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Advances in Smart Construction and Intelligent Buildings
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Advances in Smart Construction and Intelligent Buildings

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 20 October 2025 | Viewed by 958

Special Issue Editors

Dr. Na Xu

E-Mail Website
Guest Editor
School of Mechanics and Civil Engineering, China University of Mining & Technology, Xuzhou 221000, China
Interests: safety risk management; knowledge management; artificial intelligence; big data
Prof. Dr. Wei Chen

E-Mail Website
Guest Editor
School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China
Interests: mine communication; artificial intelligence; industrial Internet of Things; safety monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue seeks to curate groundbreaking research at the intersection of digital transformation, automation, and sustainability in the built environment. As urbanization and climate imperatives intensify, the integration of smart technologies—including IoT, AI-driven analytics, digital twins, robotics, and self-healing materials—into construction and building management systems has become pivotal. We invite contributions that transcend traditional disciplinary boundaries, addressing challenges such as real-time adaptive infrastructure design, energy-autonomous buildings, resilient urban systems, and human-centric intelligent environments. Submissions should emphasize novel theoretical frameworks, experimental validations, or scalable case studies that demonstrate transformative impacts on efficiency, safety, and environmental performance. Of particular interest are studies leveraging generative AI for design optimization, blockchain-enabled lifecycle management, autonomous robotic systems for construction, and bio-inspired adaptive materials. Cross-disciplinary approaches bridging civil engineering, computer science, materials science, and behavioral economics are strongly encouraged. This Special Issue will prioritize works that not only advance technical frontiers but also critically address ethical, regulatory, and socio-economic dimensions of smart construction ecosystems. By fostering dialog between academia and industry, we aim to establish a roadmap for next-generation intelligent buildings that harmonize technological innovation with planetary stewardship and occupant well-being.

Dr. Na Xu
Prof. Dr. Wei Chen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital twins
  • IoT-enabled infrastructure
  • sustainable urban resilience
  • generative AI in architecture
  • autonomous construction robotics
  • self-healing building materials
  • blockchain for lifecycle management
  • cognitive building automation
  • energy-positive structures
  • big data analytics in BIM

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Published Papers (1 paper)

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Research

16 pages, 2935 KiB  
Article
LLM-Enhanced Framework for Building Domain-Specific Lexicon for Urban Power Grid Design
by Yan Xu, Tao Wang, Yang Yuan, Ziyue Huang, Xi Chen, Bo Zhang, Xiaorong Zhang and Zehua Wang
Appl. Sci. 2025, 15(8), 4134; https://doi.org/10.3390/app15084134 - 9 Apr 2025
Viewed by 302
Abstract
Traditional methods for urban power grid design have struggled to meet the demands of multi-energy integration and high resilience scenarios due to issues such as delayed updates of terminology and semantic ambiguity. Current techniques for constructing domain-specific lexicons face challenges like the insufficient [...] Read more.
Traditional methods for urban power grid design have struggled to meet the demands of multi-energy integration and high resilience scenarios due to issues such as delayed updates of terminology and semantic ambiguity. Current techniques for constructing domain-specific lexicons face challenges like the insufficient coverage of specialized vocabulary and imprecise synonym mining, which restrict the semantic parsing capabilities of intelligent design systems. To address these challenges, this study proposes a framework for constructing a domain-specific lexicon for urban power grid design based on Large Language Models (LLMs). The aim is to enhance the accuracy and practicality of the lexicon through multi-level term extraction and synonym expansion. Initially, a structured corpus covering national and industry standards in the field of power was constructed. An improved Term Frequency–Inverse Document Frequency (TF-IDF) algorithm, combined with mutual information and adjacency entropy filtering mechanisms, was utilized to extract high-quality seed vocabulary from 3426 candidate terms. Leveraging LLMs, multi-level prompt templates were designed to guide synonym mining, incorporating a self-correction mechanism for semantic verification to mitigate errors caused by model hallucinations. This approach successfully built a domain-specific lexicon comprising 3426 core seed words and 10,745 synonyms. The average cosine similarity of synonym pairs reached 0.86, and expert validation confirmed an accuracy rate of 89.3%; text classification experiments showed that integrating the domain-specific dictionary improved the classifier’s F1-score by 9.2%, demonstrating the effectiveness of the method. This research innovatively constructs a high-precision terminology dictionary in the field of power design for the first time through embedding domain-driven constraints and validation workflows, solving the problems of insufficient coverage and imprecise expansion of traditional methods, and supporting the development of semantically intelligent systems for smart urban power grid design, with significant practical application value. Full article
(This article belongs to the Special Issue Advances in Smart Construction and Intelligent Buildings)
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