TY - JOUR
T1 - Two-layer Adaptive Blockchain-based Supervision model for off-site modular housing production
AU - Li, Xiao
AU - Wu, Liupengfei
AU - Zhao, Rui
AU - Lu, Weisheng
AU - Xue, Fan
N1 - Funding Information:
The work presented in this paper was financially supported by the Hong Kong Innovation and Technology Commission (ITC) with the Innovation and Technology Fund (ITF) (No. ITP/029/20LP ). This funding source had no role in the design and conduction of this study.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/6
Y1 - 2021/6
N2 - By manufacturing housing products off-site and assembling on-site, modular construction can significantly improve the housing supply efficiency, particularly for high-density cities. However, off-site modular housing production (OMHP) supervision is currently problematic. The production parties are reluctant to provide detailed private data; Even worse, the submitted operation records can be easily fabricated, tampered with, or hard to trace the responsibility. This study develops an innovative Two-layer Adaptive Blockchain-based Supervision (TABS) model for OMHP. The first layer includes the adaptive private sidechains of participants. The second layer is the main blockchain for communication and ‘trading’ among all participants. Benefitted from the unique adaptive two-layer structure, TABS can avoid tampering with operation records by the main blockchain and drive the participants to publish their operation records promptly without privacy leaks. A system prototype was also developed to evaluate the performance of the TABS model. The results indicated that the TABS model could enhance privacy and reduce storage costs at an acceptable latency level. The findings of this study can pave the avenue for a tamper-proof and privacy-preserving supervision mechanism in the architecture, engineering, and construction industry.
AB - By manufacturing housing products off-site and assembling on-site, modular construction can significantly improve the housing supply efficiency, particularly for high-density cities. However, off-site modular housing production (OMHP) supervision is currently problematic. The production parties are reluctant to provide detailed private data; Even worse, the submitted operation records can be easily fabricated, tampered with, or hard to trace the responsibility. This study develops an innovative Two-layer Adaptive Blockchain-based Supervision (TABS) model for OMHP. The first layer includes the adaptive private sidechains of participants. The second layer is the main blockchain for communication and ‘trading’ among all participants. Benefitted from the unique adaptive two-layer structure, TABS can avoid tampering with operation records by the main blockchain and drive the participants to publish their operation records promptly without privacy leaks. A system prototype was also developed to evaluate the performance of the TABS model. The results indicated that the TABS model could enhance privacy and reduce storage costs at an acceptable latency level. The findings of this study can pave the avenue for a tamper-proof and privacy-preserving supervision mechanism in the architecture, engineering, and construction industry.
KW - Blockchain
KW - Modular construction
KW - Modular housing production
KW - Off-site construction
KW - Two-layer adaptive blockchain
UR - http://www.scopus.com/inward/record.url?scp=85102139888&partnerID=8YFLogxK
U2 - 10.1016/j.compind.2021.103437
DO - 10.1016/j.compind.2021.103437
M3 - Journal article
AN - SCOPUS:85102139888
SN - 0166-3615
VL - 128
JO - Computers in Industry
JF - Computers in Industry
M1 - 103437
ER -