Decentralizing construction AI applications using blockchain technology

被引:41
作者
Adel, Kareem [1 ]
Elhakeem, Ahmed [1 ]
Marzouk, Mohamed [2 ]
机构
[1] Arab Acad Sci Technol & Maritime Transport AASTMT, Coll Engn & Technol, Construct & Bldg Engn Dept, Cairo, Egypt
[2] Cairo Univ, Fac Engn, Struct Engn Dept, Giza, Egypt
关键词
Blockchain; Trusted Decentralized AI; Chaincodes; Decentralized Inference; Decentralized Learning; Construction Cost Estimate; PARAMETRIC COST ESTIMATION; NEURAL-NETWORK MODEL; INDUSTRY;
D O I
10.1016/j.eswa.2022.116548
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Decentralizing the Artificial Intelligence (AI) applications is deemed the next wave of Blockchain Technology (BT) in the construction industry. Most of previous research studies employed the AI and the BT separately with limited efforts providing a conceptual view for possible convergence in real-life applications. Nevertheless, such efforts do not address construction applications. This research introduces a novel tailorable decentralized AI system that utilizes BT as a computing-oriented technology. The proposed system is developed as an inference engine while having a number of interesting features. First, the system validates and audits the decision-making process while sharing and recording the input data and the computed outcomes in a synchronized trusted manner. Second, the system allows the formation of distributed AI repository that can absorb and manage concurrent use-cases while targeting different scopes and covering diverse AI branches. Third, it provides a workable solution for the AI applications' distribution problem, which hinders their wide employment. Fourth, the introduced system guarantees sustainable versioning and evolution over time for AI applications based on their performance or the newly acquired data. A case study of estimating the construction cost for road projects is provided to illustrate the system's workability and demonstrate its performance.
引用
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页数:11
相关论文
共 88 条
[41]  
Kim G.H., 2013, J. Build. Constr. Plan. Res, V1, P1, DOI [DOI 10.1016/j.autcon.2008.09.007, DOI 10.4236/JBCPR.2013.11001]
[42]   Hybrid models of neural networks and genetic algorithms for predicting preliminary cost estimates [J].
Kim, GH ;
Seo, DS ;
Kang, KI .
JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2005, 19 (02) :208-211
[43]   Neural network model incorporating a genetic algorithm in estimating construction costs [J].
Kim, GH ;
Yoon, HE ;
An, SH ;
Cho, HH ;
Kang, KI .
BUILDING AND ENVIRONMENT, 2004, 39 (11) :1333-1340
[44]   Artificial Neural Network Blockchain Techniques for Healthcare System: Focusing on the Personal Health Records [J].
Kim, Seong-Kyu ;
Huh, Jun-Ho .
ELECTRONICS, 2020, 9 (05)
[45]   Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis [J].
Kim, Suhyeon ;
Park, Haecheong ;
Lee, Junghye .
EXPERT SYSTEMS WITH APPLICATIONS, 2020, 152
[46]  
조홍규, 2013, [Journal of the Korea Institute of Building Construction, 한국건축시공학회지], V13, P66, DOI 10.5345/JKIBC.2013.13.1.066
[47]   Exploring the potentials of blockchain application in construction industry: a systematic review [J].
Kiu, M. S. ;
Chia, F. C. ;
Wong, P. F. .
INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT, 2022, 22 (15) :2931-2940
[48]   Integrating blockchain technology with artificial intelligence for cardiovascular medicine [J].
Krittanawong, Chayakrit ;
Rogers, Albert J. ;
Aydar, Mehmet ;
Choi, Edward ;
Johnson, Kipp W. ;
Wang, Zhen ;
Narayan, Sanjiv M. .
NATURE REVIEWS CARDIOLOGY, 2020, 17 (01) :1-3
[49]   Integrated digital twin and blockchain framework to support accountable information sharing in construction projects [J].
Lee, Dongmin ;
Lee, Sang Hyun ;
Masoud, Neda ;
Krishnan, M. S. ;
Li, Victor C. .
AUTOMATION IN CONSTRUCTION, 2021, 127
[50]  
Li J., 2020, 37 CIB W78 INFORM TE