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Review

Blockchain Oracles for Digital Transformation in the AECO Industry: Securing Off-Chain Data Flows for a Trusted On-Chain Environment

by
Liupengfei Wu
1,*,
Frank Ghansah
2,
Yuanben Zou
3 and
Benjamin Ababio
3
1
Division of Industrial Data Science, School of Data Science, Lingnan University, Hong Kong SAR, China
2
School of the Built Environment and Architecture, London South Bank University, London SE1 0AA, UK
3
Department of Real Estate and Construction, The University of Hong Kong, Hong Kong SAR, China
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(20), 3662; https://doi.org/10.3390/buildings15203662
Submission received: 22 August 2025 / Revised: 27 September 2025 / Accepted: 4 October 2025 / Published: 11 October 2025
(This article belongs to the Special Issue Digital Transformation and Resilience in Construction Management: Technologies, Strategies, and Applications)
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Abstract

As noted in recent blockchain review articles, several blockchain studies have attracted attention to the architecture, engineering, construction, and operation (AECO) industry. The reason is that blockchain offers opportunities to revolutionize the AECO industry owing to its transparency, traceability, and immutability. However, these benefits cannot be realized without blockchain “oracles”. Oracles are intermediary agents that connect blockchain systems to real-world applications. They function by collecting and verifying off-chain data, which is then fed into the blockchain for use by smart contracts. To investigate this uncharted territory, this paper adopts a hybrid research method of descriptive, bibliometric and content analysis; cross-mapping; and gap analysis to identify the trend; key topics; current status; future directions; and governance, ethical, legal, and social implications (GELSI) framework of blockchain oracles. This paper contributes to the body of knowledge by synthesizing trends, current status, key topics, and GELSI of blockchain oracles, promoting areas of improvement, and bridging knowledge gaps on blockchain oracles in the AECO industry.

1. Introduction

The emergence of blockchain technology offers novel prospects for designers, engineers, builders, and facility management managers for a cleaner production future [1]. Blockchain contains a decentralized network that uses broadcast ledgers to document relevant data transactions [2]. These transactions are encrypted using cryptographic algorithms and are mutually endorsed by all nodes configured in the peer network through a consensus mechanism [3]. The widely propagated benefits of blockchain technology, therefore, include enhanced security, reinforced traceability, increased efficiency, improved transparency, and reduced costs [2]. For example, it can be used as a collaborative platform during the architectural design phase to encourage stakeholder communication [4] or to address the practical challenges of protecting architectural design intellectual property on digital platforms [5]. In engineering and construction, it can help trace prefabricated components and prefinished modular integrated construction (MiC) modules in the supply chain [6], enhance construction data immutability [7], automate project contract management [8], and prevent late progress payments [9]. In the operational phase, it can store and exchange data associated with the operation of smart facilities in a decentralized manner [9]. Based on these advantages, blockchain has attracted great interest from the architecture, engineering, construction, and operation (AECO) industry.
Nevertheless, the functions of blockchain technology cannot be fully realized without the use of oracles; a term derived from Greek mythology, meaning those who can communicate directly with gods and foresee the future [10]. In the blockchain setting, oracles are intermediary means that link the blockchain-based platforms (on-chain world) and real-life practices (off-chain world) by collecting and proving data generated by the actual activities and transferring it to the blockchain for use [10]. Types of oracles in the blockchain environment are dependent on several different attributes. They can be classified as inbound or outbound according to the direction of data flow [11], or as centralized or decentralized based on the trust mode [12]. According to the data source, oracles are also classified as software, hardware, or human [13]. Many construction activities recorded by blockchain must exchange data with the outside world (e.g., real-life construction projects). When the endorsement of blockchain data depends on the state of the off-chain world, the importance of oracles cannot be ignored.
The literature search revealed that several scholars have reviewed the blockchain studies in construction, outlining its existing situation, key application scenarios, limitations, and future research directions (e.g., [10,14,15,16,17,18,19,20,21]). However, several research gaps have been identified, which are the essential impetus for this study. First, current blockchain review studies only consider the scope of the on-chain world, while the oracles are largely ignored. Second, most of these review studies involve qualitative and manual evaluation and do not outline the up-to-date blockchain oracles in the AECO industry qualitatively and quantitatively. Therefore, the research results may be influenced by personal bias. Third, previous blockchain review studies hold specific perceptions and concentrate on narrow areas. For example, ref. [16] focus on blockchain applications in disaster recovery, and ref. [19] focus on managing construction disputes. Fourth, there is a lack of governance, ethical, legal, and social implications (GELSI) framework for blockchain oracles in the AECO industry. To sum up, a literature review is needed to provide a holistic understanding and in-depth knowledge of blockchain oracles in the AECO industry.
This study aims to review the recent advances of blockchain oracles in the AECO industry. It has three specific objectives: (1) to examine the status quo of the off-chain world of oracle research in the AECO industry; (2) to determine the mainstream research topics and prospective research agenda of blockchain oracles based on the collected studies; (3) to propose a GELSI framework of blockchain oracles for the AECO industry. The structure of this paper is summarized below. Section 2 illustrates research methods. Section 3 describes the status quo of blockchain oracle research in the AECO industry. Future research agendas are given in Section 4. Section 5 presents the GELSI framework, and the conclusion is offered in Section 6.

2. Research Methods

2.1. A Guiding Research Model

In order to deliver the objectives and navigate the study plan, a guiding model consisting of six steps, namely literature review, descriptive statistical analysis, bibliometric analysis, content analysis, future research direction mapping, and legal and regulatory gap analysis is proposed, as shown in Figure 1. The first step involved a literature search and followed the PRISMA criteria, a widely adopted method for literature reviews [22]. The second step was a descriptive statistical analysis, which enabled the research team to extract annual publishing trends and understand the distribution of journals, countries, and productive authors. In step 3, bibliometric analysis was performed by the research team to understand the collaboration among researchers and their research focus. Next, we adopted the content analysis to summarize and discuss the main topics of blockchain oracles in the AECO industry. Besides, in step 5, we mapped out the future research directions after identifying the research gaps. Finally, in step 6, we developed the GELSI framework of blockchain oracles for the AECO industry based on above steps.

2.2. Literature Search

The search involved six retrieval techniques: collection, scoping, screening, reduction identification, and synthetization, as shown in Figure 2. The first step involved the search and collection of papers. The research team adopted Google Scholar and Web of Science primarily for the search and collection, chosen to maximize the chances of retrieving a wide range of relevant publications and for efficient indexing processes. The detailed search strings used for each database were as follows:
-Web of Science Core Collection: allintitle: (“blockchain oracle” OR “distributed ledger technology” OR blockchain) AND TS = (“architecture” OR “engineering” OR “construction” OR “operation” OR “AECO” OR “built environment”)
-Google Scholar: allintitle: “blockchain oracle” architecture | engineering | construction | operation
The search was limited to English-language publications. No starting date restriction was applied due to the emergent nature of blockchain oracles in the AECO industry. The search was conducted initially in June 2022 and was updated periodically, with a final cutoff date of 15 September 2025. This process yielded an initial collection of 2307 papers.
The research team also confirmed the comprehensiveness of the data collected by adopting a snowball method in the university’s e-library and Scopus, using similar query terms.
In screening the literature, several inclusion and exclusion criteria were developed. First, we limited our search to studies issued in the English language. Second, we performed the search only for journal or conference papers, as they are usually of good quality and reviewed by reviewers. Third, we compared the search results from each database and removed duplicate studies. Fourth, we screened studies by reading and checking their titles and abstracts to ensure they were relevant to our target topic. Blockchain oracles and construction were indicated in titles or abstracts in some studies, but their content was irrelevant to our target topic. Conversely, some studies did not mention blockchain oracles or construction in their title or abstract but contained research content relevant to our target topic and were therefore included in our review. After the elimination process, we were left with 1205 articles that met our inclusion criteria.
In the reduction and identification processes, these articles were downloaded and read in full by the research team to assess their relevance to our research objectives and extract relevant information for our review. It was discovered that the full papers of seven articles were unobtainable, and 1149 articles were deemed inconsistent with the topic of this research. However, we identified three additional articles through snowballing. In the end, we retained 52 articles for our final review during the synthetization process. Table 1 displays the final chosen papers and their corresponding information.

2.3. Descriptive Statistical Analysis and Bibliometric Analysis

Descriptive statistical analysis, a method to logically and systematically identify, summarize, and describe the papers above [70], was then employed. This method aimed to analyze the main characteristics of the blockchain oracle dataset without making any inferences. In this step, the publication trends, journal and country distribution, and prolific authors were analyzed using descriptive statistical analysis to summarize blockchain oracles in the AECO industry concisely. The descriptive statistical analysis results were reported numerically in the manuscript text and its tables and figures.
Next, a bibliometric analysis was conducted. As a quantitative method, bibliometric analysis was used to analyze blockchain oracle literature, mainly examining its external characteristics, namely the collaboration between authors and key research words [71]. In this study, this was achieved by using VOSviewer software (version 1.6.20). First, the collaboration network between authors was constructed and visualized using VOSviewer software. Second, VOSviewer provided text mining functions for creating and visualizing the co-occurrence network of key research words extracted from the collected blockchain oracle literature.

2.4. Content Analysis and Future Research Direction Mapping

Content analysis, as a research method, is often adopted by researchers to identify appearance of specific words, topics, or concepts if a qualitative dataset is offered [72]. In this study, it was used to determine if there were key research themes on blockchain oracles in the collected papers. Firstly, the research team defined the level of analysis, i.e., key topics rather than words or phrases. Secondly, the research team carefully read the collected papers and distinguished whether their topics belonged to the architecture, engineering, construction, or operation phase. Thirdly, if a research topic appeared at least once in the literature, the research team only counted and coded the topic one time, irrespective of the number of times it appeared. Fourthly, each of the key research topics identified is discussed in depth in Section 4 of this study.
Finally, cross-mapping was performed through the collected papers, a strategic approach to identify opportunities for further exploration [73]. Firstly, research gaps were identified by synthesizing the limitations indicated in each paper. Secondly, the identified limitations and the connections between different studies were mapped out. Thirdly, a research framework was proposed to demonstrate potential pathways for future investigations.

2.5. Legal and Regulatory Gap Analysis

The legal and regulatory gap analysis method systematically evaluates discrepancies between existing legal frameworks and the requirements for implementing emerging technologies, identifying critical areas where current regulations may be inadequate or misaligned with technological advancements. This structured approach involves mapping applicable laws, assessing compliance challenges, and pinpointing specific gaps in governance to inform the development of adaptive policies and frameworks that bridge legal requirements with technological innovation. In this study, the legal and regulatory gap analysis method systematically examined existing laws, standards, and policies through a structured approach to identify and address discrepancies between current regulatory frameworks and blockchain oracle implementation requirements in the AECO industry.

3. Current Status of Blockchain Oracles in the AECO Industry

3.1. Descriptive Statistics Results

3.1.1. Annual Publishing Trends

The annual publishing trends of blockchain oracle-related studies of the AECO industry are visualized in Figure 3. Figure 3a offers the amounts of paper published by researchers each year and percentage growth. The research team did not set a specific timeline for data collection, but the fact that the first relevant paper was published in 2017 suggests that the study on oracles for construction blockchain is a comparatively recent development. Furthermore, it is evident that since 2020, the quantity of scholars publishing articles on blockchain oracles has increased by 71.4%. Moreover, Figure 3b shows that, except for 2019, blockchain oracle research was published in journals every year. In 2022, 13 articles (twelve journal papers and one conference paper) on this subject were published, more than 10 times that of 2017. Based on the trend observed in the data, the possibility that the amounts of publications will continue to grow year on year will be high due to the attention blockchain oracle is receiving from AECO industry practitioners and researchers in 2025. Figure 3c shows that 92% of blockchain oracle papers were published in journals, while only 8% were published in conference papers. This may be because the review process of journal papers is more rigorous than conference papers. Figure 3d shows the 2025 quartile rankings of the collected blockchain oracle papers provided by the Journal Citation Reports (JCR). In JCR, quartile ranking relies on the ranking of journal impact factors, i.e., Q1 signifies the topmost 25% of journals, while Q4 characterizes the bottommost 25% of journals. Regarding the papers included, 73% of the papers were published in the first quarter, 19% of the papers were published in the second quarter, and only 8% of the papers were unranked conference papers, indicating that the existing blockchain oracle research is of good quality and has a great influence.

3.1.2. Journals

Analyzing journal statistics helps readers to acquire reliable materials and determine which journals are suitable for considerations for future studies. Out of the 52 chosen papers, the authors published 48 papers in journals and 4 papers in conferences. According to Figure 4, the 48 papers were published in 19 different journals, with eight journals publishing two or more articles and the remaining journals publishing one. Automation in Construction published 18 papers and is thus the most prominent journal in this field.

3.1.3. Countries/Regions

There were 12 countries whose institutions had authors contributing to blockchain oracle research in the AECO industry, as shown in Figure 5. During the timeframe of our analysis (from January 2017 to September 2025), China was the country that had the paramount of articles (31 papers). After China, the United States had eight publications, and then the United Kingdom, South Korea, Egypt, and Turkey each had three publications. Therefore, readers should pay attention to these countries as they are leading the latest blockchain oracle developments. Australia and Germany each published two studies on blockchain oracles in the AECO industry, while the remaining countries, such as Finland, UAE, Switzerland, and India, published one paper each. This reflects the awareness these countries attach to and their initial attempts to address off-chain security issues.
Table 2 summarizes the citations of published papers and the average citations per paper for 12 countries, showing the influence and relevance of blockchain oracle research in the AECO industry. Research from China and the United States received the most citations, with 1911 and 1094 citations, respectively. Also of attention is that even though Australia and Finland only contributed one article each among the 12 countries, their number of average citations was considerable with 196 and 180, respectively.

3.1.4. High-Yielding Authors

Pursuing publications by analyzing high-yielding authors is an effective method to comprehend the cutting-edge blockchain oracles in the AECO industry quickly. Overall, 153 authors wrote 52 papers. Among these authors, just 11 published four or more papers. As presented in Table 3, Lu and his colleagues and team members published the most papers (nine) related to blockchain oracles (eight papers with Wu and five papers with Xue), followed by Cheng and Das, who published five papers. Some authors published just one paper but had many citations, such as [23], with 180.

3.2. Bibliometric Analysis Results

3.2.1. Author Cooperation Network

The network of the author cooperation of the 52 chosen papers using VOSviewer software is shown in Figure 6. Each author is represented by a circle in the figure. The cycle size is positively correlated with the amounts of studies published on the theme of blockchain oracles, per the researcher. The timescale is indicated by different colors of the circle as displayed in the legend. Figure 6 shows some research collaboration networks related to blockchain oracles that have been established. Notably, in 2022, numerous collaborative networks were established as time progressed. For example, research team members coached by Lu, Cheng, and Zhong have demonstrated an efficient cooperation network. In contrast, researchers such as Ahmadisheykhsarmast, Sonmez, Ye, and König conducted individual research. In summary, the number of research teams focusing on oracles in the AECO industry is increasing and diversifying. However, it is expected that there will be more collaboration between scholars and research teams from different countries in the future.

3.2.2. Keyword Co-Occurrence Network

The network of keyword co-occurrence highlights critical contents of blockchain oracle research and relevant research matters [74]. We used VOSviewer software to draw the all-keyword co-occurrence network, and the threshold of occurrences was fixed as two. As a result, 41 out of 204 keywords occurred twice. Next, similar words were combined, such as “BIM” against “building information modeling,” “smart contracts” against “smart contract”, and “blockchain” against “blockchain technologies.” Thus, Figure 7 shows 30 integrated words, where nodes are assigned different colors to denote various clusters. Similar to Figure 6, the size of the node is positively interrelated with the occurrence of each keyword. In Figure 7, the co-occurrence relations among keywords are represented by curves, and the thickness of the link visualizes the bonding force of each relationship. Notably, keywords such as “blockchain,” “BIM,” “smart contracts,” and “Internet of Things” (IoT) frequently appear, signifying that the involvement of BIM, blockchain smart contracts, and IoT as blockchain oracles are a focus of researchers, as are design, smart construction objects, construction supply chain, and construction contracts.

3.3. Results of Content Analysis

The outcomes obtained from the content analysis are summarized in Section 3. Section 3.3.1 provides an overview of oracle research in the AECO industry, and Section 3.3.2 summarizes key research topics in blockchain oracle. Section 3.3.3 describes the existing situation of oracle in the industry, and Section 3.3.4 provides an in-depth discussion.

3.3.1. Overview

The engineering and construction phase attracted the most blockchain oracle research, as shown in Table 4. Among these studies, most explored software, hardware, and human-enabled blockchain oracles for construction information management. In the engineering and construction phase, smart construction objects (SCOs) have also been explored as hardware oracles for construction supply chain management (CSCM). Another primary stream of blockchain oracle research focuses on secure progress payment in construction. Additionally, a few studies have explored software and human oracles to enhance the confidentiality and security of digital design in collaboration. Only two preliminary studies were found for the operation phase.

3.3.2. Key Research Topics of Blockchain Oracles in the AECO Industry

This research identified five topics in blockchain oracle studies based on content analysis. Researchers have paid attention to CSCM and information management, as shown in Figure 8. Research on blockchain oracles for design in collaborative digital environments is a recent topic in literature. For the design-related topic, only software and human-combined oracles have been found. Using ubiquitous SCOs as oracles for CSCM is another hot topic due to their awareness, communicativeness, and autonomy. For example, SCO-enabled oracles can help to capture and mark actual situations due to their awareness. At the same time, communicativeness gives SCO-enabled oracles the power to exchange information directly to blockchain systems they have obtained through their awareness. SCO-enabled oracles can then alert blockchain users to act or autonomously perform actions based on preset rules. Another key topic is using blockchain oracles for secure interim payments in construction. Due to the immature nature of hardware oracles in capturing construction progress, most studies employed project progress management software and humans as oracles for secure interim payments. The following key blockchain oracle topic is information management, where three blockchain oracle combinations have emerged: purely human oracles, oracles that combine software and humans, and standalone hardware oracles. The last key research topic related to blockchain oracles is associated with building operation management. In literature, limited research has explored IoT sensors as oracles for building operational performance monitoring in recent years. Not surprisingly, these key topics are associated with the distinctive features of blockchain oracles in addressing input errors, data loss, and information manipulation in the off-chain world.

3.3.3. Summary of Current Status of Blockchain Oracles in the AECO Industry

Blockchain oracles have only been explored by researchers in the AECO industry since 2017, which shows the newness of the topic. While more scholars have paid attention to this topic since 2022, the overall amount of AECO blockchain oracle research papers are relatively low, and more attention is needed. Only lately have investigations on proof-of-concept and pilot testing begun to emerge. Even though decentralized blockchain has been extensively explored in the construction industry in recent years, blockchain oracles that connect blockchain systems and real-world practices have not been systematically studied. Blockchain oracles have not been widely adopted for design in collaborative digital environments, secure interim payments in construction, and building operation management, while a small number of investigations have discovered blockchain oracles for CSCM and information management in construction. In addition, there is no strong collaboration between countries and institutions, as observed in the analysis. Content analysis shows that only China and the United States are actively involved in blockchain oracle research in the AECO industry. Therefore, both industrialized and emerging economies still lack the strength to develop various blockchain oracles.

3.3.4. In-Depth Discussion of Blockchain Oracles in the AECO Industry

  • For Design in Collaborative Digital Environments
Using blockchain oracles for design in collaborative digital environments is a hot topic in research. There were only six articles on design, focusing on two aspects: namely, confidentiality and data security. Both software and human oracles have been involved in preserving the privacy of design metadata and user access control. For example, ref. [24] point out that the human-enabled consensus mechanism can serve as human oracles, and BIM can serve as software oracles for secure collaborative architectural design on the blockchain. Ref. [25] adopted design software as oracles to record design element changes, allowing project stakeholders to avoid disputes on collaborative blockchain-based digital design platforms. Ref. [26] applied InterPlanetary File System to enhance the storage of irreversible design changes of large design files, such as BIM models, so that smart contracts can provide reliable design change data for blockchain-based collaborative design platforms. Refs. [27,28] also employed BIM and smart contracts as oracles to preserve the privacy of design metadata and enhance user access control in a blockchain-enabled common data environment. Ref. [29] proposed a data escrow platform. This platform safeguards the broadness and reliability of openBIM data by feeding reliable offsite construction design data to a blockchain-enabled platform. Due to the nature of digital design, no hardware blockchain oracles were observed during the design phase.
  • For Construction Logistics and Supply Chain Management
There were 11 articles on CSCM, indicating that the combination of ubiquitous SCO-enabled oracles with CSCM has attracted attention from scholars. Ref. [1] pointed out that IoT models with sensing, processing, and communicating capacities can be integrated with construction resources to transform them into SCO-enabled blockchain oracles for various scenarios in CSCM. A few studies (e.g., [30,31,32,33]) adopted IoT oracles such as Global Positioning System (GPS) trackers and QR codes as blockchain oracles. These oracles were used to facilitate the traceability in the logistics management of prefabricated components. Likewise, inertial measurement units (IMUs) and GPS trackers were used to turn prefabricated modules into SCOs and acted as blockchain oracles to provide accurate location and motion data to blockchain-based CSCM platforms for location and quality monitoring [1]. Furthermore, ref. [34] innovatively combined SCO-enabled blockchain oracles and signature techniques. Such an integration was used to safeguard information integrity in CSCM. Ref. [35] implanted the YOLOv3 algorithm into IoT sensors to detect objects and feed reliable detection data to a blockchain-based CSCM platform. Researchers, such as [6], showed that IoT sensors can be integrated with materials (e.g., cement, gravel, and sand batches) as oracles to achieve decentralized material management for blockchain-based CSCM. Recently, ref. [36] adopted QR code and i-Core sensors, which are integrated IoT sensors with timers, hygrometers, thermometers, IMU, and GPS trackers, to feed reliable provenance and details of construction products to blockchain-based compliance checking platforms for cross-border customs clearance. Thus, minimized human resources were required while more automated and reliable production information was collected. The quantitative benefits of such systems are beginning to be documented; for instance, ref. [32] reported that their blockchain-enabled IoT-BIM platform for modular construction supply chain management shortened the average time for information retrieval and verification by 40%.
  • For Securing Interim Payments in Construction
There were eight articles on using blockchain oracles for secure interim payments in construction. Most of these studies developed software for blockchain oracles to collect construction progress data, such as web-based progress reporting software or mobile applications, with human oracles then adopted to endorse the collected progress data through the decentralized network of blockchain platforms. For example, ref. [9] developed an automated computerized protocol with a Microsoft Project add-on as oracles to collect and feed contract value and construction progress data to human oracles on a blockchain smart contract-based payment security system, minimizing arguments between quantity surveyors and main contractors on work progress and eliminating the need of third parties such as banks. Their research estimated that such a system could reduce the payment delay period from an average of 48 days to just 7 days. Refs. [37,38] adopted smart contracts and human as oracles to initiate, validate, and disburse interim payments on blockchain. Refs. [39,40,41] adopted both blockchain smart contracts and BIM as oracles for automated billing on blockchain in construction. Ref. [42] adopted mobile applications, project management applications, and smart contracts as oracles to realize payment freezing and disbursement on the blockchain. Only one study [43] explored using smart contracts and robotic construction progress detention tools as software and hardware oracles to provide reliable progress data for construction payment automation. In their pilot project, they demonstrated a 96.4% accuracy in automated progress detection and achieved a 98.5% reduction in the time required to validate progress payments, effectively eliminating delays and disputes for the monitored tasks. Furthermore, ref. [37] estimated that their blockchain-based payment framework could reduce the overall cost of payment administration by 30–35%.
  • For Building Operation Management
On the topic of building operations management, only two blockchain oracle papers focus on the key role of hardware and human oracles in the data input and verification process. For example, ref. [44] used IoT as an oracle to collect underground structural health data, which was then sent to a blockchain platform for human oracles to monitor. Ref. [19] used IoT sensors to collect building performance data for blockchain users to approve. The small number of studies found in building operations management suggest that research related to blockchain oracles remains underexplored. Reasons may include: (1) the complexity of blockchain oracles in building operations management, (2) limited awareness of blockchain oracles, (3) limited human and financial resources, (4) the interdisciplinary nature of buildings operations management, (5) emerging blockchain technology, and (6) lack of industry adoption of blockchain oracles. Future research is desired to expand the understanding of oracles in this blockchain-based domain.
  • For Information Management in Construction
Information management in construction is a key topic in blockchain oracle research. Using humans as oracles makes it easy to provide construction data to the blockchain (e.g., [45]). However, this also introduces the risk of data manipulation if the consensus mechanism is poorly designed. One group of scholars adopted both software and human oracles for blockchain platforms. In this case, software is often used as a data input and endorsement tool. For instance, ref. [7] developed software as oracles to capture the product, organization, and process information related to construction quality and then involve quality inspectors as human oracles to endorse captured information. Ref. [3] involved information-sharing software and project stakeholders as oracles to feed accurate data related to onsite assembly of modular construction to blockchain. Their case study implementation reported that the system reduced information sharing errors by approximately 25%. Other collected studies adopted IoT sensors only as hardware oracles to provide reliable information to blockchain platforms and reduce human intervention. For example ref. [23] adopted IoT sensors as oracles to collect and provide reliable design, construction, and operation information to blockchain users, and [46,47] adopted IoT sensors to offer blockchain users with trustworthy and manageable fine dust and building pollutant data, respectively, on construction sites.

3.3.5. Synthesis and Critical Analysis of Technical Characteristics and Challenges

The foregoing survey of application areas has attempted to highlight the tremendous promise blockchain oracles held for the AECO industry. Nonetheless, by also critically reflecting on the state of the literature on oracles, it is possible to distill several key technological traits, and, above all, central challenges which tend to consistently impede their mass-adoption and operational maturation. The step from mapping applications to a more theoretical level of engagement with these issues seems like an important one to take to set the direction for future investigations.
The technical approach of oracles used in the surveyed papers can be further classified into three main categories: data source, data direction, and trust. The sources of data for construction oracles are trade-offs between automated data acquisition, costs, and a contextual understanding of the input; for example, whether a software source (e.g., Application Programming Interface [APIs] of BIM models), hardware source (IoT sensors), or human validators are used. For instance, ref. [43] demonstrated the use of autonomous robotic reality capture (hardware oracles) to objectively track construction progress for payments, automating a traditionally subjective process. In contrast, studies like [9] relied on a human oracle (e.g., a project manager) to validate progress data within a software dashboard before triggering a smart contract payment, highlighting the continued reliance on human judgment for complex validation. Hardware sensors are automated, available for 24/7 data acquisition, but limited to structured and quantitative data that is easy to plug into a system and may be lacking contextual understanding or fine grain control for complex construction processes. Human validators oracles provide necessary judgment and context that may be missing from other sources but come with their own subjectivity and latency and introducing potential bias, and at the risk of a new central point of trust oracles. Inbound data (from the off-chain world to the blockchain) is the current application of AECO oracles for the data direction category; outbound oracles to effect real-world actions on the off-chain world (e.g., actuating machinery or signing bank transfers) from a smart contract are largely unexplored and the next step towards complete process automation. The last item, trust, is both a philosophical and pragmatic problem. The blockchain is inherently decentralized, but most AECO oracle proposals involve centralizing or federating data points in a counterintuitive way. Examples of this include a single BIM model controlled by an architect or a single sensor data point. Ironically, this reintroduces a single point of failure, which blockchain is specifically intended to eliminate. This reintroduces a central point of failure, since the validity of the entire on-chain record hinges on the security and honesty of its off-chain components.
Decentralized Oracle Networks (DONs) are one of the most popular suggested solutions to the “oracle problem” [75]. DONs pull data from multiple nodes and sources, with the information delivered on-chain being verified through cryptographic and economic means in order to ensure that the data is correct and tamper-proof. Although general-purpose DONs, such as Chainlink, are now commonplace, their use in AECO is still in its early stages. That being said, there are some projects that are leading the way in AECO-specific implementations, such as BUILDCHAIN. BUILDCHAIN is a construction industry-specific implementation of DONs that is looking to provide decentralized, trustworthy data feeds for smart contracts in a variety of areas, including supply chain tracking and progress verification [76]. The study of AECO-specific DON implementations such as BUILDCHAIN is an important area for future research as these are likely to offer the solutions that are needed to eliminate the trust paradox involved with using oracles, while still maintaining the decentralized nature of blockchain [75].
Our analysis identifies four paramount challenges that underpin these technical characteristics. First and foremost is the oracle problem, which questions the trustworthiness of data entering an otherwise trustless system. A blockchain’s immutability is rendered meaningless if the external data it receives is inaccurate or maliciously manipulated. This was a noted limitation in the pilot study by [3], where the accuracy of onsite assembly information fed to the blockchain was contingent on the reliability of the mobile app and the workers inputting the data, creating a potential vulnerability. It is not merely a technical issue but a profound philosophical challenge for decentralized systems. The use of commercial DONs, such as Chainlink, is a mature and working option when considering DONs for decentralized data feeds, but it also raises questions of complexity and potential high cost when integrated into the AECO industry. The practical application and proof of their efficacy have not yet been widely demonstrated in peer-reviewed literature, particularly in the adversarial and complex context of a construction project, where verification of progress payments or quality may require complex, expert analysis.
Secondly, scalability and cost need to be considered. For example, ref. [1] discussed the significant cost and energy consumption associated with storing high-frequency sensor data from SCOs directly on-chain, a challenge that limited the scope of their proposed supply chain management system. Thus, the monetary and computational cost of constantly writing high frequency sensor data to a blockchain is absurd. Transaction (gas) fees and consensus latency make the constant real-time monitoring of an entire project site economically or technically infeasible with today’s technology. This obviously strongly limits oracle use cases to high-value, low-frequency events like milestone verification for payments or end of project compliance checks, as opposed to continuous performance monitoring.
Thirdly, there is the challenge of system integration complexity. The AECO industry is a heavily siloed software landscape (e.g., BIM, project management, IoT platforms). Implementing oracles to achieve a seamless data pipeline from these legacy systems through the oracle layer to the blockchain will require engineering significant middleware and standard APIs. The case study by [32] on an IoT-BIM platform explicitly detailed the non-trivial challenge of developing middleware to integrate data from various IoT sensors (hardware oracles) with a BIM model and then feed a consolidated data stream to the blockchain. The integration complexity represents a major barrier to entry for typical construction firms. This results in substantial technical debt and operational overhead. This can be a massive barrier to entry for firms without strong digital integration skills.
Lastly, another challenge is missing data standardization and contextualization. The data pushed by most oracles is raw and atomic (e.g., temperature: 25° C, location: X, Y). However, construction process is a very contextual process. A human manager knows that a late shipment event occurred because of weather event, and not because the supplier is late. Smart contracts consuming only raw data from oracles are context agnostic. They are inherently brittle and are unable to deal with exceptions and context which ultimately are the norm in construction projects. The absence of industry-wide standardized data schemas for oracle-reported information further complicates the development of robust and interoperable smart contract logic. Ref. [4]’s work on confidential BIM collaboration highlighted this issue. Their system could control access to a BIM model (a software oracle), but the smart contracts lacked the ability to understand the context or significance of the design changes being made, operating only on pre-defined, rule-based permissions.

4. Future Research Directions

4.1. A Research Direction Mapping Framework for Blockchain Oracles

As shown in Figure 9, the research team proposed a framework to cross-map present research, key topics, and forthcoming investigation directions to address key research gaps, although some preliminary studies have explored blockchain oracles for the AECO industry. Project teams and researchers can benefit from the identified future research directions to gain a timely and systematically comprehensive understanding of new trends in blockchain oracles and their potential for the future of the industry.

4.2. Future Research Directions

4.2.1. Zero Knowledge Proof-Enabled Software Oracles for Design in Collaborative Digital Environments

Trust is an important yet complex issue in a digital design environment where multiple parties collaborate. In the AECO industry, BIM is a popular and thriving technology which facilitates efficient design among stakeholders. Ensuring that the right individuals access the appropriate design content (e.g., BIM)—in essence, addressing authentication concerns—has emerged as one of the most critical issues in BIM-based collaboration. Existing software and human blockchain oracles for collaborative digital design mainly involve access control models [31]. However, these models cannot protect against intentional theft of authentication credentials such as passwords and private keys, otherwise referred to as password attacks. Zero-knowledge proof (ZKP), on the other hand, is a cryptographic method with three important properties [31]; namely, (1) completeness, where an honest prover can persuade the verifier if the statement is true; (2) reliability, which guarantees that the verifier can be misled with negligible probability if the prover does not know the statement; and (3) surety that the verifier only confirms that “the prover has this knowledge”, without the need for additional meaningful information. These fundamental properties of ZKP enhance the reliability of blockchain oracles, thus offering integrity and security assurances for blockchain-based design data. For example, ZKP can recognize a random subset of on-chain historical BIM design records to prove the designer identity.

4.2.2. Decentralized SCO Combinations for CSCM

To maximize cost efficiency, several SCO design profiles can be combined and contrasted according to the CSCM mission’s goals. SCOs can work either as oracle machinists that analyze and transmit precise, dependable, and validated data to blockchain-based CSCM systems, or they can perform as data suppliers, collecting and sensing information from a variety of CSCM resources and circumstances. For example, positioning services in cross-border logistics can be used using a low-energy SCO that has a single GPS. High-frequency sensors that track various motions and environmental conditions can also be used in field installation and production environments that are offshore or off-site. Figure 10 shows the various design patterns of SCO-enabled blockchain oracles.

4.2.3. The Adoption of Hardware Oracles for Secure Interim Payments in Construction

Future research could use hardware oracles, such as autonomous robotic reality capture technologies, to provide precise progress data to smart contracts for construction job payments. Most current research on blockchain oracles use software oracles to collect progress data, which is subsequently forwarded to human oracles for approval. However, there is a possibility that information could be falsified or that there will be disputes over the exact amount of work completed. Autonomous robotic reality capture systems continually record and monitor building progress with high accuracy and reliability. Eliminating or minimizing the need for human intermediaries in the endorsement process can significantly reduce the risk of data manipulation, disagreements, and erroneous progress. For example, in two real real-life projects in Canada and the United States, [43] studied the use of drones with cameras and remote-controlled cars with laser scanners to record the progress of smart payments. There are two primary future directions identified: (1) using multi-sensory reality capture hardware to monitor and identify alternations of geometry and visual aspects within the physical construction site; this ensures that construction progress and quality are securely fed to smart contracts without the risk of human data manipulation; and (2) developing hybrid contracts that involve both decentralized smart contracts and traditional contracts, summarizing the records of adjustments of off-chain and on-chain workflows and specify the degree of human involvement.

4.2.4. Artificial Intelligence and Hardware-Enabled Blockchain Oracles for Building Operation Management

Integrating artificial intelligence (AI) and hardware-enabled blockchain oracles is a potential future research direction to advance efficiency and reliability in building operation management. For instance, advanced hardware oracles like IoT devices and autonomous robots can collect real-time data related to building performance and then feed the data to intelligent AI algorithms. Such integration can enable the combined use of multimodal AI, and hardware blockchain oracles to automatically trigger smart contracts that self-execute predefined actions (e.g., maintenance requests) based on the received data. As a result, blockchain users may improve energy efficiency significantly, receive maintenance requirements timely, and guarantee regulatory compliance accurately. Integrating AI algorithms and hardware-enabled blockchain oracles can ultimately enhance building operation performance with reinforced data security.

4.2.5. Large Language Model and Hardware-Enabled Blockchain Oracles for Information Management in Construction

Integrating large language models (LLMs) and hardware-enabled blockchain oracles can facilitate information management in construction. However, existing studies have yet to explore this emerging area. Hardware-enabled blockchain oracles can feed reliable data to blockchain systems without human judgment. LLMs can then learn statistical relationships from data collected (e.g., project documentation, emails, and reports) on blockchain systems in self-supervised and semi-supervised training processes while maintaining data reliability. For example, LLMs can generate a monthly construction progress report based on the progress data collected by autonomous robotic reality capture technologies, and smart contracts can then feed this progress report to project stakeholders. As a result, blockchain users can gain valuable insights that facilitate the decision-making process. However, domain-specific LLMs for the AECO industry and a secure LLM and hardware blockchain oracle integration method need further study.

5. A Governance, Ethical, Legal, and Social Implications (GELSI) Framework for Blockchain Oracles in the AECO Industry

Blockchain oracles, which serve as bridges between off-chain and on-chain data, present intricate challenges in their application within the AECO industry. It is not only necessary to maintain existing GELSI standards but also to anticipate and mitigate the consequences that can arise from their usage. To this end, the GELSI framework presented in Figure 11 can help to provide a detailed set of use case-relevant steps to ensure responsible and fruitful implementation of blockchain oracles in the AECO industry. The framework, summarized in Figure 11 and detailed in Table 5, aligns with existing regulations and provides actionable guidelines for practitioners.

5.1. Governance Implications

Blockchain oracles present their own governance challenges and questions. If blockchain transactions are immutable and auditable, the “oracle problem” is how to guarantee the immutability of the input data to the blockchain in the first place. Besides high-level policy concerns, more granular and actionable good governance for oracles needs to map to current AECO industry standards and practices where they already exist. For example, an information management process defined in accordance with ISO 19650 provides a useful model for describing the roles, responsibilities, and data requirements of oracle nodes and a project CDE in particular. A DON model with a DAO of stakeholders in the project can guard against centralization. Metrics for oracle performance (latency, accuracy, etc.) could be incorporated into the information management plan of a project.

5.2. Ethical Implications

The Ethical considerations also need to be proactive. Algorithmic bias in AI-based hardware oracles (e.g., drones evaluating progress) should be prevented by regular audits and diverse training datasets, following emerging standards such as the EU’s Ethics Guidelines for Trustworthy AI. To ensure smaller companies are not priced out, the cost of participating in oracle networks may need to be minimized or subsidized, possibly through consortium-based funding models. Transparency is also crucial; oracle data sources and methods should be auditable to ensure trust. This is particularly important for data collected in public spaces, where citizen consent and privacy must be strictly maintained.

5.3. Legal Implications

The legal framework is an important domain for pragmatic alignment. Smart contracts tied to oracles must be legally enforceable, which means anchoring them on adapted versions of tried-and-tested standard contracts like FIDIC, where a handful of new clauses may be enough to define oracle-fed data as a certified source for either triggering payments (Clause 14 [Contract Price and Payments]) or to make a claim for variations (Clause 13 [Variations and Adjustments]), including an explicit carve-up of liability for oracle failure in Oracle SLAs, which allocates liability between the technology provider, the node operator and the data sources.
Data privacy presents a paramount challenge. Any oracles gathering data on construction sites have to follow GDPR, CCPA and other privacy laws, which means they must be “privacy-by-design”—i.e., they should be set up to only collect data they need, to pseudonymize personal information at source, and use cryptographic techniques (e.g., ZKPs) to verify information without showing raw personal data on the public ledger, in accordance with not just legal but also information security industry best practice.

5.4. Social Implications

The social element must address workforce transition management and tangible societal benefit. Augmentation, not replacement, should be the mantra. Oracles should be deployed to automate the low-value data validation steps that currently occupy experts, shifting their focus to higher-value decision-making. Targeted upskilling programs may be required. For example, the benefit should be a higher degree of fairness. Immutable oracle data can remove the all-too-common risk of late or non-payment on a subcontractor’s project, which has been a long-term social ill in the industry. Public trust may be garnered by framing the technical features in terms of public goods, e.g., a higher degree of accountability on publicly funded infrastructure projects.

6. Conclusions

Because blockchain technology is transparent, traceable, and immutable, it presents new opportunities to transform the AECO sector. However, these blockchain advantages cannot be wholly realized without oracles that connect the actual physical project and blockchain platforms. This research reveals cutting-edge patterns in development and potential paths for blockchain oracles in the AECO sector. The descriptive statistics and bibliometric analysis first identify annual publishing trends, journal distribution, nation distribution, prolific authors, author collaboration networks, and keyword co-occurrence. Second, the key research topics and current status of blockchain oracles were summarized, and key topics related to CSCM, secure interim payment, building operation management, information management, and design in collaborative digital environments were discussed as they are five crucial study issues that promise blockchain oracle development in the AECO sector. Next, the research framework was used to define and explain research gaps and future study goals. Finally, a GELSI framework of blockchain oracles in the AECO industry was proposed.
This research makes six major contributions to the body of knowledge. To help researchers correctly understand and grasp the current trends, this study first helps to systematically analyze and summarize publication and collaboration channels that can exert an impact on the sustainable development of oracles in the blockchain-based environment of the AECO industry. Second, this study identifies five key research topics related to blockchain oracles in the AECO industry: (1) design in collaborative digital environments, (2) construction logistics and supply chain management, (3) secure interim payments in construction, (4) building operation management, and (5) information management. Identifying key research topics helps highlight the focus areas for further in-depth investigation. Third, this study contributes a framework for cross-mapping current research, key topics, and future research directions in blockchain oracles. This framework can guide researchers, project teams, and industry practitioners in understanding the landscape of blockchain oracles in the AECO industry. Fourth, this study provides a roadmap for further exploration in the field of blockchain oracles by offering insights for future research directions, such as the use of zero-knowledge proof-enabled software oracles, decentralized smart construction objects for supply chain management, hardware-enabled blockchain oracles for secure payments, AI integration for building operation management, and the adoption of large language models for information management in construction. Fifth, this study facilitates the dissemination of knowledge of blockchain oracles. Sixth, this study proposes a GELSI framework of blockchain oracles in the AECO industry. It promotes collaboration in advancing the use of blockchain oracles in the AECO industry by bridging the gap between academic researchers, industry practitioners, and software suppliers.
This study has several limitations that present opportunities for future research. First, its scope was deliberately focused on the AECO industry. A comparative analysis of oracle implementations in other sectors (e.g., finance, healthcare, logistics) could yield valuable cross-disciplinary insights and best practices applicable to AECO. Second, while we focused on major application domains, several emerging niche applications such as decentralized carbon credit verification, real-time safety compliance monitoring, and asset tokenization were beyond our scope but represent vital avenues for future investigation. Finally, the rapidly evolving nature of both blockchain and oracle technology means that this review captures a snapshot in time. The dynamic landscape necessitates ongoing research, and we recommend a subsequent literature review be conducted within the next five years to integrate new findings and track the evolution of this field. The results generated from this research are vigorous, but they may change over time as oracles are novel to the industry. It is advised that another evaluation be carried out during the next five years, and future research should incorporate new publications based on the May 2024 deadline of this assessment.

Author Contributions

Conceptualization, L.W. and F.G.; methodology, L.W., F.G., and Y.Z.; software, L.W.; validation, L.W. and F.G.; formal analysis, L.W.; investigation, L.W.; resources, L.W. and Y.Z.; data curation, L.W. and Y.Z.; writing—original draft preparation, L.W.; writing—review and editing, F.G. and B.A.; visualization, L.W. and B.A.; supervision, L.W.; project administration, L.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. A guiding research model.
Figure 1. A guiding research model.
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Figure 2. Literature search and screening strategy.
Figure 2. Literature search and screening strategy.
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Figure 3. Publication distribution and scientific journal ranking: (a) publication amounts; (b) publication distribution each year; (c) document type; (d) scientific journal ranking.
Figure 3. Publication distribution and scientific journal ranking: (a) publication amounts; (b) publication distribution each year; (c) document type; (d) scientific journal ranking.
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Figure 4. Distribution of papers published in different journals.
Figure 4. Distribution of papers published in different journals.
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Figure 5. Geographical distribution of published blockchain oracle papers in the AECO industry.
Figure 5. Geographical distribution of published blockchain oracle papers in the AECO industry.
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Figure 6. Author cooperation network.
Figure 6. Author cooperation network.
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Figure 7. Keyword co-occurrence network.
Figure 7. Keyword co-occurrence network.
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Figure 8. Five major research topics related to blockchain oracles in the AECO industry.
Figure 8. Five major research topics related to blockchain oracles in the AECO industry.
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Figure 9. A research direction mapping framework for blockchain oracles.
Figure 9. A research direction mapping framework for blockchain oracles.
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Figure 10. Various design patterns of SCO-enabled blockchain oracles.
Figure 10. Various design patterns of SCO-enabled blockchain oracles.
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Figure 11. GELSI framework for blockchain oracles in the AECO industry.
Figure 11. GELSI framework for blockchain oracles in the AECO industry.
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Table 1. Selected papers for this study.
Table 1. Selected papers for this study.
No.References *Article TypeOracle TypeMethodsAECO
1[1]JournalHardwareCase study❖❖
2[3]JournalSoftware/HumanCase study❖❖
3[4]JournalSoftwarePoC❖❖
4[7]JournalSoftware/HumanPoC❖❖
4[8]JournalSoftware/HumanPoC❖❖
5[9]JournalSoftware/HumanCase study❖❖
7[20]JournalSoftware/HumanCase study❖❖
8[23]JournalHardwareTheoretical concept❖❖❖
9[24]ConferenceSoftware/HumanPoC❖❖
10[25]ConferenceSoftwareTheoretical concept❖❖
11[26]JournalSoftwarePoC❖❖
12[27]JournalSoftware/HumanCase study❖❖
13[28]JournalSoftwareCase study❖❖
14[29]JournalSoftwarePoC,
Questionnaire		❖❖
15[30]JournalSoftware/HumanCase study❖❖
16[31]ConferenceHardwareCase study❖❖
17[32]JournalHardware/SoftwareCase study❖❖
18[33]JournalSoftware/HumanPoC❖❖
19[34]JournalHardware/HumanCase study❖❖
20[35]JournalHardwarePoC❖❖
21[36]JournalHardware/Human/SoftwareCase study❖❖
22[37]JournalSoftware/HumanPoC❖❖
23[38]JournalSoftware/HumanPoC❖❖
24[39]ConferenceSoftwarePoC❖❖
25[40]JournalSoftwarePoC❖❖
26[41]JournalSoftware/HumanPoC,
Questionnaire		❖❖
27[42]JournalSoftware/HardwareCase study❖❖
28[43]JournalHardwareCase study❖❖
29[44]JournalHardwarePoC❖❖❖
30[45]JournalHumanCase study❖❖
31[46]JournalSoftware/HardwarePoC❖❖
32[47]JournalHardwarePoC❖❖
33[48]JournalSoftware/HumanPoC❖❖
34[49]JournalSoftware/HumanCase study❖❖
35[50]JournalHuman/SoftwarePoC❖❖
36[51]JournalHardware/Human/SoftwareCase study ❖
37[52]JournalSoftware/HumanPoC❖❖❖
38[53]JournalSoftware/HumanPoC❖❖
39[54]JournalHuman/SoftwareCase study❖❖
40[55]JournalHardwareCase study❖❖
41[56]JournalSoftwareCase study❖❖
42[57]JournalSoftwareCase study❖❖
43[58]JournalSoftwareCase study❖❖
44[59]JournalHuman/SoftwareCase study❖❖
45[60]JournalHardware/HumanPoC❖❖
46[61]JournalHuman/SoftwareCase study❖❖
47[62]JournalHumanCase study❖❖
48[63]JournalSoftware/HumanCase study❖❖
49[64]JournalHuman/SoftwarePoC ❖
50[65]JournalHuman/SoftwareCase study ❖
51[66]JournalHuman/SoftwarePoC ❖
52[67]Journal Human/SoftwarePoC ❖
PoC = proof of concept. ❖ = The study is involved in this phase. * = [68,69] were excluded from this table due to lack of information realted to oracles.
Table 2. Citations and average citations of published paper.
Table 2. Citations and average citations of published paper.
No.CountryCitations of Published PapersAverage Citations of Each Paper
1China193762.48
2United States1094136.75
3United Kingdom6020.00
4South Korea15752.33
5Turkey29999.67
6Egypt3913.00
7Germany14572.50
8Australia19798.50
9Finland180180.00
10United Arab Emirates7272.00
11Switzerland1131.00
12India1616.00
Table 3. List of high-yielding authors who have at least four papers.
Table 3. List of high-yielding authors who have at least four papers.
AuthorsNo. of Published PapersUniversity
Lu, W.9The University of Hong Kong (HKU)
Wu, L.8HKU
Xue, F.5HKU
Cheng, J.5The Hong Kong University of Science and Technology (HKUST)
Das, M.5HKUST
Zhong, B.5Huazhong University of Science and Technology
Tao, X.4HKUST
Li, X.4HKU
Xu, J.4HKU
Zhao, R.4HKU
Lou, J.4HKU
Table 4. Distribution of blockchain oracle studies in various phases of the AECO industry.
Table 4. Distribution of blockchain oracle studies in various phases of the AECO industry.
PhaseNo. of PublicationsRelative Percentage
Architecture, engineering
and construction (AEC)		4484.62%
Purely engineering
and construction (EC)		59.62%
3-multiple phases (AECO)35.76%
Total52100%
Table 5. Implementation guidelines for blockchain oracles in AECO.
Table 5. Implementation guidelines for blockchain oracles in AECO.
DimensionKey ChallengesImplementation Guidelines & StrategiesRelevant Standards & Frameworks for Alignment
GovernanceData validation, reliable node operation, consensus mechanisms, single points of failure, system interoperability.
  • Adopt a DON with a diverse set of node operators (academics, contractors, clients, insurers).
  • Implement slashing conditions to penalize malicious or unreliable nodes.
  • Establish a Decentralized Autonomous Organization (DAO) or a hybrid oversight committee for oracle selection and dispute resolution.
  • Ensure oracle data formats are compatible with existing BIM (ISO 19650) and construction data classification (e.g., Uniclass) standards.
ISO 19650 (Information Management, FIDIC Contract Suite
ReNo EthicalData tampering, algorithmic bias in IoT sensors, exclusion of smaller stakeholders, lack of transparency.
  • Publish oracle source code and data validation methodologies for public audit (Open-Source ethos).
  • Conduct bias audits on AI/ML models used by hardware oracles.
  • Design tiered oracle networks allowing participation with varying levels of investment (e.g., hardware or software-only nodes).
  • Establish clear consent procedures for data collection on public infrastructure projects, especially when using visual capture technologies (drones, cameras).
IEEE Ethically Aligned Design, EU Ethics Guidelines for Trustworthy AI
LegalLiability for oracle failure, smart contract enforceability, cross-jurisdictional compliance, data privacy.
  • Develop explicit Oracle Service Level Agreements (SLAs) defining uptime, accuracy, and liability clauses.
  • Modify traditional contract conditions (e.g., FIDIC Clause 4.12 [Unforeseen Conditions]) to reference oracle-fed data as a trigger for compensation events.
  • Design systems for GDPR/CCPA compliance: implement “privacy-by-design” in oracles (e.g., data minimization, on-device processing), and establish clear data controller/processor roles for oracle nodes.
  • Use Zero-Knowledge Proofs (ZKPs) to validate data without exposing sensitive personal information on-chain.
GDPR, CCPA, FIDIC Contracts, Model Law on Electronic Transferable Records (UNCITRAL)
SocialWorkforce displacement, marginalization of traditional knowledge, digital divide, public skepticism.
  • Develop training programs to upskill existing workforce (e.g., “Oracle Data Validator” as a new role).
  • Showcase social benefits: use oracles to automate and guarantee timely payments to subcontractors and suppliers, improving financial fairness.
  • Launch public engagement campaigns to demystify blockchain and oracle technology, focusing on benefits like enhanced transparency and auditability in public projects.
  • Implement hybrid decision-making models where oracle data informs but does not autonomously execute critical decisions requiring human judgment.
UN Sustainable Development Goals (SDG 9, 11), Industry-specific Collective Bargaining Agreements
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Wu, L.; Ghansah, F.; Zou, Y.; Ababio, B. Blockchain Oracles for Digital Transformation in the AECO Industry: Securing Off-Chain Data Flows for a Trusted On-Chain Environment. Buildings 2025, 15, 3662. https://doi.org/10.3390/buildings15203662

AMA Style

Wu L, Ghansah F, Zou Y, Ababio B. Blockchain Oracles for Digital Transformation in the AECO Industry: Securing Off-Chain Data Flows for a Trusted On-Chain Environment. Buildings. 2025; 15(20):3662. https://doi.org/10.3390/buildings15203662

Chicago/Turabian Style

Wu, Liupengfei, Frank Ghansah, Yuanben Zou, and Benjamin Ababio. 2025. "Blockchain Oracles for Digital Transformation in the AECO Industry: Securing Off-Chain Data Flows for a Trusted On-Chain Environment" Buildings 15, no. 20: 3662. https://doi.org/10.3390/buildings15203662

APA Style

Wu, L., Ghansah, F., Zou, Y., & Ababio, B. (2025). Blockchain Oracles for Digital Transformation in the AECO Industry: Securing Off-Chain Data Flows for a Trusted On-Chain Environment. Buildings, 15(20), 3662. https://doi.org/10.3390/buildings15203662

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