and reuse. Consequently, this improves smart contract reusability and overall efficiency. The suggested smart contract broker can serve as a reference model to enhance the flexibility and reusability of smart contract management in a blockchain environment.
Article
Construction & Building Technology
Xingyu Tao, Yuhan Liu, Peter Kok-Yiu Wong, Keyu Chen, Moumita Das, Jack C. P. Cheng
Summary: This paper proposes a confidentiality-minded framework (CMF) for blockchain-based design collaboration, which protects sensitive BIM data effectively by developing an access control model and design strategies.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Energy & Fuels
Sri Nikhil Gupta Gourisetti, D. Jonathan Sebastian-Cardenas, Bishnu Bhattarai, Peng Wang, Steve Widergren, Mark Borkum, Alysha Randall
Summary: This paper proposes a reference framework for a transactive energy market based on blockchain technology, addressing both engineering requirements and cybersecurity needs. The framework leverages blockchain attributes to provide value propositions applicable to transactive energy market applications.
Article
Chemistry, Analytical
Youngjun Sung, Sunghyun Yu, Yoojae Won
Summary: Countries need measures to prevent food fraud, even with a quality food management certification system in place. Blockchain tokens have been introduced for quality and supply chain management, but face challenges in the food industry, especially in forest and agricultural products. This study focuses on wild-simulated ginseng in Korea, analyzing its quality management process and proposing potential solutions to token-related issues from consumers.
Article
Chemistry, Multidisciplinary
Katharina Sigalov, Xuling Ye, Markus Koenig, Philipp Hagedorn, Florian Blum, Benedikt Severin, Michael Hettmer, Philipp Hueckinghaus, Jens Woelkerling, Dominik Gross
Summary: Smart contracts in construction projects combine BIM approaches with blockchain technology to automate billing and ensure transparent payments, addressing issues caused by complex contract structures.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Mehmet Baygin, Orhan Yaman, Nursena Baygin, Mehmet Karakose
Summary: The continuous growth of e-commerce emphasizes the importance of point-to-point shipment transportation and the need for efficient and fast service from shipment management systems. This study introduces a blockchain-based solution for local cargo networks, utilizing UHF-RFID, IoT sensors, and smart contracts to ensure secure and fast shipping management architecture.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Peilin Zheng, Quanqing Xu, Zibin Zheng, Zhiyuan Zhou, Ying Yan, Hui Zhang
Summary: This article introduces a systematic study on sharded consortium blockchain, proposing a solution called Meepo to improve cross-shard efficiency through cross-epoch and cross-call strategies. It also designs a partial cross-call merging strategy to handle multi-state dependency in contract calls, and employs replay-epoch and shadow shard based recovery algorithm to ensure strict transaction atomicity and enhance shard robustness. In performance testing, Meepo demonstrates high throughput in cross-shard transactions.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2022)
Article
Construction & Building Technology
Faris Elghaish, M. Reza Hosseini, Tuba Kocaturk, Mehrdad Arashpour, Masoomeh Bararzadeh Ledari
Summary: Blockchain and smart contracts are utilized to accelerate the implementation of circular economy in construction processes. However, there is still a lack of integrated solutions that cover all aspects of the circular supply chain. This paper proposes a workable solution to address the fragmented adoption of blockchain in construction procedures, following the five-stage procedure of design science research. The proposed solution has novel features and provides fertile ground for future research.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Construction & Building Technology
Rowaid Ibrahim, Ahmed Alaa Harby, Mohamed Salem Nashwan, Ahmed Elhakeem
Summary: The use of cryptocurrency blockchain is a paradigm shift in data storage, retrieval, and verification, ensuring data security through decentralization. Integrating smart contracts enables automation and creates a suitable ecosystem for multiple industries. This study presents a prototype of a cryptocurrency blockchain with programmable smart contracts for the construction industry, guaranteeing a decentralized system and improving efficiency.
Article
Food Science & Technology
Yiqin Zhang, Luyao Chen, Maurizio Battino, Mohamed A. Farag, Jianbo Xiao, Jesus Simal-Gandara, Haiyan Gao, Weibo Jiang
Summary: This article recommends the use of blockchain to upgrade the current fresh fruit supply chain and analyzes the obstacles faced by the implementation of this technology in relation to participants' attitude, fruit preservation, and blockchain technical loopholes. The research shows that blockchain can help solve the problems in supply chain management, including information tamper resistance, supply-demand relationship, and traceable supervision.
TRENDS IN FOOD SCIENCE & TECHNOLOGY
(2022)
Article
Chemistry, Analytical
Yang Liu, Yuxi Zhang, Zhiyuan Lin, Zhaoguo Wang, Xuan Wang
Summary: This paper proposes a blockchain system simulation platform, dividing the blockchain system into four layers for optimization, and implements a prototype of an efficient blockchain simulation system.
Article
Computer Science, Information Systems
Daojing He, Rui Wu, Xinji Li, Sammy Chan, Mohsen Guizani
Summary: This article introduces common security vulnerabilities in blockchain smart contracts and classifies the detection tools into six categories, including formal verification, symbolic execution, fuzzy testing, intermediate representation, state analysis, and deep learning methods. The authors tested 27 detection tools and concluded that most of them only detect vulnerabilities in a single and old version of smart contracts. Although fewer types of vulnerabilities are detected, the deep learning method has higher accuracy and efficiency. Therefore, combining static detection methods like deep learning with dynamic methods like fuzzy testing to detect more types of vulnerabilities in multi-version smart contracts is a future research direction.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Industrial
Haizhe Yu, Xiaopeng Deng, Na Zhang
Summary: This study aims to discuss the obstructing clauses in real-world contracts and analyze the technical and economic feasibility of transforming contract clauses into executable codes. Through inductive content analysis and speculative analysis, the study identifies the flexibility clauses in traditional contracts and explores different methods to transform these clauses into computer languages.
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Rini Handayani, Anak Agung Gde Agung
Summary: The concept of a smart grid has been proposed to ensure efficient distribution of electricity and secure transactions. This paper suggests using blockchain technology to manage transactions in the smart grid, providing security and immutability.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Construction & Building Technology
Giulio Mariniello, Tommaso Pastore, Domenico Asprone, Edoardo Cosenza
Summary: This paper introduces a novel Extreme Learning Machine framework for accurately detecting and localizing damages affecting the prestressing system of a prestressed concrete bridge, showing remarkable accuracy and efficiency in computational experiments.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Construction & Building Technology
Giulio Mariniello, Tommaso Pastore, Antonio Bilotta, Domenico Asprone, Edoardo Cosenza
Summary: The study discusses the pre-dimensioning problem and presents a hybrid algorithm for its solution, which significantly improves design efficiency compared to traditional methods.
JOURNAL OF BUILDING ENGINEERING
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Giovanni Giacco, Giulio Mariniello, Stefano Marrone, Domenico Asprone, Carlo Sansone
Summary: A quick and accurate post-earthquake safety assessment is crucial for emergency management and reconstruction. Standard forms and a Deep Learning-based tool can be utilized to accurately assess damages and aid in faithful reconstruction.
IMAGE ANALYSIS AND PROCESSING, ICIAP 2022, PT II
(2022)
Article
Computer Science, Interdisciplinary Applications
Giulio Mariniello, Tommaso Pastore, Costantino Menna, Paola Festa, Domenico Asprone
Summary: This paper explores the capabilities of decision tree ensembles (DTEs) for detecting and localizing damage in structural health monitoring (SHM) and proposes a D-2-DTE methodology based on vibration analysis for health assessment. The method is validated for various damage scenarios and shows competitive performances in accuracy and localization errors compared to state-of-the-art methodologies.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2021)
Article
Construction & Building Technology
Jia Liang, Qipeng Zhang, Xingyu Gu
Summary: A lightweight PCSNet-based segmentation model is developed to address the issues of insufficient performance in feature extraction and boundary loss information. The introduction of generalized Dice loss improves prediction performance, and the visualization of class activation mapping enhances model interpretability.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Gilsu Jeong, Minhyuk Jung, Seongeun Park, Moonseo Park, Changbum Ryan Ahn
Summary: This study introduces a contextual audio-visual approach to recognize multi-equipment activities in tunnel construction sites, improving monitoring effectiveness. Tested against real-world operation data, the model achieved remarkable results, emphasizing the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Jin Wang, Zhigao Zeng, Pradip Kumar Sharma, Osama Alfarraj, Amr Tolba, Jianming Zhang, Lei Wang
Summary: This study presents a dual-path network for pavement crack segmentation, combining Convolutional Neural Network (CNN) and transformer. A lightweight CNN encoder is used for local feature extraction, while a novel transformer encoder integrates high-low frequency attention mechanism and efficient feedforward network for global feature extraction. Additionally, a complementary fusion module is introduced to aggregate intermediate features extracted from both encoders. Evaluation on three datasets confirms the superior performance of the proposed network.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Pierre Gilibert, Romain Mesnil, Olivier Baverel
Summary: This paper introduces a flexible method for crafting 2D assemblies adaptable to various geometric assumptions in the realm of sustainable construction. By utilizing digital fabrication technologies and optimization approaches, precise control over demountable buildings can be achieved, improving mechanical performance and sustainability.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Jorge Loy-Benitez, Myung Kyu Song, Yo-Hyun Choi, Je-Kyum Lee, Sean Seungwon Lee
Summary: This paper discusses the advancement of tunnel boring machines (TBM) through the application of artificial intelligence. It highlights the significance of AI-based management subsystems for automatic TBM operations and presents recent contributions in this field. The paper evaluates modeling, monitoring, and control subsystems and suggests research paths for integrating existing management subsystems into TBM automation.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Alireza Shamshiri, Kyeong Rok Ryu, June Young Park
Summary: This paper reviews the application of text mining and natural language processing in the construction field, highlighting the need for automation and minimizing manual tasks. The study identifies potential research opportunities in strengthening overlooked construction aspects, coupling diverse data formats, and leveraging pre-trained language models and reinforcement learning.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zhengyi Chen, Hao Wang, Keyu Chen, Changhao Song, Xiao Zhang, Boyu Wang, Jack C. P. Cheng
Summary: This study proposes an improved coverage path planning system that leverages building information modeling and robotic configurations to optimize coverage performance in indoor environments. Experimental validation shows the effectiveness and applicability of the system. Future research will focus on further enhancing coverage ratio and optimizing computation time.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Yonglin Fu, Junjie Chen, Weisheng Lu
Summary: This study presents a review of human-robot collaboration (HRC) in modular construction manufacturing (MCM), focusing on tasks, human roles, and interaction levels. The review found that HRC solutions are applicable to various MCM tasks, with a primary focus on timber component production. It also revealed the diverse collaborative roles humans can play and the varying levels of interaction with robots.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Qiong Liu, Shengbo Cheng, Chang Sun, Kailun Chen, Wengui Li, Vivian W. Y. Tam
Summary: This paper presents an approach to enhance the path-following capability of concrete printing by integrating steel cables into the printed mortar strips, and validates the feasibility and effectiveness of this approach through experiments.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Honghu Chu, Lu Deng, Huaqing Yuan, Lizhi Long, Jingjing Guo
Summary: The study proposes a method called Cascade CATransUNet for high-resolution crack image segmentation. This method combines the coordinate attention mechanism and self-cascaded design to accurately segment cracks. Through a customized feature extraction architecture and an optimized boundary loss function, the proposed method achieves impressive segmentation performance on HR images and demonstrates its practicality in UAV crack detection tasks.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Daniel Lamas, Andres Justo, Mario Soilan, Belen Riveiro
Summary: This paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Kahyun Jeon, Ghang Lee, Seongmin Yang, Yonghan Kim, Seungah Suh
Summary: This study proposes two enhanced unsupervised text classification methods for domain-specific non-English text. The results of the tests show that these methods achieve excellent performance on Korean building defect complaints, outperforming state-of-the-art zero-shot and few-shot text classification methods, with minimal data preparation effort and computing resources.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Yoonhwa Jung, Julia Hockenmaier, Mani Golparvar-Fard
Summary: This study introduces a transformer-based natural language processing model, UNIfORMATBRIDGE, that automatically labels activities in a project schedule with Uniformat classification. Experimental results show that the model performs well in matching unstructured schedule data to Uniformat classifications. Additionally, the study highlights the importance of this method in developing new techniques.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi, Keivan Bamdad, Tosin Famakinwa
Summary: This paper introduces a digital twin technology combining Building Information Modelling and the Internet of Things for the construction industry, aiming to optimize building conditions. The technology is implemented in a university library, successfully achieving real-time data capture and visual representation of internal conditions.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zaolin Pan, Yantao Yu
Summary: The construction industry faces safety and workforce shortages globally, and worker-robot collaboration is seen as a solution. However, robots face challenges in recognizing worker intentions in construction. This study tackles these challenges by proposing a fusion method and investigating the best granularity for recognizing worker intentions. The results show that the proposed method can recognize multi-granular worker intentions effectively, contributing to seamless worker-robot collaboration in construction.
AUTOMATION IN CONSTRUCTION
(2024)
