The research paper deals with the optimization route of whole-process quality management in construction engineering projects in the era of intelligence, and develops a comprehensive quality-control system, which is aimed at reviewing designs, construction implementation, electrical installation regulation, acceptance of hidden work, commissioning, and handing over at the end. In order to solve the practical issues of scattered quality information, low accountability, slow feedback, and poor interaction between civil and electromechanical systems, the study proposes blockchain, smart contracts, and advanced CP-ABE mechanism as the reliable technical basis of the quality-management platform, thus allowing sharing, dynamic access and full tracing of essential quality records, inspection findings, correction logs, and electrical commissioning information in a safe manner. The results of the experiments demonstrate that the given mechanism has obvious performance benefits in terms of platform-side quality data processing: ciphertext size is constant (5.8 KB), and upload time is regulated (9.2 ms) and memory consumption is low (13.9 MB and CPU usage is 26.1 percent under 25 attributes), whereas latency in tracing situations does not exceed 0.41 s with throughput exceeding 570 bits. The model also yields very high defense rates when Sybil and DoS and U2R attacks are considered. These findings suggest that the suggested methodology has the potential to offer a useful technical assistance to the intelligent development of whole-process quality management, particularly when it comes to quality adjustment and collaborative control in electrical engineering subsystems.
Povzetek: The proposed research paper presents an intelligent whole-process quality management model of construction engineering projects, especially focusing on the coordinated control of electrical installation quality, system adjustment, and multi-party quality evidence circulation. With the use of blockchain, smart contracts and attribute-based encryption, the model can facilitate trusted quality record keeping, high-quality permission control as well as end-to-end traceability of inspection and correction actions. Experimental findings confirm the effectiveness of the model in terms of responsiveness, resource usage, and safety protection, and it is able to offer a reliable technical assistance to enhance the quality governance ability in intelligent construction settings.
