Blockchain-enabled IoT-BIM Platform for Supply Chain Management in Modular Construction
Xiao Li 1*, Weisheng Lu 2, Fan Xue 3, Liupengfei Wu 4, Rui Zhao 5, Jinfeng Lou 6, and Jinying Xu 7
This is the peer-reviewed, post-print version of the paper:
Li, X., Lu, W., Xue, F., Wu, L., Zhao, R., Lou, J., & Xu, J. (2022). Blockchain-enabled
IoT-BIM Platform (BIBP) for supply chain management in modular construction.
Journal of Construction Engineering and Management, 148(2), 04021195. Doi:
10.1061/(ASCE)CO.1943-7862.0002229
This material is shared under the permission of ASCE, and may be downloaded for personal
use only. Any other use requires prior permission of ASCE. The official version of this paper
can be accessed at https://doi.org/10.1061/(ASCE)CO.1943-7862.0002229

Abstract
Configuring a trustworthy IoT-enabled BIM Platform (IBP) is significant for modular
construction to ensure transparency, traceability, and immutability throughout its fragmented
supply chain management. However, most current IBPs are designed adopting a centralized
system architecture, which fails to achieve a decentralized and effective one to ensure a
single point of truth in BIM and prevent a single point of failure in IoT networks. To address
this challenge, this study introduces permissioned blockchain with IBP and proposes a novel
service-oriented system architecture of blockchain-enabled IoT-BIM platform (BIBP) for the
data-information-knowledge (DIK) driven supply chain management in modular
construction. Firstly, Infrastructure as a Service (IaaS) is designed with hardware, core
technologies, and protocols to offer accurate data from daily practice to blockchain BIM.
Blockchain BIM as a Service (BaaS) is then developed within the permissioned blockchain to
ease the interoperability of the information, semantics, and meaningful inferences.
Postdoctoral Fellow, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong
SAR.

1

Email: xl1991@hku.hk, Tel.: (852) 5537 0842,
ORCiD: 0000-0001-9702-4153; * Corresponding author
Professor, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong SAR.

2

Email: wilsonlu@hku.hk, Tel.: (852) 3917 7981,
ORCiD: 0000-0003-4674-0357;
3
Assistant Professor, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong
SAR.
Email: xuef@hku.hk, Tel.: (852) 3917 4174, Fax: (852) 2559 9457,
ORCiD: 0000-0003-2217-3693:
Ph.D. student, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong SAR.

4

Email: u3545425@connect.hku.hk, Tel.: (852) 6930 8019,
ORCiD: 0000-0002-3768-9142
5
Research Assistant, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong
SAR.
ORCiD: 0000-0003-1993-3129
Email: ruizhao@hku.hk, Tel.: (852) 6998 6845,
Ph.D. student, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong SAR.

6

Email: waseljf@connect.hku.hk, Tel.: (852) 9423 1962,
ORCiD: 0000-0001-5748-0146
7
Postdoctoral Fellow, Department of Real Estate and Construction, The University of Hong Kong, Hong Kong
SAR.
Email: jinyingxu@connect.hku.hk, Tel.: (852) 6025 1696,

1

ORCiD: 0000-0001-9589-6396;

Furthermore, Software as a Service (SaaS) is configured with decentralized applications to
achieve knowledgeable operations or processes with a crash fault-tolerant consensus
mechanism. The demonstrative case study in a modular student residence project evaluates
the proposed BIBP system prototype with the performance analysis of storage cost,
throughput, latency, privacy, and feedback from stakeholders. The results indicate that BIBP
has an effective system architecture with acceptable throughput and latency, can save storage
costs to achieve a single point of truth in BIM, and avoid a single point of failure for IoT
networks with privacy and security preserving mechanisms.
Keywords: Blockchain, IoT, BIM, Supply Chain Management, Modular Construction

1 Introduction
The construction industry contributed a considerable 13% share of global Gross Domestic
Product (GDP) at 7% employment of the world’s working population (Barbosa et al., 2017).
However, it is encountering challenges such as declining total productivity, professional labor
shortfall, and the aging workforce. To improve these issues, modular construction has been
adopted worldwide, such as in Singapore (Hwang et al., 2018), UK (Innella et al., 2019),
Canada (Liu et al., 2019), United States (Ramaji and Ali, 2016), Australia (Thai et al., 2020),
and China (Liu et al., 2017). Practices in these countries have demonstrated its benefits,
including shortened construction time, reduced site labor, minimized construction waste, and
improved environment and safety (Li et al., 2019a).
Modular construction becomes more demanding in high-density and resource-limited cities,
such as Hong Kong, which take advantage of supply chain management (SCM) to outsource
every piece of prefabricated components and transport them to local sites for installation (Luo
et al., 2020). However, the rising fragmentation of such supply chain has attracted much more
attention from stakeholders for efficient collaboration, visibility, accountability, and
traceability, especially as more expensive assets such as prefabricated modules and units are
produced and shipped off-site with the travel restrictions during coronavirus pandemic (Li et
al., 2021).
Academics and industry have collaboratively developed practical platforms for SCM in
prefabricated construction by embracing Building Information Modeling (BIM) and Internet
of Things (IoT) (Li et al., 2018a; Zhong et al., 2017; Xu et al., 2018; Zhai et al., 2019). These
multi-dimensional IoT-BIM platforms can help collect near real-time data to increase
visibility and traceability in production, logistics, and on-site installation. Different
stakeholders can then track a project's cost and schedule (Li et al., 2020).
However, the current IoT-BIM Platform works in a centralized way, leading to several issues:
(1) although IoT does establish the connections between construction resources (e.g.,
prefabricated modules) and BIM, it cannot ensure the single point of truth for any change in
2

BIM. It leaves room for human manipulation of BIM models without provenance (Xue and
Lu, 2020); (2) random errors, noises, or malicious data generated from IoT sensors can result
in a single point of failure for IoT networks, reducing data quality for BIM and negatively
affecting the trustworthiness of IoT-BIM (Lee et al., 2021); (3) an open IoT-BIM platform
can boost construction companies' competitiveness as more and more stakeholders (e.g.,
customers) under industry 4.0 prefer to be involved in the transparent construction processes
(Lu et al., 2021). However, the privacy and security of the open IoT-BIM can not be
guaranteed in the existing system architecture. These persistent issues challenge the extensive
and profound impact of IoT-BIM solutions for SCM in modular construction.
Blockchain technology is well-known for its distributed database, trustworthy digital ledger,
and a complete no-trust peer network with consensus protocols (Cachin, 2016). Recently,
blockchain is also introduced into BIM and IoT to record the BIM modification history and
build trust in the distributed IoT network (Zheng et al., 2019; Xue and Lu, 2020; Lu et al.,
2021; Li et al., 2020). The integration of Blockchain and IoT-BIM may address the issues of
the IoT-BIM platform in SCM of modular construction. However, configuring a blockchainenabled IoT-BIM platform (BIBP) for SCM in modular construction is now staying at a
concept rather than a developed system and is still in its infancy. Designing effective system
architecture with lower storage cost, lower latency, and higher throughput to ensure a single
point of truth for BIM and avoid a single point of failure of IoT is challenging.
Thus, this study aims to develop a brand new BIBP for SCM in modular construction. To this
end, it has three concrete objectives: (1) establishing a Data-information-knowledge (DIK)
driven supply chain management model for modular construction as a reference model for
BIBP; (2) instantiating this theoretical model by proposing an effective system architecture of
BIBP; and (3) validating the system architecture by implementing a prototype, using a case
study as an evaluation experiment. The remainder of the paper is structured as follows.
Subsequent to this introductory section is Section 2, which elaborates on related works of
modular construction, supply chain management, IoT, BIM, and blockchain. Section 3
delineates a DIK-driven SCM model, followed by the BIBP system architecture. Section 4
provides a demonstrative evaluation experiment to illustrate and validate the functions and
system architecture of BIBP. Finally, discussions are conducted in Section 5, and conclusions
are drawn in Section 6.

2 Background
2.1 Supply Chain Management in Modular Construction (SCM-MC)
Modular construction is a revolutionary construction method whereby 3D-volumetric fully
finished modules are prefabricated in off-site factories and then shipped to the construction
site for installation (Yin et al., 2019). Modular construction is distinguished by an advanced
planning and optimization approach for the supply chain. According to Mentzer et al. (2001),
3

a supply chain is a network of actors (e.g., organizations or individuals) engaged in the flows
of goods, services, finances, and information from a supplier to a customer. Therefore, SCM
in modular construction can be defined as ensuring the flow of prefabricated products,
services, data, information, and even knowledge to be smoothly delivered from production,
logistics to on-site installation.
Handling SCM of modular construction well in practice is challenging due to the old-decade
issues, such as lack of trust, fragmentation, and discontinuity. Trust is commonly understood
as the positive expectations one party has about another party’s intentions, and trust is
fundamental for a transparent and secured supply chain (Luo et al., 2020). However, the
construction industry is infamous for its lacking trust and prevalent adversarial relationship
with one-off organizational settings, resulting in widespread claims, opportunism, risk
aversion, less flexibility, mediocre quality, high cost, and poor value for money (MacLeamy,
2004; Bankvall et al., 2010). The most worth-noticing cases in SCM for lack of trust are
product provenance issues and disputable inspection.
Fragmentation mainly results from the massive stakeholders and multiple stages (Hsu et al.,
2019). SCM in modular construction involves more geographically distributed stakeholders,
e.g., manufacturers, materials suppliers, and logistics agencies. To ensure resilient process
management and assured quality, these stakeholders must keep frequent communication in
multiple stages, e.g., design, production, storage, logistics, and on-site installation (See
Fig.1). Thus, producing and delivering prefabricated modules at the right time and place to
the right person requires a coordinated SCM system. However, the current SCM system in
modular construction is inconsiderate and lacks multi-user-oriented functional modules, such
as compliance check, process control, and quality assurance.
The discontinuity can be ascribed to the low level of information traceability and
immutability. For example, product data collected from the factory to the construction site is
still mainly dependent on manual operations and paperwork (Zhai et al., 2019). Therefore,
such time-consumed manual processes may bring in input errors, file missing, and data
tampering. Furthermore, logistic companies still fail to achieve just-in-time deliveries due to
information delays, as the lack of a synergistic information platform hinders the visibility,
traceability, and even knowledge-based business intelligence of SCM (Li et al., 2018a; Li et
al., 2019b). Together, these pain points stimulate the need for data-information-knowledge
(DIK) driven SCM models in modular construction to ensure improved data privacy,
effective information sharing, rapid knowledge consensus.

4

Figure 1. Process management and quality assurance in SCM-MC.
2.2 BIM, IoT, Blockchain, and their Integration
Building Information Modeling (BIM) has been widely used to improve the fragmentation
and discontinuity in the construction SCM (Li et al. 2019a; Hijazi et al. 2021; Deng et al.
2019). The BIM kernel is “information,” which helps stakeholders in construction SCM be
informed of one another’s operations through collaboration. The definition of the above
information can be supported by OpenBIM. One of the most salient OpenBIM standards is
the Industry Foundation Classes (IFC), a commonly used schema for data exchange that
promotes BIM interoperability among stakeholders. However, effective communication and
responsible decision-making among stakeholders require real-time interaction between the
physical world and BIM.
The Internet of Things (IoT) is a growing concept that can help provide BIM with real-time
data to link the physical resources with virtual BIM objects (Dave et al., 2018). Academia
and industry have developed many enabling technologies to realize the concept of IoT, such
as radio-frequency identification, near-field communication for short-range wireless (Xue et
al., 2018), 5G for medium-range wireless (Li et al., 2018b), and low-power wide-area
networking (e.g., LoraWan, NB-IoT) for long-range wireless (Mekki et al., 2018). Niu et al.
(2016) also proposed a robust IoT model in construction, namely smart construction objects
(SCOs), to augment construction resources with smartness.
Integrating IoT data with BIM in real-time has become an essential paradigm for developing
digital twin applications to enhance construction productivity. These applications have been
widely utilized in monitoring construction resource and progress (Li et al., 2018a),
occupational health and safety management (Kanan et al., 2018), construction logistics and
supply chain management (Zhong et al., 2017), and facility management (Cheng et al., 2020).
To achieve these applications, it needs numerous building blocks, such as system
architecture, open BIM standards for interoperability, and protocols of information
integration and management (Xu et al., 2018).
5

Service-Oriented Architecture (SOA) is commonly used to develop IoT-enabled BIM
platforms by combining various web services. However, SOA still lacks a useful design
pattern to achieve real-time BIM model updates, two-way interactions between IoT and BIM,
and integration with other technologies (e.g., blockchain). These mainly rely on the
interoperable open BIM standards and protocols for IoT-BIM integration. Tang et al. (2019)
also summarized five mainstream approaches for integrating time-series IoT data with
contextual BIM data. For example, integrating semantics web (for BIM) and relational
database (for IoT) has been identified as a promising hybrid approach for IoT-enabled BIM
platforms. However, the integration of BIM and IoT alone is insufficient to ensure data
privacy and security and truly achieve trust among stakeholders. For example, the shared
cloud BIM model and its data can be manipulated, and IoT sensors (e.g., RFID, GPS) may
suddenly be powerless or noises reported to reduce data quality. Blockchain seems to hold
the key.
Blockchain is a distributed ledger of relevant data and transactions that are voluntarily agreed
upon and shared across all peer-to-peer network users. (Nakamoto, 2008). Four components
support a blockchain to function: cryptography, a distributed database, consensus mechanism,
and smart contracts (Zheng et al., 2017). Cryptography, e.g., hashing algorithms, is applied to
encrypt transactions based on the accepted protocol that makes the data hard to be tampered
with (Beck et al., 2016). Distributed ledgers are also supported by an extensive network of
computers, which records all data in each participant's ledger. The consensus defines the
necessary agreement of maintaining network-wide synchronization of data transactions
(Nguyen and Kim, 2018). Smart contracts are self-executing contracts that act automatically
based on a consensus mechanism when certain trigger circumstances are met. (Buterin,
2014). Permissionless and permissioned blockchain platforms are now available. (Helliar et
al., 2020). A permissionless blockchain is entirely decentralized, allowing anybody to access
the data contained in blocks, such as Bitcoin and Ethereum (Buterin, 2014). Only a few
recognized users can validate transactions and access block data in a permissioned
blockchain., such as Hyperledger Fabric (Cachin, 2016). Permissionless blockchain
emphasizes openness and decentralization, whereas permissioned blockchain uses
deterministic consensus methods to increase throughput. (Gupta et al., 2020). This renders
permissioned blockchains more accessible to projects at a time-sensitive level regarding
transparency, traceability, immutability, decentralization, privacy, and smartness (Qian and
Papadonikolaki, 2020). However, few studies have investigated blockchain technology in
SCM of modular construction. For example, Wang et al. (2020) established a blockchainbased information management system for a precast supply chain to improve traceability and
information communication. Zhang et al. (2020b) further investigated an integrated
framework of the quality traceability system for prefabricated components.
In addition, numerous studies have explored the integration of blockchain and BIM, or
integration of blockchain and IoT, separately. For example, Zheng et al. (2019) proposed a
6

blockchain-based BIM data audit mechanism to record the BIM modification history and
ensure the integrity and provenance of BIM data. Xue and Lu (2020) developed a semantic
differential transaction approach to minimize information redundancy and improve
information interoperability in integrating BIM and blockchain. Moreover, Lu et al. (2021)
proved that blockchain could build trust in the distributed IoT network via a sidechain and
provide confidence in such massive IoT-oriented data sources for construction SCM. Lee et
al. (2021) designed an integrated digital twin and blockchain system for traceable data
transmission. The blockchain authenticates and provides trust to all data transactions to the
digital twin, while the digital twin updates BIM in near real-time utilizing IoT. The previous
studies demonstrate that the fusion of blockchain and IoT-BIM may have the potential to
address the current issues of IoT-enabled BIM platforms in SCM of modular construction.
However, they mainly focus on data traceability. Developing and designing an effective
system architecture with lower storage cost, lower latency, and higher throughput to ensure a
single point of truth for BIM, avoid a single point of failure of IoT, and map the complex
data-information-knowledge paradigm to the SCM processes/end-users is challenging.
2.3 Research Gaps
Through the above analysis, three observations can be summarized: (1) there is a lack of a
useful operation model for guiding trustworthy, integrated, and continuous SCM in modular
construction; (2) the development and configuration of functions, services, and applications
with such model faces challenges, e.g., unaccountable data, inconsiderate information, and
dull knowledge; (3) integration of blockchain with IoT-BIM could be the solution but need an
effective system architecture at the current stage for further ensuring a single point of truth
for BIM and avoiding a single point of failure of IoT.

3 System Architecture of BIBP
As SCM's business processes in modular construction are fragmented due to involving more
stakeholders, stages, and technologies, data from multimedia and multi-modal information
becomes more complex and semantically meaningful. Consequently, the cross-relation
among various data in SCM processes brings the semantic information into the data,
information, and knowledge (DIK) paradigm. The DIK paradigm has been a successful
framework for combining and elevating the multimodal data into the models of information
and knowledge (Zins, 2007; Zhang et al., 2020a). Thus, it can help map the evidence from
SCM practice (data, e.g., facts, signals, symbols), system (information, e.g., semantics,
descriptions, functions) to users (knowledge, e.g., cognition, decision, evaluation). This
mapping has the potential to contribute to the design of BIBP via the following aspects: (1) It
can connect the service, virtual and physical elements in SCM-MC business processes from
the perspective of DIK; (2) It can help identify the data sources, information requirements,
and knowledge applications in SCM-MC processes for BIBP; (3) It can help configure the
BIBP network by forming design dimensions and system organizations.
7

3.1 DIK-oriented SCM-MC model
This study proposes a DIK-oriented SCM model for modular construction. As shown in
Fig.2, this model presents its physical, virtual, and service layers with five dimensions:
physical, data, information, knowledge, and service spaces.
The physical layer observes the real-time status of processes and resources in physical space
(PS). For example, production-transportation-installation flow and construction objects (e.g.,
man, machine, material, method, environment (4M1E)) can serve in a decentralized IoT
network. All data (e.g., structured, semi-structured, nonstructured) captured from PS can be
mapped to data space (DS), and PS then communicates with the upper level through DS in a
publish-subscribe manner.
The virtual layer tries to mirror the virtual resources and processes using BIM and make PS
work at its optimal state by incorporating information space (IS) and knowledge space (KS).
DS offers interfaces for IS and KS to access the data. IS can describe and function the
geometric and non-geometric information from the virtual BIM environment. KS can
integrate knowledge models (e.g., learning, prediction, evaluation, reasoning) to serve as a
brain to handle various SCM issues (e.g., constraints, risks, uncertainties) in PS, DS, or IS.
The service layer bundles SCM processes and resources into services to make it easier for
different SCM stakeholders in the service space (SS) to communicate.. For example,
decentralized applications (Dapps) for process management and quality assurance could be
stakeholders' immediate demands.

8

Figure 2. Three-layer DIK-oriented SCM model in modular construction
3.2 Overall System Architecture of BIBP
Based on the DIK-driven SCM model, BIBP is the integration of blockchain, IoT, and BIM,
where IoT ubiquitously connects processes and resources in PS to the BIM-based IS while
blockchain connects DS, IS and KS of BIBP with double chains in a secure, immutable,
transparent, traceable, decentralized, and smart manner. Thus, BIBP is formalized as:
Definition 1 BIBP:= {𝑃𝑃𝑃𝑃𝐼𝐼𝐼𝐼𝐼𝐼 , 𝐷𝐷𝐷𝐷, 𝐼𝐼𝐼𝐼𝐵𝐵𝐵𝐵𝐵𝐵 , 𝐾𝐾𝐾𝐾, 𝑆𝑆𝑆𝑆} ⋈ 𝐵𝐵𝑃𝑃𝑃𝑃−𝐷𝐷𝐷𝐷−𝐼𝐼𝐼𝐼−𝐾𝐾𝐾𝐾−𝑆𝑆𝑆𝑆

Where 𝑃𝑃𝑃𝑃𝐼𝐼𝐼𝐼𝐼𝐼 connects physical processes and resources of PS to virtual 𝐼𝐼𝐼𝐼𝐵𝐵𝐵𝐵𝐵𝐵 , DS, KS, and
SS are the other three dimensions of BIBP. 𝐵𝐵𝑃𝑃𝑃𝑃−𝐼𝐼𝐼𝐼−𝐷𝐷𝐷𝐷−𝐾𝐾𝐾𝐾−𝑆𝑆𝑆𝑆 denotes the blockchain
networks and the transaction logics of five dimensions to support smart SCM in modular
construction.

9

According to the BIBP definition, a system architecture of BIBP for configuring the DIKdriven SCM model is developed in Fig.3. Three layers and five dimension spaces in SCM are
fused into a three-layer service-oriented architecture (SOA), including Infrastructure as a
Service (IaaS), Blockchain BIM as a service (BaaS), and Software as a Service (SaaS). The
platform uses the XaaS (Anything as a Service) paradigm to bridge the SCM practices and
multiple stakeholders' demands in modular construction.

Figure 3. System architecture of BIBP for SCM in modular construction
IaaS includes hardware, core technologies, and protocols (e.g., IoT protocols and open
BlockchainBIM standards), which are used to extract SCM data from daily practice to
blockchain BIM. Each resource (4M1E) and process in SCM are connected with their virtual
twin via IoT, serving as transaction monitoring nodes to observe statutes (e.g., disturbances,
constraints, abnormal conditions). Blockchain IoT interfaces can offer local optimal-state
operation control based on the smart contract. For example, the accelerometer mounted on
prefabricated modules can help measure their vibrations during transportation. Once
vibrations exceed the threshold, the accelerometer can publish this transaction proposal to the
blockchain, and alerts to drivers and other stakeholders can be triggered by smart contracts
when the proposed transaction has reached consensus in the decentralized network.

10

BaaS structure and interfaces hold the key to information management in the BIBP for interoperating
the information, semantics, and meaningful inferences. There are two primary modules to achieve
BaaS functionality. One is the blockchain BIM system to record the changes of BIM in the
blockchain. The other is the open blockchain BIM interfaces, which extend IoT properties in IFC
within the new blockchain BIM system. Based on the BaaS, knowledge models (KMs) for process
management (PM) and quality assurance (QA) can be developed.

SaaS meets multiple stakeholders' demands with the applications of knowledge-based
stakeholder communication, PM, QA, BIM, and IoT through various KMs. These
applications collect statutes of resources and processes to perceive instantaneous SCM
performance via learning and evaluation. And then, these applications invoke KMs via smart
contracts to intelligently improve the performance of SCM in modular construction.
Furthermore, all SCM resources and processes are grouped as DIK services within the
blockchain to serve end users and other connected systems (e.g., ERP, city information
modeling (CIM), GIS) in a service-oriented manner.
The system architecture of BIBP can not only connect physical construction resources to the
virtual BIM system via traceable and authentic IoT but also define a smart contract-oriented
PM/QA mechanism within the Blockchain BIM system to support the real-time improvement
of SCM in modular construction. Furthermore, this configuration can allow BIBP to work as
a whole to offer innovative SCM services, helping modular construction companies better
compete in construction 4.0.
3.2.1 Infrastructure as a Service (IaaS)
The hardware and protocols in IaaS can serve in edge and cloud infrastructures (See Fig.4
(a)). The edge comprises IoT-enabled construction resources (e.g., 4M1E), communication
protocols, gateway nodes (GNs), broker nodes (BNs), and computing unit nodes (CUNs).
Construction resources include man (e.g., worker), machine (e.g., crane, vehicle), material
(e.g., prefabricated modules), method (e.g., inspection standards), environment (e.g.,
production plant, construction site). The real-time statuses of construction resources are
captured by IoT devices and sensors with various communication protocols. GNs work as the
interface to preprocess the data from IoT and forward the unified data to BNs, CUNs, BIM
nodes (BIMNs), and KM nodes (KMNs), meanwhile receiving and transmit their responses
and orders to IoT-enabled construction resources. BNs assign proper CUNs to process the
time-sensitive tasks at the edge or pass on the complex tasks to the cloud. BIMNs update the
virtual models by incorporating the data from the edge. Cloud offers sufficient computing and
storage capacity for BIM and KMs to handle computing-intensive but latency-tolerant tasks
or share burdens from BNs and CUNs.
A smart IoT plan is proposed in IaaS, where smart IoT can also work as an information
exchange agent is called an “oracle” in the blockchain. It can be a flexible board of IoT
sensors. For example, inertial measurement units and air pressure units can compensate the
11

GPS positions on precise movements and height data. Furthermore, for facility management,
a supplement of passive RFID and QR codes can adhere to the prefabricated modules for a
long time. For certain IoT applications, a mix of diverse IoT design profiles can provide the
best performance-price ratio. Fig.4 (b) shows some detailed IoT plans. The initial plan
includes two models: (1) A single low-energy GPS sensor for LBS logistics offshore. (2) For
off-site plant and on-site assembly PM/QA, high-frequency, numerous movements and
environmental sensors are required.
Hardware and software protocols in the IaaS are designed to regulate the synchronization of
SCM reality. As shown in Fig.4 (c), the SCM process involves several stages and various
stakeholders. There are existing means to manage the SCM activities in practice, such as asdesigned BIM, documents, and orders of prefabricated modules, construction IoT for SCM,
and the progress monitoring system. Therefore, comprehensive hardware and software
protocols fulfill the need to map and integrate the data in existing means and systems to the
BIBP platform.
In comparison to existing blockchain systems in the construction industry, this research offers
open blockchain IoT-BIM as the Infrastructure, which is based on an open BIM standard that
is expanded from IFC. Extending the existing open BIM standard IFC (ISO 16739-1:2018) is
a necessity in IaaS. Fig.4 (d) shows that the extended BIM standard can handle more
functions than the conventional IFC standard. The new extension in IFC involves two parts.
The first part is a semantic deferential transition (SDT) model developed by Xue and Lu
(2020) for blockchain computability. As BIM models are usually massive in size, the
blockchain cannot handle massive data due to network capability. Also, as shared by multiple
stakeholders, BIM is subjected to simultaneous changes by different parties simultaneously.
Therefore, a well-defined extension model to bridge the fundamental gap between the IFC
and blockchain can manage the real-time, simultaneous changes as IFC change consensuses.
The other extension to IFC is the IoT properties, which were non-existed in the current IFC
properties. Examples include production line, logistics company, driver ID, defects, and
maintenance history. These new IoT properties are attached to the IFC standard directly.

12

Figure 4. Hardware and protocols of BIBP.
3.2.2 Blockchain BIM as a Service (BaaS)
BIBP adopts the Hyperledger Fabric as the framework with the following advantages: a. it is
a closed permission-based network that can provide higher throughputs and is very suitable
for the scenario of project-based SCM in modular construction; b. it is under a modular
architecture facilitating plug-in components development; c. It ensures consensus efficiency
among peer nodes to enhance performance and scalability; d. Channels designed in Fabric
offer a way to separate sensitive data; e. The Fabric with LevelDB facilitates query functions.
BIBP includes the services of the BIBP network, ledger model, and smart contracts in BaaS.
(1) BIBP network service: As shown in Fig.5, the BIBP network is a double-chain (e.g.,
double channels in Hyperledger Fabric) structure that offers services of ledgers (L1, L2) and
smart contracts (S1, S2) to facilitate DIK-driven agile SCM-MC. Each dimension of DIKSCM-MC can be considered as an organization 𝑅𝑅 ⊆ ℝ = {𝑅𝑅𝑃𝑃𝑃𝑃 , 𝑅𝑅𝐷𝐷𝐷𝐷 , 𝑅𝑅𝐼𝐼𝐼𝐼 , 𝑅𝑅𝐾𝐾𝐾𝐾 , 𝑅𝑅𝑆𝑆𝑆𝑆 } to join in
a network, where any participant in an organization needs a verifiable identity that is issued
with X.509 certificates by the corresponding certificate authority 𝐶𝐶𝐶𝐶 ⊆ ℂ𝔸𝔸 =
{𝐶𝐶𝐶𝐶𝑃𝑃𝑃𝑃 , 𝐶𝐶𝐶𝐶𝐷𝐷𝐷𝐷 , 𝐶𝐶𝐶𝐶𝐼𝐼𝐼𝐼 , 𝐶𝐶𝐶𝐶𝐾𝐾𝐾𝐾 , 𝐶𝐶𝐶𝐶𝑆𝑆𝑆𝑆 }. For example, 𝐶𝐶𝐶𝐶𝑆𝑆𝑆𝑆 distributes X.509 certificates to
recognize the participants (e.g., client, manufacturer, logistics provider, contractor) affiliated
to 𝑅𝑅𝑆𝑆𝑆𝑆 . Also, 𝑅𝑅𝐼𝐼𝐼𝐼 and 𝑅𝑅𝑆𝑆𝑆𝑆 control the network by defining the policy rules specified in
network configuration (NC). They also serve as network administration points for ordering
service 𝑂𝑂𝐼𝐼𝐼𝐼 and 𝑂𝑂𝑆𝑆𝑆𝑆 . 𝑅𝑅𝐼𝐼𝐼𝐼 , 𝑅𝑅𝐾𝐾𝐾𝐾 , and 𝑅𝑅𝑆𝑆𝑆𝑆 can form a consortium on channel #1 (C1) for
knowledge-based SCM services, where C1 is managed to comply with the policy rules
defined in channel configuration (CC1) and can be described as:
13

𝑆𝑆1

𝐿𝐿1

Definition 2 C1:= �𝐴𝐴𝑆𝑆𝑆𝑆 , … , 𝐴𝐴𝐼𝐼𝐼𝐼𝐼𝐼 , 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 � ↔ �𝑃𝑃𝑆𝑆𝑆𝑆 , 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 � ↔ {𝑂𝑂𝐼𝐼𝐼𝐼 , 𝑂𝑂𝑆𝑆𝑆𝑆 }

Where C1 comprises a set of stakeholder peer nodes 𝑃𝑃𝑆𝑆𝑆𝑆 ∈ 𝑅𝑅𝑆𝑆𝑆𝑆 , a set of process management
and quality assurance KMs peer nodes 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 ∈ 𝑅𝑅𝐾𝐾𝐾𝐾 , and a set of BIM peer nodes 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 ∈
𝑅𝑅𝐼𝐼𝐼𝐼 . DApps, such as stakeholder communication application 𝐴𝐴𝑆𝑆𝑆𝑆 , the intelligent PM-QA
application 𝐴𝐴𝐼𝐼𝐼𝐼𝐼𝐼 , and BIM application 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 are allowed to connect with C1 based on 𝐶𝐶𝐶𝐶𝑆𝑆𝑆𝑆 ,

𝐶𝐶𝐶𝐶𝐾𝐾𝐾𝐾 , and 𝐶𝐶𝐶𝐶𝐼𝐼𝐼𝐼 . Also, a smart contract packages S1 is adopted to produce business service,
knowledge, and information level transactions from DApps and peer nodes, and these
transactions are then sorted into blocks by 𝑂𝑂𝐼𝐼𝐼𝐼 or 𝑂𝑂𝑆𝑆𝑆𝑆 , and broadcast the validated transactions
to each peer node in the C1 where they received the immutable copy of the ledger L1.
Furthermore, 𝑅𝑅𝑃𝑃𝑃𝑃 , 𝑅𝑅𝐷𝐷𝐷𝐷 , and 𝑅𝑅𝐼𝐼𝐼𝐼 can form another consortium on channel #2 (C2) to achieve
efficient data and information management of DIK-SCM-MC. C2 is governed by CC2 and
formalized as:
𝑆𝑆2

𝐿𝐿2

Definition 3 C2:= {𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 , … , 𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆 } ↔ {𝑃𝑃𝐵𝐵𝐵𝐵 , 𝑃𝑃𝐶𝐶𝐶𝐶𝐶𝐶 , 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 } ↔ {𝑂𝑂𝐼𝐼𝐼𝐼 , 𝑂𝑂𝑆𝑆𝑆𝑆 }

Where C2 includes a set of BNs 𝑃𝑃𝐵𝐵𝐵𝐵 and CUNs 𝑃𝑃𝐶𝐶𝐶𝐶𝐶𝐶 , belonging to 𝑅𝑅𝐷𝐷𝐷𝐷 , and a set of BIM
peer nodes 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 ∈ 𝑅𝑅𝐼𝐼𝐼𝐼 . DApps, such as BIM application 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 , the IoT-enabled construction
resources, named as smart construction objects (SCOs), for data and resources management
application 𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆 are allowed to sit in the C2 based on 𝐶𝐶𝐶𝐶𝐼𝐼𝐼𝐼 , 𝐶𝐶𝐶𝐶𝐷𝐷𝐷𝐷 , and 𝐶𝐶𝐶𝐶𝑃𝑃𝑃𝑃 . S2 is applied to
generate operational data level transactions across DApps and peer nodes, which are then
sorted into blocks by 𝑂𝑂𝐼𝐼𝐼𝐼 or 𝑂𝑂𝑆𝑆𝑆𝑆 , and broadcast the validated transactions to each peer node in
the C2 where they received the immutable copy of the ledger L2.

Figure 5. BIBP network
14

(2) Ledger service: the ledger stores factual information about SCM objects, namely, BIMbased PM and QA on L1 for C1, and SCOs on L2 for C2. A ledger is owned and retained by
the decentralized peer nodes within the BIBP network. The ledger service in the BaaS
contains two components: a world state and a blockchain (See Fig.6). The former presents the
latest value of the objects' attributes, while the latter records the immutable history of all
transactions that resulted in these current values of the world state. The world state is
physically executed as a database (e.g., LevelDB, CouchDB) to offer simple and efficient
storage and retrieval of ledger states. The blockchain is structured as a sequential log of
interlinked blocks, where each block contains transactions in an ordered sequence, each
transaction representing a query or update to the world state. Each block can be defined as a
triple 𝐵𝐵𝑖𝑖 = {𝐻𝐻𝑖𝑖 , 𝐷𝐷𝑖𝑖 , 𝑀𝑀𝑖𝑖 }. A block header 𝐻𝐻𝑖𝑖 comprises three fields: block number, current
block hash, and previous block header hash. Block data 𝐷𝐷𝑖𝑖 includes an ordered sequence of
transactions. These transactions are recorded when the ordering service 𝑂𝑂𝐼𝐼𝐼𝐼 or 𝑂𝑂𝑆𝑆𝑆𝑆 generates
the block. Block metadata 𝑀𝑀𝑖𝑖 includes a timestamp, the certificate, public key, and signature
of the block creator. Each transaction 𝑇𝑇𝑖𝑖 contains a header, a cryptographic signature and a
proposal from DApp, responses as the smart contract’s output, and endorsements from the
required organizations with response signature.
As a blockchain data structure is standardized in a ledger model, the world states W1 and W2
in L1 and L2 can be defined as:
𝑄𝑄𝑄𝑄

Definition 4 W1:= �{⋃𝑖𝑖 〈𝐾𝐾𝑖𝑖𝑃𝑃𝑃𝑃 , 𝑉𝑉𝑖𝑖𝑃𝑃𝑃𝑃 〉}, {⋃𝑙𝑙 〈𝐾𝐾𝑙𝑙 , 𝑉𝑉𝑙𝑙

𝑄𝑄𝑄𝑄

𝐵𝐵𝐵𝐵𝐵𝐵
〉}, {⋃𝑚𝑚 〈𝐾𝐾𝑚𝑚
, 𝑉𝑉𝑚𝑚𝐵𝐵𝐵𝐵𝑀𝑀 〉}�

W2:= ��⋃𝑗𝑗 〈𝐾𝐾𝑗𝑗𝑆𝑆𝑆𝑆𝑆𝑆 , 𝑉𝑉𝑗𝑗𝑆𝑆𝑆𝑆𝑆𝑆 〉�, {⋃𝑛𝑛 〈𝐾𝐾𝑛𝑛𝐵𝐵𝐵𝐵𝐵𝐵 , 𝑉𝑉𝑛𝑛𝐵𝐵𝐵𝐵𝐵𝐵 〉}�
𝑄𝑄𝑄𝑄

Where W1 includes three key-value 〈𝐾𝐾, 𝑉𝑉〉 pairs, namely, 〈𝐾𝐾𝑖𝑖𝑃𝑃𝑃𝑃 , 𝑉𝑉𝑖𝑖𝑃𝑃𝑃𝑃 〉, 〈𝐾𝐾𝑙𝑙 , 𝑉𝑉𝑙𝑙

〈𝐾𝐾 𝐵𝐵𝐵𝐵𝐵𝐵

, 𝑉𝑉

𝐵𝐵𝐵𝐵𝐵𝐵 〉,

𝑄𝑄𝑄𝑄

〉 and

presenting the current knowledge states of the ith PM, lth QA and the mth
𝑄𝑄𝑄𝑄

changes of the BIM model, respectively. 𝐾𝐾𝑖𝑖𝑃𝑃𝑃𝑃 and 𝐾𝐾𝑙𝑙

denote the sequence number of SCM𝑄𝑄𝑄𝑄

MC processes and quality inspection procedures. 𝑉𝑉𝑖𝑖𝑃𝑃𝑃𝑃 and 𝑉𝑉𝑗𝑗
𝑄𝑄𝑄𝑄

indicate a set of knowledge

for 𝐾𝐾𝑖𝑖𝑃𝑃𝑃𝑃 and 𝐾𝐾𝑙𝑙 , including the results from optimization, simulation, prediction for PM and
QA. 𝐾𝐾 𝐵𝐵𝐵𝐵𝐵𝐵 represents the identifier of the changes of the BIM model, and 𝑉𝑉 𝐵𝐵𝐵𝐵𝐵𝐵 indicates the
properties of the changes of the BIM model, such as geometric and non-geometric
information. Similarly, W2 demonstrates the current data states of the jth SCO. 𝐾𝐾𝑗𝑗𝑆𝑆𝑆𝑆𝑆𝑆

indicates the identity of IoT-enabled construction resources and 𝑉𝑉𝑗𝑗𝑆𝑆𝑆𝑆𝑆𝑆 comprises the data

regarding the resources, such as status, location, vibration, altitude, etc. In summary, each
endorsed transaction causes the ledger to update the changing values of a key-value pair.

15

Figure 6. Ledger service model in BaaS.
(3) Smart Contract Services: Smart contracts define the executable logics between the five
dimensions of SCM in modular construction that generate new facts added to the ledger,
facilitating the optimal PM-QA of SCM. In BaaS, two chaincodes (smart contract packages),
namely S1 and S2, are deployed on C1 and C2, respectively.
S1 comprises seven main smart contracts to support intelligent PM-QA of SCM, including
value assessment contract (VAC), capacity assessment contract (CAC), availability
assessment contract (AAC), process optimization contract (POC), quality control contract
(QCC), BIM update contract (BUC), decision support contract (DSC). For a new order from
a stakeholder, VAC, CAC, and AAC can help assess the order’s business value, as well as the
capacity and availability of resources and processes, and determine whether approve this
order depending on the responses from the three smart contracts. Based on the approved
order, 𝐴𝐴𝐼𝐼𝐼𝐼𝐼𝐼 makes an initial plan as the transaction proposal to C1, where POC and QCC first
optimize and simulate the plan by invoking KMs and then offer the optimal plan. 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 can
use BUC to record the BIM model changes caused by the order and plan. When reaching a
consensus, the optimized PM-QA plan can be the input from BIM to C2 by executing DSC.

S2 includes four primary smart contracts to manage the data-oriented services across PS, DS,
and IS, namely, state validation contract (SVC), state computing contract (SCC), state
evaluation contract (SEC), and state update contract (SUC). Each 𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆 perceives the statuses
of construction resources and processes to understand current disturbance in PM and QA, and
these states can be published as transaction proposals to C2. For a new proposal, SVC, SCC,
and SEC can help check, compute, evaluate the data and then determine to approve the states
if all three smart contracts produce positive responses. In the PM and QA, SUC can update
the states to the 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 . 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 also subscribe to historical states and disturbances to learn the
current PM and QA's performance and optimize future performance with appropriate KMs.
16

3.2.3 Software as a Service (SaaS)
All the DApps, such as stakeholder communication application 𝐴𝐴𝑆𝑆𝑆𝑆 , the intelligent process
management and quality assurance application 𝐴𝐴𝐼𝐼𝐼𝐼𝐼𝐼 , BIM application 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 , SCOs

management application 𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆 can work as SaaS in BIBP by involving consensus. The
consensus is the convergence process of transactions through the BIBP network, where a
consensus mechanism used in 𝑂𝑂𝐼𝐼𝐼𝐼 and 𝑂𝑂𝑆𝑆𝑆𝑆 can be applied to guarantee that the relevant peer
nodes have agreed to a deal on the content and sequence of transactions. BIBP adopts
Hyperledger Fabric as the core blockchain infrastructure in BaaS, and such permissioned
blockchain works with a group of documented, defined, and frequently qualified peer nodes.
Thus, BIBP uses a basic Crash Fault-Tolerant (CFT) consensus mechanism to control the
transaction flow. As CFT in permissionless blockchain has no costly mining process such as
PoW, it can reach higher throughput performance and lower latency. According to CFT, 𝐴𝐴𝑆𝑆𝑆𝑆 ,
𝐴𝐴𝐼𝐼𝐼𝐼𝐼𝐼 , 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 , and 𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆 can be the representative services to achieve consensus transaction
flow.

As presented in Fig.7 (a), a stakeholder communication begins with a transaction T1 with the
proposal P, which includes the details and specifications of the order proposed by a user (e.g.,
client stakeholder) via 𝐴𝐴𝑆𝑆𝑆𝑆 . 𝐴𝐴𝑆𝑆𝑆𝑆 chooses an identity from a wallet to decide this user's role
and right to join C1 via the gateway. 𝐴𝐴𝑆𝑆𝑆𝑆 then passes P proposed by the user via the private
key to other peer nodes 𝑃𝑃𝑆𝑆𝑆𝑆 , 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 . 𝑃𝑃𝑆𝑆𝑆𝑆 assesses the business value of P by
implementing VAC in S1 and produces a response R1 with the endorsement E1 signed with
the private key of 𝑃𝑃𝑆𝑆𝑆𝑆 . 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 assess the status, capacity, and availability of process

and resources with BIM by executing KMs based smart contracts, such as CAC and AAC,
which produces R2 with E2 and R3 with E3. 𝐴𝐴𝑆𝑆𝑆𝑆 then obtains endorsed responses and
determines whether to proceed or end T1. When the endorsed responses reach a consensus,
T1 can be delivered to the ordering service. 𝑂𝑂𝐼𝐼𝐼𝐼 and 𝑂𝑂𝑆𝑆𝑆𝑆 pack these transactions into a new
block and broadcasts it to all peer nodes on C1. Once the peer nodes validate this new block,
it will be recorded on the L1 of all peer nodes on C1. The peer nodes will then notify the
connected DApp with the user that T1 has been processed. 𝐴𝐴𝐼𝐼𝐼𝐼𝐼𝐼 takes the notified and entire

order transaction from 𝐴𝐴𝑆𝑆𝑆𝑆 as the input to get the initial plans as transaction T2 with proposal
P, which is delivered to 𝑃𝑃𝑆𝑆𝑆𝑆 , 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 . 𝑃𝑃𝑆𝑆𝑆𝑆 , 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 optimize and simulate

the plan with various constraints, risks, and uncertainties by executing POC and QCC, and
generates R1 with E1, R2 with E2, and R3 with E3. 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 then record any BIM model change
caused by the order and plan as transaction T3 with proposal P, and also need confirmation
from 𝑃𝑃𝑆𝑆𝑆𝑆 , 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 . 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 can validate the change record and IFC objects
by executing BUC and produces R2 with E2 and R3 with E3. 𝑃𝑃𝑆𝑆𝑆𝑆 can reach a consensus to
confirm the results presented in BIM using DSC and generate R1 with E1.

Fig.7 (b) demonstrates a transaction flow for data and information-oriented PM-QA of SCM.
Once T2 is generated in C1, 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 may conduct cross-chain delivery to transform the
17

optimal plan into practical operations in C2 as transaction T1 with proposal P to guide the
operations of PM and QA in PS. 𝑃𝑃𝐶𝐶𝐶𝐶𝐶𝐶 and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 can visually present and analyze the
operation considering the current status of resources and processes by executing SCC and
SEC. During the PM-QA processes, each 𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆 publishes a real-time status as the transaction
T2 with proposal P, which is delivered to 𝑃𝑃𝐵𝐵𝐵𝐵 . 𝑃𝑃𝐵𝐵𝐵𝐵 help judge whether there is an abnormal
and complexity by implementing SVC and provides R1 with E2. If R1 presents an abnormal
and complexity, 𝑃𝑃𝐵𝐵𝐵𝐵 deliver this state to 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 for further KMs processing by using SUC and
generates R2 with E2. If R1 indicates a normal and simple condition, 𝑃𝑃𝐵𝐵𝐵𝐵 deliver this state to
𝑃𝑃𝐶𝐶𝐶𝐶𝐶𝐶 for processing by using SCC and generates R3 with E3. 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 subscribes all the
statuses from 𝑃𝑃𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 to assess the current states and improve the future performance by
executing SEC with learning and prediction capacity. Besides, 𝑂𝑂𝐼𝐼𝐼𝐼 and 𝑂𝑂𝑆𝑆𝑆𝑆 capture these
transactions and order them into a new block to update L2.

(a)

(b)
Figure 7 Service-oriented transaction flow on (a) C1; and (b) C2.
18

4 Implementation and Evaluation
4.1 Case Study
A modular construction project in Hong Kong is used to test the BIBP in its SCM. This
project is a student residence with two 17-floor towers comprising 1224 prefabricated hostel
rooms and other supporting facilities (e.g., prefabricated toilet, kitchen). The graphical details
of the project are shown in Fig. 8. Fig.9 demonstrates the processes of SCM in this project,
including the production, logistics, and installation. Apart from the consultancies of architect,
structure, and building service, the primary stakeholders in this project include HKU Estate
Office (owner), Paul Y. Engineering (general contractor), Yahgee Modular House
(manufacturer). All these stakeholders can access the BIBP through the peer nodes of 𝑃𝑃𝑆𝑆𝑆𝑆 . In
this case test, each peer node for each stakeholder is a docker deployed in the server. The
typical scenarios, e.g., intelligent process management and quality assurance, BIM status
updates, IoT sensing and tracking, are included. The following steps illustrate the transaction
logic in each application scenario: (1) The peer nodes handle transaction proposals from
DApps by implementing smart contracts and produce responses with endorsements. (2)
DApps receive certain transactions with responses and endorsements from peer nodes and
sign their validity. (3) Ordering service nodes package the valid transactions into new blocks
and distribute them to the related network's peer nodes. (4) The transactions in new blocks are
then validated by each peer node and are thereby added to the ledger and dedicated to the
network to notify DApps.

Figure 8. Overview of the MC project for this experiment: (a) project overview; (b) typical
floor layout; (c) five types of prefabricated module; and (d) BIM model of Module M1.
19

Figure 9. SCM process in BIBP for modular construction
In this case study, the passive RFID is used as the IoT plan to track the process status of SCM
in modular construction. The RFID tags are stuck to the modular units, and near-field
communication tags are embedded in the truck. The BIBP GN is a data converter in the
production factory, transportation vehicles, and construction site. All RFID events are
captured through 𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆 , computed via CUNs, validated and stored in the C2 of BIBP, which
can be broadcast among all the participants. The validated processes are demonstrated in
different colors through 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 , such as grayish-yellow (3D assembly & inspection), dark
green (arriving at the site), dark blue (hoisting). These status changes (e.g., format:
{‘ifcprocess’:{‘Material Check’→‘2D Panel Production’}}) in the BIM model can be finally
updated into the C1 of BIBP. KM for QA/QC in 𝐴𝐴𝐼𝐼𝐼𝐼𝐼𝐼 is used to inspect the components or
modules completed by the previous task, such as measuring the geometric differences
between the as-built and as-designed models. The truck is recognized and confirmed by
identifying the truck’s NFC tags.

4.2 Prototype System
The BIBP was built using Hyperledger Fabric (version 1.4), and the smart contracts in the
chaincodes were written using Javascript. The development environment was Ubuntu 18.04,
and docker with isolated containers consumes fewer hardware resources to ease system
prototype development than virtual machines. Using SpringBoot (version 2.4.0) and
AdminLTE (version. 3), we created backend and front-end prototypes for each peer node,
including frameworks, tools, and components (see Fig. 10). SpringBoot is a Java backend
20

framework for web server and MySQL development. AdminLTE is a front-end framework
based on Bootstrap that provides rapid development with responsive, reusable, and widely
used components.

Figure 10. Frameworks, tools, and components involved in this prototype development.
In the prototype, 𝑃𝑃𝑆𝑆𝑆𝑆 , 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 are connected to form the C1 in Hyperledger Fabric

for upper smart PM-QA in SCM. C2 includes 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 and other functional nodes (𝑃𝑃𝐵𝐵𝐵𝐵 and
𝑃𝑃𝐶𝐶𝐶𝐶𝐶𝐶 ) to facilitate accurate status tracking and operations of PM-QA in SCM. Other external
systems and DApps are also connected with the Hyperledger Fabric to facilitate the above
executions. Networks, channels, chaincodes, blocks, transactions, membership service
provider (MSP), and ordering service are all part of the BIBP.
Fig. 11 (a) presents the BIBP network details, which includes five-dimension organizations
(PS, DS, IS, KS, SS), two orders, and one cross-chain peer node (𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 ). Fig.11 (b) (c)
demonstrates the examples of the web front end of the C1 and C2, in which the Hyperledger
Fabric Cello graphical interfaces provide the comprehensive network composition,
organization information, peer nodes, and chaincodes (see Fig.11 (d)). Each block stored
transactions (20 transactions at most) that keep PM-QA events and links with other blocks
based on their hash values to compose L1 and L2. The block size is configured to 98 MB, and
CouchDB is applied for word state cache and retrieval. C1 includes six peer nodes and one
chaincode (S1), while C2 contains three peer nodes and one chaincode (S2) heretofore. Six
peer nodes in C1 correspond to the peer nodes in 𝑃𝑃𝑆𝑆𝑆𝑆 , 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 . There are four peer
nodes are involved in 𝑃𝑃𝑆𝑆𝑆𝑆 : (1) the owner, who is also the orderer in the 𝑂𝑂𝑆𝑆𝑆𝑆 ; (2) the
contractor; (3) the manufacturer; (4) the logistics agency. Each of 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 and 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 has one
peer node in C1, and each of 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 , 𝑃𝑃𝐵𝐵𝐵𝐵 , and 𝑃𝑃𝐶𝐶𝐶𝐶𝐶𝐶 has one peer node in C2.

Fig.12 presents the configuration information for these nodes, and cryptogen in Hyperledger
Fabric is used to ease the registration process by generating certificates such as admincert
(for each node's administrator), cacert (for the order), and tlscacert (for the transaction) (for
establishing connections). Each peer node has an administrator registered in either C1 or C2.
At the back end, MSP handles CAs with various dimensions of SCM and the wallets of
DApps, which ensures peer nodes can receive certificates and public-private keys as the
21

cryptographic identities. The administrator can also send requests to the sidechain's Fabric
CA for offering certificates and the public-private key to operators in the associated
organization, who are in charge of adding operation records to the sidechain. The ordering
service, consortium, and each peer node are all configured in the C1's genesis block. In each
peer node, an anchor peer 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 is created for cross-node communication in the C1 as well as
cross-chain interactions between the C1 and C2. By collecting transactions, bundling them
into a block, and distributing the block to peer nodes, the ordering service (configured in
Fig.10) makes it easier to achieve an agreement on the sequence of transactions.

(a)

(b)

(c)

(d)

Figure 11. BIBP prototype system: (a) BIBP network details; (b) C1 details; (c) C2 details;
and (d) chaincode details.

22

Figure 12. Order configuration
4.3 Performance Analysis
This section introduces the storage cost, throughput, and latency performance measures used
to assess the BIBP prototype in the experiment. There are two assumptions: (1) A total of 40
modular products (one typical floor) are produced, transported, and installed in 60 days; (2)
each modular product generates an average of 34 transactions (one order from 𝐴𝐴𝑆𝑆𝑆𝑆 , eleven
PM-QA operations in 𝐴𝐴𝐼𝐼𝐼𝐼𝐼𝐼 , eleven status updates in 𝐴𝐴𝐵𝐵𝐵𝐵𝐵𝐵 , eleven times data collection by
𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆 ,). Tblock = 2 hours/block (12 working hours per day) can be used as the block time,
which means a new block is created every half minute for recording SCM-MC transactions.
As a result, based on a preliminary calculation, each block contains an average of four
transactions.

4.3.1 Storage Cost
In the previous IoT-enabled BIM platform, the BIM model is stored in the webserver with the
size can be around 128.84 MB (e.g., BIM model in Fig.9). To make the BIM model the single
point of truth, we need to save the BIM model into the blockchain. However, it may lead to
redundancy in the blockchain network if the BIM model's full information is stored in the
blockchain network. In BIBP, any status change of the BIM is computed as the minimum
SDTs. One transaction’s average size can be reduced to 1 KB (Xue and Lu, 2020), and all of
the detailed information is kept in a local database. The total number of transactions in this
experiment is 1360 (40 × 34) and the maximum scenario in each ledger of the network for the
experiment only generates1360 KB (1360 × 1). For the present blockchain storage capacity, it
23

is a suitable size. Storage burdens may be freed from the BIBP system architecture, especially
useful for tracking vital information in big BIM files.
4.3.2 Throughput and Latency
Fig. 13 presents the throughput simulated and measured at peer nodes by transactions per
second, while the latency performance was tested by measuring the time of peer-to-peer
transactions. Both metrics are simulated by changing the block size. When the block size is
98 MB, the findings show that the Hyperledger Fabric can reach an acceptable throughput of
around 331 transactions per second (TPSs) with a latency of about 100 ms. The system's
latency is measured in milliseconds, as evidenced by the result. Each transaction may be
published minutes or hours apart in actual SCM procedures for modular construction. Some
material supply and production activities are also long processes that might take up to a day.
As a result, the prototype's latency may be acceptable. This analysis established that
permissioned blockchains, such as Hyperledger Fabric, are suitable for BIBP.Moreover, the
performance of Hyperledger Fabric in throughput and latency has also been validated in
other studies to indicate it outperforms Ethereum (Pongnumkul et al. 2017; Dabbagh et al.
2020).

Figure 13. Throughput and latency of the prototype system
4.3.3 Privacy and Security Analysis
According to Lu et al. (2021) and Li et al. (2021), the privacy and security analysis of the
proposed BIBP (particularly for the IoT network) can be explored via confidentiality,
integrity, non-repudiation, authentication, and authorization.
24

Confidentiality: thanks to its cross-chain design (e.g., two channels in Hyperledger Fabric)
and private data, this study can maintain confidentiality and private data. The former
facilitates IoT-related operations by creating channel #2, allowing transactions to be accessed
exclusively by peers (e.g., 𝑃𝑃𝐵𝐵𝐵𝐵 , 𝑃𝑃𝐶𝐶𝐶𝐶𝐶𝐶 , 𝑃𝑃𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 ) who engage in channel #2. The latter implies
that transactions are encrypted with a hash and kept in the private database of authorized
peers. As a result, the suggested method protects both privacy and confidentiality.
Integrity and non-repudiation: A transaction's integrity cannot be compromised while it is
being sent. All transactions in channels #1 and #2 are tamper-proof and include timestamps.
Furthermore, Transport Layer Security in Hyperledger Fabric allows transaction integrity
check across peer nodes to avoid “man in the middle” attacks and otherwise secure
connections.
Authentication: Authentication mechanisms rely on digital signatures, which necessitate the
possession of two cryptographically corresponding keys by each peer node: a public key that
is widely distributed and serves as an authentication anchor and a private key used to
generate digital signatures on transactions.
Authorization: MSP in Hyperledger Fabric is used in this study to prove the identity of
authorized peers. Smart contracts can only be activated by approved peers.
4.3.4 Feedback from Stakeholders
The primary stakeholders provide positive feedback on this prototype development. For
example, HKU Estate Office (owner) said, “ We now understand how the physical BIBP is
set up amongst the project stakeholders and know the virtual process of transaction flows in
the BIBP prototype”. Paul Y. Engineering (general contractor) praised, “It is a uniform and
open BIBP system suitable for different functions (e.g., inspections, progress monitoring,
authentic data selection, privacy preservation) with involving different stakeholders.” And
“We truly understand the immutability in BIBP through the chained blocks with hashed
transactions and stakeholders’ consensus.” Yahgee Modular House (manufacturer)
commented, “It is not easy to graphically visualize and monitor the data-informationknowledge transactions operation process, but we understand the rationality of how the IoT
data (via a hash table, dictionary-like data structure), inspection form (via URL), and BIM
information (via changes in IFC) stored and validated on the BIBP.” And “we learned that
decentralized applications, such as quality inspection apps, how to interact with BIM, IoT,
and blockchain system.”

5 Discussion
Three features of originality to the proposed BIBP system design are outlined below in
comparison to previous studies.

25

•

First, by combining blockchain, IoT, and BIM, BIBP can inherit the merits of
permissioned blockchain for SCM of modular construction in secure communication,
accountable operations, traceable data, transparent information, and reliable
knowledge when compared with existing IoT-enabled BIM platforms. BIBP can not
only minimize manual interruption to SCM processes via establishing ubiquitous IoT
among physical construction resources but also integrate BIM-based functional nodes
and knowledge model nodes to construct an SCM network in modular construction.

•

Secondly, in comparison to current blockchain systems in the construction industry,
this research offers open blockchain IoT-BIM as the Infrastructure, which is based on
an open BIM standard that is expanded from IFC. Therefore, the BIM in consensus
and BIM in the local cache are IFC compatible. The open BIM standard can help the
public body (e.g., government agency reluctant to mandating commercial software)
access and assess the BIMs developed on commercial platforms. New information
and functions are also easy to implement on an open BIBP.

•

Thirdly, DApps for stakeholder communication, intelligent PM-QA, BIM, and IoT are
designed with various smart contracts in SaaS. Moreover, the consensus-oriented
transaction flow has been proposed in BIBP to achieve on-chain, cross-chain, and offchain activities. The case study-based experiment has also indicated lower storage
cost and acceptable latency and throughput than the traditional IoT-enabled BIM
platform.

Despite these advancements, this study faces a few limits and problems in terms of practical
use.
•

Firstly, although the SDT can reduce the BIM model's redundancy, transactions in the
PM-QA process of SCM are more complicated since the data, information, and
knowledge, e.g., the analysis and solutions for constraints, risks, uncertainties, and
disturbances, are dynamic and massive. Including them in each transaction can also
lead to redundancy and low latency for the blockchain network. These complex
transactions also prevent knowledge-based real-time optimization and control tasks.
Thus, the extension of SDT to the knowledge models is needed.

•

Secondly, constraints, risks, uncertainties, and disturbances in the PM-QA processes
of SCM in modular construction are complex and dynamic, and current smart
contracts are almost deterministic. How to develop adaptive smart contracts to process
these data, information, and knowledge is still challenging. As the complex SCM
process of modular construction may require various knowledge models, they are not
be elaborated and tested in this study.

•

Thirdly, the BIBP currently stays at the one case study experiment. It should be
further developed and tested in more real off-site construction projects (e.g., modular,
prefabricated, or panelized construction) based on the well-explained business process
26

analysis, completed open BIM standard, comprehensive IoT protocols, robust
blockchain network with adaptive smart contracts, optimal block size, efficient
consensus mechanism, and other Dapps or externally connected systems (e.g., ERP,
GIS, CIM).

6 Conclusion
This study presents a service-oriented and decentralized system architecture of BIBP by
linking three-layer and five-dimension SCM to support knowledge and information-driven
smart SCM services and data-driven SCM operations in modular construction. BIBP
integrates blockchain with IoT-BIM for configuring DIK-driven SCM in modular
construction toward construction 4.0. BIBP was explained based on its DIK-oriented SCM
model, system architecture, IaaS (e.g., hardware, core technologies, and protocols), BaaS
(e.g., BIBP network service, smart contract service, ledger service), and SaaS (e.g., DApps
and transaction flow). Significant contributions are summarized threefold based on the
findings in this study. Firstly, a brand new BIBP system architecture for configuring SCM in
modular construction was developed by connecting blockchain with the IoT-BIM. BIBP
embraced significant merits in communicating information with security and transparency,
and conducting operations with traceability and smartness while reducing competitive storage
cost and achieving acceptable throughput and latency performance. Secondly, the
configuration of IaaS, BaaS, and SaaS offered insights into the future industrial
implementation of BIBP. Thirdly, the prototype system and its case study evaluation improve
the feasibility of BIBP for SCM in modular construction. The experiment results indicated
that the BIBP could carry out lower storage costs and reasonable throughput and latency.
Future studies can improve and upgrade the proposed BIBP. For example, the design of the
optimal consensus mechanism to achieve lower latency performance when increasing the
number of transactions and the size of blocks, and also the development of adaptive smart
contracts to more efficiently process complex data, information, and knowledge, such as
constraints, risks, uncertainties, and disturbances in SCM of modular construction, by
customizing the latest machine learning approaches.

Acknowledgments
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.

Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from
the corresponding author upon reasonable request.

27

List of Abbreviations
AAC
BaaS
BIBP
BIM
BNs
BUC
CAC
CC
CFT
CUNs
Dapps
DIK
DS
DSC
GNs
IaaS
IoT
IS
KM
KS
MC
MSP
NC
POC
PM
PS
QA
QCC
SaaS
SCC
SCM
SCOs
SDTs
SEC
SOA
SUC
SVC
SS
VAC
4M1E

Availability Assessment Contract
BIM as a Service
Blockchain-enabled IoT-BIM Platform
Building Information Modeling
Broker Nodes
BIM Update Contract
Capacity Assessment Contract
Channel Configuration
Crash Fault-Tolerant
Computing Unit Nodes
Decentralized Applications
Data-Information-Knowledge
Data Space
Decision Support Contract
Gateway Nodes
Infrastructure as a Service
Internet of Things
Information Space
Knowledge Model
Knowledge Space
Modular Construction
Membership Service Provider
Network Configuration
Process Optimization Contract
Process Management
Physical Space
Quality Assurance
Quality Control Contract
Software As A Service
State Computing Contract
Supply Chain Management
Smart Construction Objects
Semantic Differential Transactions
State Evaluation Contract
Service-Oriented Architecture
State Update Contract
State Validation Contract
Service Space
Value Assessment Contract
Man, Machine, Material, Method, Environment

References
Bankvall, L., Bygballe, L., Dubois, A., & Jahre, M. (2010). Interdependence in supply chains
and projects in construction. Supply Chain Management, 15(5), 385-393.
Barbosa, F., Woetzel, J., & Mischke, J. (2017). Reinventing Construction: A Route of Higher
Productivity. McKinsey Global Institute.
28

Beck, R., Stenum Czepluch, J., Lollike, N., & Malone, S. (2016). Blockchain–the gateway to
trust-free cryptographic transactions.
Buterin, V. (2014). A next-generation smart contract and decentralized application
platform. white paper, 3(37).
Cachin, C. (2016, July). Architecture of the hyperledger blockchain fabric. In Workshop on
distributed cryptocurrencies and consensus ledgers (Vol. 310, No. 4).
Cheng, J. C., Chen, W., Chen, K., & Wang, Q. (2020). Data-driven predictive maintenance
planning framework for MEP components based on BIM and IoT using machine
learning algorithms. Automation in Construction, 112, 103087.
Dabbagh, M., Kakavand, M., Tahir, M., & Amphawan, A. (2020, September). Performance
Analysis of Blockchain Platforms: Empirical Evaluation of Hyperledger Fabric and
Ethereum. In 2020 IEEE 2nd International Conference on Artificial Intelligence in
Engineering and Technology (IICAIET) (pp. 1-6). IEEE.
Dave, B., Buda, A., Nurminen, A., & Främling, K. (2018). A framework for integrating BIM
and IoT through open standards. Automation in Construction, 95, 35-45.
Deng, Y., Gan, V. J., Das, M., Cheng, J. C., & Anumba, C. (2019). Integrating 4D BIM and
GIS for construction supply chain management. Journal of Construction Engineering
and Management, 145(4), 04019016.
Gupta, S., Hellings, J., Rahnama, S., & Sadoghi, M. (2020). Building high throughput
permissioned blockchain fabrics: challenges and opportunities. Proceedings of the
VLDB Endowment, 13(12), 3441-3444.
Helliar, C. V., Crawford, L., Rocca, L., Teodori, C., & Veneziani, M. (2020). Permissionless
and permissioned blockchain diffusion. International Journal of Information
Management, 54, 102136.
Hijazi, A. A., Perera, S., Calheiros, R. N., & Alashwal, A. (2021). Rationale for the Integration
of BIM and Blockchain for the Construction Supply Chain Data Delivery: A Systematic
Literature Review and Validation through Focus Group. Journal of Construction
Engineering and Management, 147(10), 03121005.
Hsu, P. Y., Aurisicchio, M., & Angeloudis, P. (2019). Risk-averse supply chain for modular
construction projects. Automation in Construction, 106, 102898.
Hwang, B. G., Shan, M., & Looi, K. Y. (2018). Knowledge-based decision support system for
prefabricated prefinished volumetric construction. Automation in Construction, 94,
168-178.
Innella, Filomena, Mehrdad Arashpour, and Yu Bai. "Lean methodologies and techniques for
modular construction: Chronological and critical review." Journal of Construction
Engineering and Management 145.12 (2019): 04019076.
Kanan, R., Elhassan, O., & Bensalem, R. (2018). An IoT-based autonomous system for
workers' safety in construction sites with real-time alarming, monitoring, and
positioning strategies. Automation in Construction, 88, 73-86.

29

Lee, D., Lee, S. H., Masoud, N., Krishnan, M. S., & Li, V. C. (2021). Integrated digital twin
and blockchain framework to support accountable information sharing in construction
projects. Automation in construction, 127, 103688.
Li, C. Z., Xue, F., Li, X., Hong, J., & Shen, G. Q. (2018a). An Internet of Things-enabled BIM
platform for on-site assembly services in prefabricated construction. Automation in
construction, 89, 146-161.
Li, C. Z., Chen, Z., Xue, F., Kong, X. T., Xiao, B., Lai, X., & Zhao, Y. (2020a). A blockchainand IoT-based smart product-service system for the sustainability of prefabricated
housing construction. Journal of Cleaner Production, 286, 125391.
Li, S., Da Xu, L., & Zhao, S. (2018b). 5G Internet of Things: A survey. Journal of Industrial
Information Integration, 10, 1-9.
Li, X., Shen, G. Q., Wu, P., & Yue, T. (2019a). Integrating building information modeling and
prefabrication housing production. Automation in Construction, 100, 46-60.
Li, X., Wu, C., Wu, P., Xiang, L., Shen, G. Q., Vick, S., & Li, C. Z. (2019b). SWP-enabled
constraints modeling for on-site assembly process of prefabrication housing
production. Journal of Cleaner Production, 239, 117991.
Li, X., Chi, H. L., Wu, P., & Shen, G. Q. (2020). Smart work packaging-enabled constraintfree path re-planning for tower crane in prefabricated products assembly
process. Advanced Engineering Informatics, 43, 101008.
Li, X., Wu, L., Zhao, R., Lu, W., & Xue, F. (2021). Two-layer Adaptive Blockchain-based
Supervision model for off-site modular housing production. Computers in
Industry, 128, 103437.
Liu, G., Li, K., Zhao, D., & Mao, C. (2017). Business model innovation and its drivers in the
Chinese construction industry during the shift to modular prefabrication. Journal of
Management in Engineering, 33(3), 04016051.
Liu, H., Sydora, C., Altaf, M. S., Han, S., & Al-Hussein, M. (2019). Towards sustainable
construction: BIM-enabled design and planning of roof sheathing installation for
prefabricated buildings. Journal of Cleaner Production, 235, 1189-1201.
Lu, W.S., Li, X, Xue, F., Zhao, R., & Wu, L.P.F.(2021). Exploring Smart Construction Objects
as Blockchain Oracles in Construction Supply Chain Management, Automation in
Construction, 129,103816
Luo, L., Jin, X., Shen, G. Q., Wang, Y., Liang, X., Li, X., & Li, C. Z. (2020). Supply Chain
Management for Prefabricated Building Projects in Hong Kong. Journal of
Management in Engineering, 36(2), 05020001.
MacLeamy, P. A. T. R. I. C. K. (2004). Collaboration, integrated information and the project
lifecycle in building design, construction and operation. WP-1202, The Construction
Users Roundtable.
Mazairac, W., & Beetz, J. (2013). BIMQL–An open query language for building information
models. Advanced Engineering Informatics, 27(4), 444-456.

30

Marzouk, M., & Abdelaty, A. (2014). Monitoring thermal comfort in subways using building
information modeling. Energy and Buildings, 84, 252-257.
Mekki, K., Bajic, E., Chaxel, F., & Meyer, F. (2018, March). Overview of cellular LPWAN
technologies for IoT deployment: Sigfox, LoRaWAN, and NB-IoT. In 2018 IEEE
international conference on pervasive computing and communications workshops (pp.
197-202). IEEE.
Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z.
G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 125.
Mohamed, A. G., Abdallah, M. R., & Marzouk, M. (2020). BIM and semantic web-based
maintenance information for existing buildings. Automation in Construction, 116,
103209.
Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system.(2008).
NIBS,
N.
I.
(2015).
National
BIM
Standard-United
States:
https://www.nationalbimstandard.org/
Nguyen, G. T., & Kim, K. (2018). A Survey about Consensus Algorithms Used in
Blockchain. Journal of Information Processing Systems, 14(1).
Pongnumkul, S., Siripanpornchana, C., & Thajchayapong, S. (2017, July). Performance
analysis of private blockchain platforms in varying workloads. In 2017 26th
International Conference on Computer Communication and Networks (ICCCN) (pp. 16). IEEE.
Qian, X. A., & Papadonikolaki, E. (2020). Shifting trust in construction supply chains through
blockchain technology. Engineering, Construction and Architectural Management.
Ramaji, Issa J., and Ali M. Memari. (2016). Product architecture model for multistory modular
buildings. Journal of Construction Engineering and Management, 142 (10), 04016047.
Solihin, W., Eastman, C., Lee, Y. C., & Yang, D. H. (2017). A simplified relational database
schema for the transformation of BIM data into a query-efficient and spatially enabled
database. Automation in Construction, 84, 367-383.
Tang, S., Shelden, D. R., Eastman, C. M., Pishdad-Bozorgi, P., & Gao, X. (2019). A review of
building information modeling (BIM) and the internet of things (IoT) devices
integration: Present status and future trends. Automation in Construction, 101, 127-139.
Thai, H. T., Ngo, T., & Uy, B. (2020). A review on modular construction for high-rise buildings.
Structures, 28,1265-1290.
Wang, Z., Wang, T., Hu, H., Gong, J., Ren, X., & Xiao, Q. (2020). Blockchain-based
framework for improving supply chain traceability and information sharing in precast
construction. Automation in Construction, 111, 103063.
Xu, G., Li, M., Chen, C. H., & Wei, Y. (2018). Cloud asset-enabled integrated IoT platform
for lean prefabricated construction. Automation in Construction, 93, 123-134.

31

Xue, F., Chen, K., Lu, W., Niu, Y., & Huang, G. Q. (2018). Linking radio-frequency
identification to Building Information Modeling: Status quo, development trajectory
and guidelines for practitioners. Automation in Construction, 93, 241-251.
Xue, F., & Lu, W. (2020). A semantic differential transaction approach to minimizing
information redundancy for BIM and blockchain integration. Automation in
Construction, 118, 103270.
Yin, X., Liu, H., Chen, Y., & Al-Hussein, M. (2019). Building information modeling for offsite construction: Review and future directions. Automation in Construction, 101, 7291.
Zhai, Y., Chen, K., Zhou, J. X., Cao, J., Lyu, Z., Jin, X., ... & Huang, G. Q. (2019). An Internet
of Things-enabled BIM platform for modular integrated construction: A case study in
Hong Kong. Advanced Engineering Informatics, 42, 100997.
Zhang, C., Zhou, G., Li, H., & Cao, Y. (2020). Manufacturing blockchain of things for the
configuration of a data-and knowledge-driven digital twin manufacturing cell. IEEE
Internet of Things Journal, 7(12), 11884-11894.
Zhang, Z., Yuan, Z., Ni, G., Lin, H., & Lu, Y. (2020 b). The quality traceability system for
prefabricated buildings using blockchain: An integrated framework. Frontiers of
Engineering Management, 7(4), 528-546.
Zheng, R., Jiang, J., Hao, X., Ren, W., Xiong, F., & Ren, Y. (2019). bcBIM: A blockchainbased big data model for BIM modification audit and provenance in mobile
cloud. Mathematical Problems in Engineering, 2019.
Zheng, Z., Xie, S., Dai, H., Chen, X., & Wang, H. (2017, June). An overview of blockchain
technology: Architecture, consensus, and future trends. In 2017 IEEE International
Congress on Big Data (BigData congress) (pp. 557-564). IEEE.
Zhong, R. Y., Peng, Y., Xue, F., Fang, J., Zou, W., Luo, H., ... & Huang, G. Q. (2017).
Prefabricated construction enabled by the Internet-of-Things. Automation in
Construction, 76, 59-70.
Zins, C. (2007). Conceptual approaches for defining data, information, and knowledge. Journal
of the American Society for Information Science and Technology, 58(4), 479-493.

32