Archives

• ISSUE 3

  Vol. 4 No. 3 (2026)
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  ISSUE 2

  Vol. 1 No. 2 (2026)

  This issue concentrates on artificial‑intelligence tools for construction projects. Papers explore how large language models can analyse risks and generate real‑time insights, how to detect and mitigate hallucinations in AI‑powered project tools, and how AI can optimise workflows and safety protocols. Other articles assess language models for regulatory compliance, integrate AI tools for risk management and apply computer‑vision and predictive‑maintenance methods to raise industrial‑engineering safety standards.

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  ISSUE 1

  Vol. 1 No. 1 (2026)

  This issue blends supply‑chain resilience with cutting‑edge semantic‑enrichment research. Articles propose integrated green‑logistics and risk‑management frameworks, human‑in‑the‑loop workflows for semantic technologies, calibration of sensors for autonomous systems and combining semantic enrichment with machine‑learning models. Other studies cover bi‑level programming and robust optimisation for sustainable supply‑chain design, big‑data analytics for semantic enrichment, quantum computing for load‑forecasting in smart grids, blockchain‑fuzzy‑logic security for smart grids and AI‑driven risk management and project‑timeline optimisation.

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  ISSUE 5

  Vol. 1 No. 1 (2025)

  The fifth issue of 2025 emphasises semantic‑enrichment pipelines and decision‑support systems. A multi‑agent framework combines retrieval, generative models, calibration and human review for collaborative enrichment, while a systematic survey catalogues a decade of enrichment methods, calibration techniques and human‑in‑the‑loop patterns. Another paper proposes a decision‑intelligence framework that integrates predictive analytics, optimisation and deep‑learning models to support operational decision‑making.

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  ISSUE 4

  Vol. 4 No. 1 (2025)

  This issue showcases AI‑driven models for urban sustainability. Studies assess subsidence impacts on power transmission towers through multi‑source data and hybrid AI–geotechnical modelling and develop machine‑learning models for air‑quality and subsidence forecasting. Others propose AI‑driven urban resilience planning, optimise energy infrastructure for climate‑adaptive cities, manage water resources using AI, enhance smart‑grid resilience, optimise transportation networks, support disaster preparedness and integrate multi‑hazard resilience frameworks.

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  ISSUE 3

  Vol. 3 No. 1 (2025)

  Dedicated to wearable sensing, this issue presents ionic‑liquid–metal–organic‑framework (IL‑MOF) sensors with self‑healing capabilities for gas detection, energy‑efficient IL‑MOF sensors with wireless integration, flexible gas sensors using polymer/metal‑oxide composites and lightweight sensor fabrics for real‑time environmental monitoring.

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  ISSUE 2

  Vol. 2 No. 1 (2025)

  This issue explores ionic‑liquid‑enhanced materials for neuromorphic and sensing applications. Articles describe solvent‑free fabrication of ionic‑liquid–geopolymer synapses for neuromorphic hardware, ionic‑liquid‑functionalised geopolymer micro‑systems for in‑memory processing and ceramic composites enabling low‑voltage synaptic devices. Several papers develop E‑jet‑printed conductive MOFs on textiles for charge transport and NOx sensing, propose humidity‑resilient sensors, explore hybrid IL‑MOF composites for multi‑analyte detection and scale fabrication through roll‑to‑roll printing.

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  ISSUE 1

  Vol. 1 No. 1 (2025)

  Papers in this issue integrate optimisation and game‑theoretic approaches for construction and IoT. They use game theory with optimisation to resolve conflicts among construction stakeholders, model adaptive resource management through behavioural insights and computational agents, employ Pareto‑based multi‑objective optimisation for resource allocation in large projects and combine deep learning with meta‑heuristic algorithms to enhance IoT security and energy efficiency.

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  ISSUE 4

  Vol. 3 No. 1 (2024)

  This issue examines strategic pricing. One paper develops a demand‑sensitive dynamic pricing framework using game theory for revenue optimisation, while the other uses blockchain to store dynamic pricing data and enforce fair and secure pricing via smart contracts.

   

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  ISSUE 3

  Vol. 2 No. 1 (2024)

  This issue centres on computational models for pricing and optimisation. It studies machine‑learning‑based competitor analysis for dynamic pricing and examines how dynamic pricing affects consumer purchase decisions via agent‑based modelling. Additional articles explore dynamic pricing combined with resource optimisation in construction, optimisation of analytical methods for process design and quality control, hybrid genetic algorithm and particle‑swarm optimisation for facility layout design and reinforcement‑learning/game‑theory frameworks for supply‑chain optimisation.

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  ISSUE 2

  Vol. 1 No. 2 (2024)

  The second issue of 2024 focuses on AI applications in project management and pricing. A paper reviews how artificial intelligence enhances agile project management through predictive analytics and resource optimisation. Others propose a machine‑learning and real‑time data‑analytics framework for proactive risk management, integrate sentiment analysis with dynamic pricing to maximise product profitability, design innovative pricing mechanisms using predictive modelling and real‑time adjustments and optimise pricing using causal inference combined with machine learning.

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  ISSUE 1

  Vol. 1 No. 1 (2024)

  This issue pairs sustainable project management with advances in semantic enrichment. One study applies AI to waste‑management projects, improving resource allocation and risk prediction in environmental initiatives. The remaining papers examine semantic enrichment: dynamic topic drift and influence modelling using a citation‑graph Hawkes process, self‑supervised contrastive embeddings for contextual alignment and entity linking and probabilistic calibration with risk‑sensitive inference to handle domain shifts.

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  ISSUE 1

  Vol. 1 No. 1 (2023)

  The inaugural issue introduces core themes in construction management and semantic enrichment. It proposes blockchain frameworks to increase transparency and efficiency in construction project management and discusses advanced optimisation techniques (linear programming, genetic algorithms and simulation) to improve resource allocation and scheduling. Two further papers lay a roadmap for trustworthy semantic enrichment with calibrated probabilities, active learning and human‑in‑the‑loop operations and develop edge‑ready semantic enrichment pipelines using quantization, pruning and knowledge‑distillation techniques to run on constrained devices.