Using Images to Detect, Plan, Analyze, and Coordinate a Smart Contract in Construction
Publication: Journal of Management in Engineering
Volume 39, Issue 2
Abstract
Reliable construction workflow relies on timely discovery, analysis, and checking of compliance with contract terms, which are time consuming and inefficient tasks. Smart contracts enabled by blockchain technology have demonstrated promise in addressing the inefficiencies of data communications due to their merits of traceability, immutability, transparency, and self-enforceability. However, a smart contract’s inability to interact with real-world data is the main issue that impedes further implementation. Today’s increasing availability of as-built data provides automatic condition assessments that have great potential to automate smart contract executions. This research area is uncharted territory for the industry. This research selects a case study to present an automatic decentralized management framework by exploring image-based deep learning solutions to automate and decentralize the conditioning of smart contract executions enabled by a web3.js-based decentralized blockchain application. It was found that the model can automate management intelligence with minimal workflow interruptions by timely identification of bottleneck activities and enforcement of mitigation strategies. Project managers can use the blockchain prototype to enhance information sharing, remove key risks, and enable a reliable workflow with minimal management efforts.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Journal of Management in Engineering
Volume 39 • Issue 2 • March 2023
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© 2023 American Society of Civil Engineers.
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Received: Jun 7, 2022
Accepted: Nov 10, 2022
Published online: Jan 9, 2023
Published in print: Mar 1, 2023
Discussion open until: Jun 9, 2023
ASCE Technical Topics:
- Artificial intelligence and machine learning
- Automation and robotics
- Business management
- Case studies
- Computer programming
- Computing in civil engineering
- Construction engineering
- Construction management
- Contracts and subcontracts
- Disaster risk management
- Engineering fundamentals
- Industries
- Information management
- Methodology (by type)
- Neural networks
- Organizations
- Practice and Profession
- Research methods (by type)
- Risk management
- Systems engineering
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