Exploring Smart Construction Objects as Blockchain Oracles in Construction Supply Chain Management
Weisheng Lu, Xiao Li, Fan Xue, Rui Zhao, Liupengfei Wu, and Anthony G.O. Yeh
The University of Hong Kong, Hong Kong SAR, China
This is the peer-reviewed post-print version of the paper:
Lu, W., Li, X., Xue, F., Zhao, R., Wu, L., & Yeh, A.G.O. (2021). Exploring smart
construction objects as blockchain oracles in construction supply chain management.
Automation in Construction, 129, 103816. Doi: 10.1016/j.autcon.2021.103816
The final version of this paper is available at: https://doi.org/10.1016/j.autcon.2021.103816.
The use of this file must follow the Creative Commons Attribution Non-Commercial No
Derivatives License, as required by Elsevier’s policy.
Highlights
• An SCO-enabled blockchain oracle (SCO-BO) framework is proposed.
• The architecture of a blockchain-enabled construction supply chain management
system (BCSCM) is established.
• Four smart contracts are examined in logistics and on-site assembly services.
• A decentralized SCO network avoids the single point of failure (SPoF).
• Ubiquitous SCOs as blockchain oracles bridge the on-chain and off-chain worlds.
Abstract
Blockchain technology has attracted the interest of the global construction industry for its
potential to enhance the transparency, traceability, and immutability of construction data and
enables collaboration and trust throughout the supply chain. However, such potential cannot
be achieved without blockchain “oracles” needed to bridge the on-chain (i.e., blockchain
system) and off-chain (i.e., real-life physical project) worlds. This study presents an innovative
solution that exploits smart construction objects (SCOs). It develops a SCOs-enabled
blockchain oracles (SCOs-BOs) framework. To instantiate this framework, the system
architecture of a blockchain-enabled construction supply chain management (BCSCM) system
is developed and validated using a case study, whereby four primary smart contracts are
examined in the context of off-site logistics and on-site assembly services. The validation
results show that accurate data is retrieved against malicious data in each request, and the
corresponding reputation scores are successfully recorded. The innovativeness of the research
lies in two aspects. In addition to mobilizing SCOs as blockchain oracles to bridge the on-chain
and off-chain worlds, it develops a decentralized SCO network to avoid the single point of
failure (SPoF) problem widely existing in blockchain systems. This study contributes to
existing research and practice to harness the power of blockchain in construction.
Keywords
Blockchain; Oracles; Smart Contract; Supply Chain Management; Smart Construction Objects;
Prefabricated Construction
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1. Introduction
The construction industry is one of the most fragmented sectors globally due to a high degree
of specialization amongst its professions, businesses and processes, and most construction
projects are one-offs involving adversarial relationships (Turk and Klinc, 2017). As a result,
construction projects worldwide have a scattered and complex supply chain (Dainty et al.,
2001). For example, the construction of a two-tower student hostel at the University of Hong
Kong involved more than 20 suppliers throughout China, the transportation of prefabricated
modules over 1500 miles from Jiangsu and, at its peak, over 200 workers on the supply chain
(Zhang et al., 2021). Collaboration is needed to manage such a fragmented supply chain, and
accountability is needed to ensure the sharing of trustworthy data on progress, quality, safety,
costs, payments, and resources (Tezel et al., 2020). A lack of accountability gives rise to
disputes, deflection of blame, and corner-cutting, which in turn lead to depressed productivity,
cost overrun, and accidents (Zhong et al., 2020). Blockchain technology can offer this missing
accountability in construction and make supply chains traceable, transparent, and immutable
for all project participants (Wan et al., 2020).
Blockchain is a decentralized trust infrastructure that combines distributed ledgers,
cryptography, and consensus protocols. It can track and store the past and present status of
tangible assets or intangible events across a decentralized peer-to-peer network. Data is saved
in a set of blocks linked in a consecutive chain. Cryptographic protocols prevent any change in
the data stored in a block without the collusion or collaboration of the majority of participants
(Kosba et al., 2016). Smart contracts can run on a blockchain, implement consensus protocols,
and allow participants to reach a consensus-based on predefined rules without a trusted third
party (Li et al., 2019a) (Yang et al., 2020). Several applications for blockchain-enabled smart
contracts have been explored in different domains, including document control (Hasan and
Salah, 2018a), delivery assurance (Hasan and Salah, 2018b), Internet of Things (IoT) access
control and authentication (Salah et al. 2019; Almadhoun et al. 2018). In the construction
industry, applications have been explored in payment security (Chong and Diamantopoulos,
2020), quality management (Sheng et al., 2020), traceability of prefabricated components
(Wang et al., 2020), Building Information Modeling (BIM) data audit (Zheng et al., 2019; Xue
and Lu, 2020), and integrated project delivery (IPD) transactions (Elghaish et al., 2020).
However, the execution of smart contracts in the construction supply chain often requires an
exchange of real-world data, which cannot be accomplished by blockchain (Wang et al., 2017).
Oracles are middleware agents that can capture and validate real-world information and feed it
to a blockchain for the use of smart contracts (Al-Breiki et al., 2020). They may be software or
hardware, inbound or outbound, or consensus-based. While humans can serve as oracles to
trigger communication between the on-chain and off-chain worlds, this is interruptive, timeconsuming, and error-prone. The use of software oracles, such as BIM manipulated by human
operators, is possible but ensuring the authenticity of external data sources is challenging.

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Software oracles also bring back the blockchain centralization problem since relying on
centralized sources increases the risk of feeding erroneous data to the blockchain system. There
is a need for oracles with autonomous and decentralized computational power scattered in key
construction processes or nodes to verify construction data correctness and accuracy before it
is fed into a smart contract, and to ensure data privacy.
Smart embedded technologies have excellent potential as blockchain oracles. Specifically,
according to a concept developed by Niu et al. (2016), construction resources (e.g., machinery,
tools, devices, materials, components, and structures) can be turned into smart construction
objects (SCOs) able to convey their designated properties and with new properties of awareness,
communicativeness, and autonomy to enable various smart applications. Thus, opportunities
exist to mobilize SCOs into hardware oracles to bridge the communication between blockchain
and real-life construction processes. However, this research area is uncharted territory.
This study, therefore, aims to investigate the extended use of SCOs as trustworthy hardware
oracles for blockchain applications in the construction industry. It has three specific objectives:
(1) to establish a deployment framework for exploring SCOs as decentralized blockchain
oracles; (2) to instantiate the framework by proposing a system architecture of SCOs-as-oracle
blockchain-enabled construction supply chain management (BCSCM); and (3) to validate the
framework and system architecture in a case study. The study makes three main contributions
to the body of knowledge. First, it is one of the first investigations on decentralized blockchain
oracles in the construction industry to improve the single point of failure (SPoF). Second, to
achieve data selection and validation through on- and off-chain interactions, the study presents
the oracles smart contract (OSC) with an unbiased random sortation mechanism and the
aggregator smart contract (ASC) with cross-reference mechanisms. Third, to realize the crosschain activities between the main (service blockchain) and side chain, it develops the reputation
smart contract (RSC) with the reputation system and service smart contract (SSC). The rest of
the paper is organized as follows. After this introductory section is Section 2, which elaborates
on some basics of blockchain and its oracles. Section 3 delineates the SCOs-enabled blockchain
oracles (SCOs-BOs) framework, and Section 4 describes the system architecture of the
BCSCM system. Section 5 is a case study that uses logistics and on-site assembly traceability
services to validate the smart contracts used in the BCSCM system. Our findings are discussed
in Section 6, and conclusions are drawn in Section 7.
2. Background
2.1 Construction Supply Chain Management
Construction supply chain management (CSCM) aims to ensure the smooth flow of goods and
services to the construction site through cooperation between supply chain participants (Dainty
et al., 2001). CSCM is massively challenging in practice due to long-standing issues, including
lack of trust, fragmentation, and discontinuity (Luo et al., 2020). Product provenance issues

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and disputed inspection of products contribute to the lack of trust (Bankvall et al., 2010), while
fragmentation issues result from a geographical distribution of stakeholders and multiple
CSCM stages (Hsu et al., 2019). Discontinuity arises because the current CSCM system lacks
good-quality data for coordinated functional modules such as compliance check, process
control, and quality assurance, and can also be ascribed to low levels of information visibility
and traceability. For example, product data is still mainly conveyed from the prefabrication
factory to the construction site on paper (Zhai et al., 2019). Such manual processes are timeconsuming and may lead to input errors, file loss, and data tampering. Integrating IoT and BIM
to connect physical construction objects with virtual BIM objects has been proved to alleviate
the fragmentation and discontinuity of CSCM (Li et al., 2019b). Researchers and practitioners
have proposed many technologies to realize IoT, such as radio-frequency identification (RFID),
near-field communication (NFC) for short-range wireless (Xue et al., 2018), 5G for mediumrange wireless (Li et al., 2018b), and low-power wide-area networking (e.g., LoraWan, NBIoT) for long-range wireless (Mekki et al., 2018). In construction, Niu et al. (2016) proposed a
robust IoT model in the form of smart construction objects (SCOs). The integration of SCOs
with BIM has been recognized as a compelling paradigm for digital twin applications to
enhance construction efficiencies. These applications have been widely explored in
construction resource and progress monitoring (Li et al., 2018a; Zhong et al., 2017),
occupational health and safety management (Niu et al., 2019), and construction logistics and
supply chain management (Niu et al., 2017). However, merely integrating BIM and SCOs is
not enough to achieve data privacy, security and trust among stakeholders. For example, the
shared cloud BIM model and its data can be tampered with, leaving data changes untraceable,
and SCO sensors (e.g., RFID, GPS) may suddenly run out of power or report noise that reduces
data quality.

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2.2 Blockchain and Smart Contracts
A potential solution to the above issues is blockchain, a distributed ledger of pertinent data and
transactions mutually agreed upon and shared among all participants in a peer-to-peer network
(Nakamoto, 2008). Three components support the functioning of blockchain: cryptography, a
distributed database, and a consensus mechanism (Zheng et al., 2017). Cryptography, in the
form of hashing algorithms, is used to encrypt transactional data based on the agreed protocol,
making the data difficult to tamper with (Beck et al., 2016). A widespread network of
computers supports distributed ledgers, recording all data in each participant’s ledger.
According to the consensus, data transactions are kept synchronized across the network
(Nguyen and Kim, 2018). Current blockchain platforms include permissionless blockchain and
permissioned blockchain (Helliar et al., 2020). A permissionless blockchain, such as Bitcoin
or Ethereum, is entirely decentralized and allows any participant to access the data in blocks
(Buterin, 2014). In permissioned blockchain, such as Hyperledger Fabric, only identified users
can validate transactions and access block data (Cachin, 2016). Permissionless blockchain

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highlights openness and decentralization, while permissioned blockchain can provide higher
throughputs by designing deterministic consensus protocols (Gupta et al., 2020). Therefore,
permissioned blockchains are more applicable for time-sensitive CSCM applications in terms
of transparency, traceability, immutability, decentralization, privacy, and smartness (Qian and
Papadonikolaki, 2020).

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The first application of blockchain, or “Blockchain 1.0”, was in cryptocurrencies, while the
technology has expanded into other sectors through smart contracts, the primary advancement
of “Blockchain 2.0” (Buterin, 2014). Smart contracts are self-executing contracts that run on
an “if-then” basis (Hasan and Salah, 2018a). They can track on-chain or cross-chain data
changes and off-chain data sources in real-time and automatically respond under preset trigger
conditions (Uriarte et al., 2020). Smart contracts can be either deterministic or nondeterministic (Kosba et al., 2016). The former, such as tokenization of assets, can be
independently executed in the blockchain without interaction with the external world. Nondeterministic smart contracts, as in the case of construction industry applications, require offchain data to trigger execution. For example, the location data of a prefabricated product can
be captured from its mounted GPS sensors. When the product arrives at the construction site,
the smart contract can extract the off-chain location data as proof of location to activate the
blockchain’s product status change. To facilitate this data exchange between the on-chain and
off-chain worlds, blockchain oracles can serve as intermediaries. Without blockchain oracles,
smart contracts have to trust only data already within the chain, and the functions of blockchain
would be seriously constrained.
2.3 Blockchain Oracles
In ancient Greece, an oracle was a messenger passing advice or prophecies from gods to
mortals. In modern society, any accurate source of information can be considered an oracle
(Al-Breiki et al., 2020). In blockchains, an oracle is a middleware agent that queries, verifies,
and authenticates external data sources and then delivers them to the blockchain for subsequent
use by smart contracts (Kochovski et al., 2019). The data transmitted by oracles in CSCM
processes include workers’ health and safety information, operation and energy information
from machinery, location and quality data from material and components, cost and progress
status, and building information contained in BIM models. Oracles can also be classified
according to the source of data (software, hardware, human), information flow direction
(inbound, outbound), design pattern (request-response, publish-subscribe, immediate–read),
and trust model (centralized, decentralized) (Beniiche, 2020).

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Oracles are not a built-in functionality of blockchain and do not have consensus mechanisms.
If oracles are compromised, smart contracts will also be compromised. Thus, centralized
oracles with a single data source may suffer single point of failure (SPoF) problems. Previous
studies have explored the use of oracles to improve data quality and authenticity in CSCM.
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Shrestha and Behzadan (2018) developed an evolutionary algorithm to refine sensor data noise
and enhance data quality for better construction planning simulation, while Bangaru et al.
(2020) found that multiple sensors or combined sensors can achieve higher accuracy in activity
classification than individual sensors. Addressing data authenticity, Chong and
Diamantopoulos (2020) used smart sensors as hardware oracles and integrated them with smart
contracts to improve payment security. Zheng et al. (2019) considered BIM as software oracles
for blockchain to store historical processes of file modification. Involving human oracles,
Wang et al. (2020) used smart contracts in blockchain to update precast components status and
operation information, and Sheng et al. (2020) explored smart contracts for handling
construction quality information such as inspection forms. However, the quality and
authenticity of off-chain data before input to the blockchain have not yet been investigated,
and some CSCM process data are noisy or miscellaneous in nature.
Several studies have investigated blockchain oracles in other industries to achieve proof of
location. For example, Vivekanandan et al. (2021) proposed an IoT device-to-device
authentication protocol for smart city applications, facilitating the registration of IoT location
data in the blockchain. Victor and Zickau (2018) stored location encoding systems in the smart
contract to represent a geofence used to evaluate the location data provided by the oracle.
Boeira et al. (2019) developed a scheme using cryptographic primitives and mobility awareness
to improve the trustworthiness of shared vehicle location information in high-speed scenarios.
Zafar et al. (2020) also summarized a state-of-the-art location proof system and highlighted
current challenges such as collusion resistance (malicious location and noise) and storage
(redundancy in blockchain but untrustworthy in distributed devices). Some off-the-shelf
decentralized blockchain oracle solutions for commercial applications have been summarized
in Al-Breiki et al. (2020), such as Witnet (De Pedro et al., 2017), Augur (Peterson et al., 2015),
Chainlink (Ellis et al., 2017), ASTRAEA (Adler et al., 2018), and Aeternity (Hess et al., 2018)
taking the reputation system, voting game, or consensus mechanism into account.
The research gaps identified can be summarized as follows: (1) there is a lack of a framework
to guide the establishment of a decentralized hardware oracle sidechain for specific CSCM
functions and to help card the logic of cross-chain (off-chain, sidechain, main chain)
interactions; (2) the automatic consensus mechanism (e.g., cross reference), reputation system,
and unbiased random sortation mechanism have not been investigated for hardware oracles in
CSCM to avoid SPoF and help get trustworthy data in an empirical study.
3. A Framework for Using Smart Construction Objects as Blockchain Oracles
3.1 Transferring SCOs as Oracles: Definition & Properties
Smart construction objects (SCOs), proposed by Niu et al. (2016), represent a robust IoT model
with sensing, processing, and communicating capacities to facilitate information exchange
among various construction resources. Here, construction resources could be men, machines,
or materials. The core properties of SCOs are awareness, communicativeness, and autonomy

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(Niu et al., 2017). Awareness shows the ability of SCOs to sense and record their real-time
situation and that of the vicinity. Communicativeness indicates the power of SCOs to exchange
information they have obtained through their awareness. Autonomy refers to the ability of
SCOs to alert people of the need for actions or take actions autonomously based on predefined
rules. These properties of SCOs are well-matched with the design patterns of blockchain
oracles (see Table 1). For example, the activity aware with passive autonomy and pull
communicativeness property is similar to the request-response pattern, where oracles can
monitor, retrieve, and record data when the specific activity or event requests are triggered.
The policy-aware with active autonomy and push communicativeness property is identical to
the publish-subscribe pattern, where oracles can broadcast real-time conditions when the
changes comply with rules and regulations. The process-aware with mixed autonomy and
mixed communicativeness property works the same as the immediate-read pattern, where
oracles can store data available for any immediate need in any construction process.
Table 1. The core and sub-properties of SCOs
Description

Oracles
Patterns

Activity aware

To be aware of and respond when an activity or event is triggered

request-response

Policy aware

To be aware of situations compliant with published rules and regulations

publish-subscribe

Process aware

To be immediately aware of activities in workflows and processes

immediate-read

Properties

Design

Awareness

Communicativeness
Pull

To offer information on request

request-response

Push

To proactively issue updated information or alerts at regular intervals

publish-subscribe

Mixed

To immediately offer and issue information

immediate-read

Passive

To assist in making decisions and taking action upon request

request-response

Active

To proactively take action based on changes at regular intervals

publish-subscribe

Mixed

To execute autonomy in both passive and active manners

immediate-read

Autonomy

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SCOs can work in a similar way to oracles in construction blockchain. They can act as data
feed providers to sense and capture data from various construction resources and scenarios and
serve as oracle node operators to process and transfer accurate, reliable, and verified data to
blockchain systems. In addition, IoT sensors installed on SCOs can serve other relevant
purposes. For example, inertial measurement units (IMU) and air pressure units can supplement
GPS locations with accurate motion and height data, while passive RFID and QR codes can be
attached to construction objects for lifelong facility management. For different construction
tasks, a combination of different SCOs design profiles can offer the optimal performance-price
ratio. Figure 1 shows a detailed SCO plan for construction processes with two types of models:
Model 1: Low-energy, single GPS sensor for location-based service in off-site logistics
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Model 2: High-frequency multiple motions and environmental sensors for off-site
production and on-site assembly

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Figure 1. An SCO plan for CSCM processes: Off-site production, logistics, and on-site
assembly services
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3.2 The SCOs-BOs Framework
This section proposes an SCOs as blockchain oracles (SCOs-BOs) framework providing a
decentralized oracle solution with multiple smart contracts to manage interactions and data
access. It can help randomly select and monitor the oracles for specific services in CSCM
processes and offer reputation scores to each oracle by cross-reference. The framework tries to
improve two bottlenecks in the data exchange between the physical CSCM processes and the
cyber blockchain worlds: (1) single point of failure (SPoF), which means only relying on one
source of information from the centralized BIM platform; and (2) the need for trustworthy,
good-quality data.

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The framework is shown in Figure 2 with the components described below.
Oracles pool: Stakeholders can provide and register new SCOs in the oracles pool. The
SCOs for specific services in the oracles pool are randomly selected and registered in
the oracle smart contract (OSC) to form a decentralized oracle network.
• Oracles sidechain: Since oracles are not as reliable as blockchain, the sidechain is a
substitution that also packages the oracles network as a side blockchain that
communicates to the main blockchain (Singh et al., 2020) (Uriarte et al., 2020) (Li et
al., 2021a). The sidechain includes the OSC and the aggregator smart contract (ASC).
The former provides a frequently used interface to select SCOs from the oracles pool

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by using an unbiased sortation algorithm for specific construction management services
(Zhou et al., 2019), and these selected SCOs can be registered in the OSC. This
registration process is verified by all stakeholders. Their data is also hashed and
returned to the ASC. The ASC receives all data hashes from the OSC, cross-references
their hash values, and broadcasts reputation scores for each involved SCO to the
reputation smart contract (RSC).
• Service blockchain: This includes a service smart contract (SSC) and an RSC. The SSC
receives ASC reputation scores to compute and record the average reputation scores for
all SCOs in the oracles sidechain and then selects the winning SCO. Also, the updated
reputation scores are returned to the SCOs in the OSC. The SSC is triggered and can
call upon the ASC’s selection interface when the specific need arises (e.g., the logistics
service is used to monitor prefabricated products’ location status).

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• Stakeholder consensus: Stakeholders in the CSCM processes can request data from the
SSCs. All SSCs and registered SCOs in the OSC should reach a consensus from all
stakeholders before execution in the services blockchain and oracles sidechain.

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Figure 2. The SCOs-Bos framework
Interactions between components in the framework are summarized in the sequence diagram
in Figure 3. These interactions can occur on-chain, cross-chain, or off-chain. Stakeholders are
responsible for deploying SCOs and reach a consensus when the SSC is ready and selected
SCOs are registered. For example, all the stakeholders can make a service consensus on the
SSC in the logistics stage to monitor prefabricated products’ real-time position status. The
logistics manager should arrange for embedding GPS sensors (e.g., Model 1) into the
prefabricated products, tractors, trailers, and drivers in the transportation process. Furthermore,
these SCOs can be registered into the OSC, where they will be agreed upon by all stakeholders.
Stakeholders can send data requests to the SSC, and the SSC conducts permission verification.
If the stakeholder has valid access permission, the request proceeds as follows:
• SSC forwards stakeholder request to ASC
•

ASC invokes the interface of OSC, and OSC randomly selects from the off-chain
oracles pool

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•

All selected SCOs can be registered into the OSC to form a decentralized sidechain,
and each registered SCO hashes its data and sends it back to ASC

•

ASC introduces a cross-reference method on all received data hashes from SCOs, gets
the most similarity on returned hashes, and reports each SCO’s reputation score to RSC
RSC updates reputation scores for all SCOs in the oracles sidechain and selects a
winner SCO based on the highest reputation score for SSC

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SSC delivers the data in the winner SCO to the stakeholders

Figure 3. Sequence diagram for the proposed framework
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4. System Architecture
This section instantiates the SCOs-BOs framework by developing and enriching a blockchainenabled construction supply chain management (BCSCM) system. The supporting
stakeholders and main services are explained below.
4.1 Overview
Figure 4 shows the architecture of the BCSCM system, which comprises four main layers: (1)
smart construction objects (SCOs), (2) oracles sidechain network, (3) service blockchain
network, and (4) services.

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Figure 4. BCSCM system architecture
SCOs serve as the foundation of this architecture. SCOs are the construction resources in the
BCSCM system and can be equipped with smart IoT devices (Zhong et al., 2020). For example,
site workers’ data, including heartbeat, heat stress, location, and motion, can be monitored and
tracked using wearable devices such as smart wristbands, vests, and helmets. These collected
construction data can be retrieved and broadcast through the SCO layer communication
channels, such as ZigBee, Bluetooth, WiFi, Ultra-wideband, 5G, and Transmission Control
Protocol/Internet Protocol (TCP/IP). The procedures of data cleaning and transformation,
aggregation and classification, standardization, and pattern recognition are also processed in
each SCO. This layer mainly has capacities in awareness, autonomy, and communicativeness
of multimode data from different IoT sensors.
In the oracles sidechain network layer, an unbiased sortation algorithm is used to randomly
select the SCOs for a specific service (e.g., production quality assurance), and these selected
SCOs can be registered and used to form a set of blocks. Each block in the oracles sidechain

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comprises a header and the selected SCOs’ data. A cross-reference method is applied in this
layer to find out the authentic data and report their reputation scores (e.g., 0 or 100) based on
similarity to the authentic data.
In the service blockchain network layer, a reputation system is adopted to elect the SCO with
the highest reputation scores as the winner and updates the reputation scores of other SCOs in
the oracles sidechain network layer. The data from the winner SCO are used to establish a set
of blocks. Each block in this network comprises a header and winner SCOs’ data, such as the
location of prefabricated products, physiological signals of workers, and operation status of the
tower crane. In the service blockchain network establishment process, a consensus mechanism
named Practical Byzantine Fault Tolerance (PBFT) is used to ensure collective decisionmaking and reduce the faulty nodes’ influence. An incentive mechanism is also devised to
reward stakeholders who deploy SCOs in the construction processes.
Numerous service-oriented applications for the BCSCM system are deployed in the service
layer, such as production quality control transparency, logistics and on-site assembly
traceability, and workers’ health and safety privacy. These services are supported by the service
main blockchain and oracles sidechain using the data from SCOs.
4.2 Supporting Stakeholders
In this BCSCM system, strategic-level, tactical-level, and operational-level stakeholders can
support and facilitate implementation of related layers.
Frontline workers and operators are representative stakeholders at the operational level. All the
SCOs’ fresh data for the BCSCM system comes from operational tasks. For example,
supported by deep cameras and laser scanners in the production plant, prefabricated products’
dimensions and smoothness can be detected and recorded. These point cloud data can be further
used for assembling the prefabricated products onsite. Operational-level stakeholders should
verify authenticity of data in the selected and registered SCOs. For example, truck drivers
should verify whether location signals of on-transport prefabricated products are consistent.
Department managers and construction engineers are representative stakeholders at the tactical
level, aiming to ensure data-exchange reliability between oracles and blockchain by designing
specific smart contracts with various algorithms and models. For example, the reputation
mechanism and cross-reference method are designed by tactical stakeholders. These data can
be further used for service blockchain when all tactical and operational stakeholders agree and
verify the data from SCOs-BOs.
Project owners and senior managers such as plant managers, logistics managers, and site
managers are the strategic-level representative stakeholders. They are accountable for forming
the service blockchain, including the provision of SCOs, and the design of incentive and

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consensus mechanisms. They are also the decision-makers of the construction supply chain for
specific strategies using the information from the service blockchain network.
4.3 Critical Services
To instantiate the SCOs-BOs framework, three construction management services may be
achieved through the proposed system architecture, as follows.
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Production quality control transparency means that quality inspection information for
each prefabricated product production process is readily available to stakeholders. This
service can facilitate remote stakeholders (e.g., contractors and project owners in Hong
Kong) access detailed quality information from an off-site manufacturing plant (e.g.,
Jiangsu province). Deep cameras and laser scanners can work as SCOs-BOs to compute
and retrieve quality inspection information for formworks (e.g., smoothness, cleanliness,
and dimensions), steel reinforcing bars (e.g., size, pattern, fixing and layout, spacers, and
concrete covers), concrete (e.g., placing and compaction), and finished products (e.g.,
surface, size, and dimensions, anchor bar). These data recorded in blockchain can
improve production process inspection accountability.
Logistics and on-site assembly traceability enable stakeholders to track construction
resources and events’ latest and historical status. For example, this service can assist site
managers in monitoring the real-time location status and assembly progress of
prefabricated products (Li et al., 2020). The low-energy, single GPS sensor for a locationbased logistics service can be mounted in each prefabricated product. These location data
can be cross-referenced as proof of location and the one with the highest reputation scores
recorded in the blockchain for further decision-making.
Workers’ health and safety privacy relate to data including images or sensor signals of
fatigue, unsafe motions, heartbeat, heat stress, and locations, which can be captured and
processed by the SCOs-BOs. Furthermore, Federated learning is used for decentralized
SCOs-BOs (Yang et al., 2019) (Li et al., 2021b), where a model can be trained by using
the local health and safety data samples in each SCO-BO without extracting them.
Instead, only the high-level insights from the data are retrieved and stored in the
blockchain.

5. Case Study
A case study using cross-border logistics and supply chain management, focusing on the
services of off-site logistics and on-site assembly traceability, is conducted to verify the SCOsBOs framework and the system architecture of the BCSCM system. According to Wan et al.
(2020), blockchain can offer clear accountability and make the construction supply chain more
traceable, transparent, and immutable among all participants involved in a project. In this case,
low-energy, single GPS sensors mounted in prefabricated beams as SCOs were transported
from mainland China to Hong Kong for a prefabricated construction project comprising five
high-rise public housing residential towers surrounding one commercial center. To validate the
proposed SCOs-BOs framework and system architecture, we implement four primary smart
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contracts (SSC, RSC, ASC, OSC) using the GPS data of prefabricated beams for the
commercial center. Although this project is complete (nine highlighted beams have been
erected as shown in Figure 5), the full record of GPS data (shown in the green data list of Figure
6) for the nine beams (C1023–C1031) in the same batch can be put into the oracles pool for
validation.

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Figure 5. Service for off-site logistics and on-site assembly
5.1 Implementation

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The proposed SCOs-Bos framework was implemented on Hyperledger Fabric (version 2.2),
and Javascript was used to write the smart contracts in the chaincode. The development
environment was in Ubuntu 18.04, and docker with isolated containers is used to facilitate
system prototype development, which uses fewer resources than virtual machines. In the
prototype, four stakeholders are involved in the service blockchain: (1) the owner, who serves
as the orderer in the ordering service; (2) the contractor; (3) the manufacturer; and (4) the
supplier. Figure 6 (a) presents the configuration information for these stakeholders, and
cryptogen in Hyperledger Fabric is used to facilitate the registration process by issuing the
certificates, such as admincert (for each stakeholder’s administrator), cacert (for the owner),
and tlscacert (for establishing connections), as shown in Figure 6(b).
Each stakeholder in Figure 6(a) has an administrator registered in both the service blockchain
and sidechain. The stakeholders can receive certificates and public-private keys from the Fabric
CA module of the service blockchain. The administrator can also send requests to the Fabric
CA of the sidechain for offering certificates and the publicprivate key to operators in the
affiliated organization, which is responsible for registering SCOs in the sidechain. The main
blockchain’s genesis block is configured, including information of ordering service,
consortium, and each stakeholder [see Figure 6(c)]. An anchor peer is devised in each
stakeholder for cross-stakeholder communication in the service blockchain and cross-chain
interactions between the service blockchain and sidechain [see Figure 6(d)].
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Figure 6. System configuration for: (a) participant; (b) certificate; (c) genesis block; and (d)
anchor peer
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The blockchain’s execution logic is to invoke smart contracts (chaincode), deployed in both
service blockchain and sidechain to enable their cross-interactions and interactions with the
shared ledger (world state). The smart contracts SSC, RSC, ASC, and OSC in SCOs-BOs are
implemented and provide rich features for testing and debugging before deployment. Figure 7
presents the interaction patterns of chaincodes. SCO information, e.g., address and GPS data,
is stored in the ledger. The stakeholder inputs the address and arguments to initialize the
transaction and the peers access the ledger via chaincode based on APIs. Two operations are
mainly involved in chaincode: the “init” and “invoke” functions, the former when initializing
or upgrading chaincode and the latter in response to transaction proposals to query or update
the ledger. The “invoke” function comprises functions in four smart contracts: data request,
select winner SCO, cross reference, and unbiased random sortition. Cross-chain interactions
are implemented with the help of InvokeChaincode() API. The initledger function creates the
initial inputs of the ledger. The main functions and interactions of the four smart contracts in
this case study are detailed in Figure 7.

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Figure 7. Interaction patterns for chaincodes of four smart contracts
(1) Service Smart Contract (SSC)
SSC manages the on-chain interactions that can help check if the site manager, project owner,
or other stakeholders can access the location data from SCOs and then send data requests. Each
service matches one smart contract, and each stakeholder in the service blockchain can request
the location data by providing the address of stakeholders and SCOs, and the demanded number
of SCOs. To reach a more than 51% consensus on accurate location data, the demanded number
of SCOs should be no less than three. Algorithm 1 presents the algorithm of the main function
for SSC. Once the stakeholder sends a request, the SSC will check if the stakeholder can access
data and then check if the SCOs are online. Once the stakeholder’s request is approved, the
SSC will generate a token which comprises: (1) request for data, created from the address of
stakeholder, address of online SCO oracles, and demand number of SCOs, (2) address of
stakeholder, (3) address of SCOs, (4) demand number of SCOs, and (5) GPS location data of
SCOs. The tokens are generated and then delivered to the ASC. After implementing the ASC,
the final data is received by OSC, RSC, and SSC through cross-chain interaction.

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(2) Aggregator Smart Contract (ASC)
The ASC coordinates the cross-chain interactions between OSC, SSC, and RSC. SSC forwards
the stakeholder’s location data requests to the ASC, which invokes the oracles to satisfy them
by retrieving and validating SCOs’ responses from the OSC. The ASC finally reports the
reputation scores of selected SCOs to the RSC. Algorithm 2 presents the algorithm of the main
function for the ASC. A minimum of three SCOs should be sent to the ASC to conduct SCO
cross-referencing for achieving proof of location, in which at least 51% consensus on the same
location data should be reached. Otherwise, the ASC cannot judge and provide the accurate
location data sent from the OSC. The ASC cross-references the SCO data based on 51%
agreement and reports a binary reputation score to the RSC. If more than 51% of SCOs send
back the same result, these SCOs will receive a 100 reputation score, and other SCOs that
return different results will get a zero score. If less than 51% of SCOs return the same result, a
new aggregation round can be conducted.

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(3) Oracles Smart Contract (OSC)
The OSC manages the off-chain interactions to select SCOs from the oracles pool to retrieve
the location data. An unbiased random sortition algorithm (RSA) was developed to ensure that
the selection processes are independent and random (see Algorithm 3). It is also vital to ensure
that stakeholders reach a consensus in the selection processes, which means selected SCOs
cannot represent any counterpart’s benefits. RSA in OSC uses a verifiable random function
(VRF) of Algorand (Gilad et al., 2017) for the oracles pool (A set of SCOs), and they can
generate a proof and a random value for each SCO. SCOs aligned with the demanded number
are selected and recognized in the sidechain’s OSC.

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(4) Reputation Smart Contract (RSC)
The RSC aims to compute each SCO’s accumulative reputation score and return the winner
SCO with the highest accumulative reputation score to the SSC. The RSC receives an input
array of authentic SCO addresses, and it sends back an output array address of the winner SCO
to the SSC. Algorithm 4 presents the algorithm of the main function for the RSC.

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5.2 Evaluation
The most critical design philosophies in SCOs-BOs are to avoid SPoF and offer authentic
construction data to the service blockchain. To this end, an evaluation is conducted to prove
SCOs-BOs usability in screening malicious data. We assume the total number of SCOs is nine,
three of which are authentic (C1024, C1029 & C1030), two malicious (C1025 & C1026), and
four offline (C1023, C1027, C1028 &C1031), and these SCOs were transported in the same
batch, which means they should be shipped in the same vehicle with identical location data
given ignoring GPS accuracy error. We suppose that the total number of data requests is 100,
300, 500, and 1000, the required number of SCOs in each request is 3, and the default reputation
score is set to 50 for each SCO. The accumulative reputation scores and winner election count
are used as the index to validate SCOs-BOs usability.
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Winner Election Count

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Tie Count

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As shown in Figure 8 (a), all three authentic SCOs are elected under a different number of data
requests, and the tie count is also significant, which indicates that each selection is independent
and random. The results prove that SCOs-BOs can avoid SPoF and reject malicious data when
authentic data occupy the majority. However, when malicious SCOs hold the majority and
form collusion, this would limit the automatic capacity to retrieve authentic data, even though
the oracles sidechain can record the data history of each selected SCO. Figure 8 (b) shows the
records of all three authentic SCOs’ accumulative reputation scores under 100 rounds of SCOs
requests. As 47-round requests reach a tie (all selected location data are different), C1024,
C1029, C1030 only receive their reputation scores 16, 22, 15 times, respectively. It is also
interesting to find that C1029 has the most winner election counts under 100 rounds of SCOs
requests but falls to the least under 1000 requests.

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C1024
C1029
C1030
Tie

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Number of Data Requests

(a) Winner election count and tie count

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C1029

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(b) Accumulative reputation score at 100 rounds of requests
Figure 8. Evaluation of SCOs-BOs usability
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According to Hasan et al. (2018) and Almadhoun et al. (2018), security analysis of the proposed
system with smart contracts can be discussed through the aspects of confidentiality, integrity,
non-repudiation, authentication and authorization.
• Confidentiality: this study enables confidentiality through its cross-chain architecture
(e.g., channels in Hyperledger Fabric) and private data. The former supports SCOs in
establishing a sidechain, where only those peers (e.g., stakeholders, SCOs) who
participate in a sidechain can access the smart contract and data transacted. The latter
means that SCO data is stored in the private state database of authorized peers (e.g.,
project owner) and encrypted with a hash. The proposed system thus preserves both
privacy and confidentiality.
• Integrity and non-repudiation: For data to have integrity, it cannot be modified
during its transmission. All exchanged SCO data in both sidechain and service
blockchain are tamper-proof with timestamps. Furthermore, to prevent “man in the
middle” attacks and otherwise secure communications, Transport Layer Security
(TSL) in Hyperledger Fabric facilitates a data integrity check between a stakeholder
and a winner SCO. The unbiased random sortition process will be recorded in tamperproof logs in the interactions between on-chain and off-chain (e.g., SCOs selection
processes).
• Authentication: Authentication mechanisms rely on digital signatures requiring each
peer to hold two cryptographically corresponding keys: a public key is made widely
available and acts as an authentication anchor, and a private key is used to produce
digital signatures on data. This study also develops a cross-referencing mechanism to
assure the authentic SCO is selected.
• Authorization: This study uses membership service provider (MSP) in Hyperledger
Fabric to prove authorized peers’ identity. Only authorized peers can trigger the
functions of smart contracts. For example, a stakeholder uses its private key to make a
consensus (e.g., using a digital signature) on the selected SCO data. The MSP on the
ordering service contains this stakeholder’s public key, which is then used to verify
that this transaction’s signature is valid.
6. Discussion
Three novel aspects of the proposed SCOs-BOs framework are summarized as follows.
• Blockchain oracles are yet to be fully investigated in the construction context because
they are reliant on big data from humans, hardware, and software for real-time
project management. SCOs offer an innovative alternative able to satisfy the design
patterns of oracles and facilitate data exchange between blockchain and real-world
CSCM processes.
• Construction data for existing blockchain systems mainly relies on human inputs or a
centralized BIM platform. The innovative establishment of a decentralized SCO
network as a sidechain has been proven in our case study to avoid the SPoF, and

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registration of SCOs can make them more accountable when compared with
unregistered SCOs. The unbiased random sortation mechanism is also deployed to
ensure fairness in selecting and registering SCOs for the sidechain.
• The proposed cross-reference mechanism together with the reputation system,
effectively screen out malicious construction data in the evaluation section. This
innovation supports the obtaining of trustworthy SCOs and sustains their on-chain
reputation.
Despite these innovations, our study has several limitations.
• Firstly, the proposed framework is conceptual and does not claim to be able to solve
all blockchain oracle issues. Instead, the framework can work as a guideline and
provide insights to help other scholars or practitioners design the four smart contracts,
conceive the structure of main (service blockchain) and sidechains, and develop the
interaction logics of the four smart contracts. Future studies will provide other
detailed solutions under this framework, such as proof-of-inspection and proof-ofassembly by involving blockchain network operations such as ordering service and
network configuration.
• Secondly, the only request-response pattern is designed in the smart contracts for
SCOs-BOs. As limited by the case study scenarios, the publish-subscribe and
immediate-read patterns have not been explored in this study.
• Thirdly, the cross-reference mechanism in this study sets a 51% consensus on the
data. However, there is a risk that malicious data could also reach a 51% agreement
when the quantity of data or SCOs is small enough. Thus, a more flexible consensus
rate range (e.g., from 51% to 67%) in the cross-reference mechanism should be
devised and matched according to the required number of SCOs.
• Lastly, we only test the usability of the SCOs-BOs by using the index of average
reputation scores and winner election count in a case study. Enabling multiple SCOs
reporting the same data streams may increase the cost of the overall system. Thus,
other performance metrics, such as the cost of SCOs, throughput, latency, and
scalability, will be considered in the future.
7. Conclusions
With its characteristics of decentralization, immutability, and consensus, blockchain can
improve construction process coordination and collaboration in an isolated deterministic
network. Meanwhile, smart construction objects (SCOs) can offer data for blockchain by
capturing, processing, verifying, and taking action with the external construction environment
in real-time. Harnessing SCOs as blockchain oracles has the potential to enable massive valueadded services in construction but also presents Gordian knots in the form of SPoF and
malicious data. Blockchain’s power may be limited when the offered data heavily rely on a
single centralized source or low-quality sources.

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This study presents a SCOs-enabled blockchain oracles (SCOs-BOs) framework to offer a
decentralized SCO network and related data authenticity mechanism. The SCOs-BOs
framework has four parts: stakeholder, service blockchain, sidechain, and oracles pool, which
can interact with each other under the request-response pattern in an on-chain, cross-chain, or
off-chain manner. Accordingly, a blockchain-enabled construction supply chain management
(BCSCM) system is developed to instantiate SCOs-BOs. The services, such as production
quality control transparency, logistics and on-site assembly traceability, workers’ health and
safety privacy, are illustrated. A case study for logistics and on-site assembly traceability
service with four main smart contracts is implemented to evaluate its usability. The oracles
smart contract (OSC) helps form the decentralized SCO network and select the SCOs from the
oracles pool randomly and independently. The aggregator smart contract (ASC) crossreferences the data and reports the reputation scores. Then, the reputation smart contract (RSC)
manages the authentic SCOs and selects the winner. The service smart contract (SSC) monitors
the data requests and responses in an overall process. The evaluation results show that accurate
data are retrieved in each request, and the corresponding reputation scores are successfully
recorded.
Future research works are recommended to enrich the SCOs-BOs framework. For example,
logics in the four smart contracts can be developed and extended for publish–subscribe and
immediate–read patterns. A cooperative game theory-based reputation system can be used to
improve the performance of rating scores for SCOs. The data semantics enrichment can be
enhanced to ensure cross-chain, off-chain, and on-chain communication. More tests are needed
for different services, such as production quality control transparency and workers health and
safety privacy.
Acknowledgments

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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.
The authors wish to express their appreciation to the anonymous reviewers for their
constructive comments.
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