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Call for Papers: Architecture Journal Special Issue

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Call for Papers: Architecture Journal Special Issue

Next-Generation Building Performance and Optimization

Dear Colleagues,

The Architecture, Engineering, and Construction (AEC) industry is undergoing rapid transformation driven by artificial intelligence (AI), computational design, and digital twin technologies. As the demand for high-performance, low-carbon buildings grows, research focus has shifted from isolated efficiency measures to integrated frameworks linking early-stage design with long-term operation. This Special Issue invites contributions that advance the discourse on next-generation building performance and optimization, exploring how computational intelligence, sustainable strategies, and smart systems can reshape the building lifecycle. By combining theoretical inquiry with applied research, this Special Issue seeks to illuminate how emerging technologies are redefining design workflows and operational performance, effectively bridging pre-construction simulations with post-construction realities.

The aim of this Special Issue is to advance both theoretical and practical knowledge on the ways in which emerging technologies can be embedded into the design and operation of buildings. Submissions may highlight methodological innovations, case studies of energy-efficient and low-carbon strategies, and cross-disciplinary collaborations connecting architecture, engineering, computer science, and environmental studies. By positioning building performance within the wider discourse of sustainability and cyber–physical systems, this Special Issue will provide a platform for envisioning next-generation approaches in which design intelligence and operational feedback converge to foster a more resilient and sustainable built environment. We welcome submissions that investigate, but are not limited to, the following thematic areas:

  • Integration of AI-driven generative designs for massing, orientation, and layout to improve daylighting, ventilation, thermal comfort, and carbon reduction;
  • Predictive modeling and energy simulation in early-stage design;
  • Use of AI and computer vision for occupancy analysis and behavioral insights;
  • Adaptive building automation for HVAC, lighting, and environmental control;
  • Machine learning applications for predictive maintenance and resource efficiency;
  • Digital twins and IoT sensor networks for real-time monitoring, feedback, and optimization;
  • Development of intelligent, data-driven, and responsive building systems;
  • Sustainable strategies at the urban scale;
  • Performance-based design approaches;
  • Building Information Modeling (BIM) for integrated workflows;
  • Building energy modeling for efficiency and carbon reduction.

Prof. Ming Tang
Guest Editor

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. Architecture is an international peer-reviewed open access quarterly 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 1200 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

  • building performance
  • energy simulation
  • digital twins
  • IoT data integration
  • green building
  • smart buildings
  • sustainable design
  • performance-based design
  • post-occupancy evaluation
  • artificial intelligence
  • data-driven prediction
  • generative design
  • computational design
  • parametric modeling
  • machine learning for built environments
  • predictive maintenance
  • real-time monitoring and control
  • human-centered design
  • climate-responsive architecture
  • net-zero energy buildings
  • resilient and adaptive design
  • lifecycle assessment (LCA)

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal’s social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI’s Special Issue policies can be found here.

Published Papers

This special issue is now open for submission.

paper on AI, XR, Metaverse, Digital Twins

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Metaverse and Digital Twins in the Age of AI and Extended Reality

Tang, Ming, Mikhail Nikolaenko, Ahmad Alrefai, and Aayush Kumar. 2025. “Metaverse and Digital Twins in the Age of AI and Extended Reality” Architecture 5, no. 2: 36. https://doi.org/10.3390/architecture5020036

 

This paper explores the evolving relationship between Digital Twins (DT) and the Metaverse, two foundational yet often conflated digital paradigms in digital architecture. While DTs function as mirrored models of real-world systems—integrating IoT, BIM, and real-time analytics to support decision-making—Metaverses are typically fictional, immersive, multi-user environments shaped by social, cultural, and speculative narratives. Through several research projects, the team investigate the divergence between DTs and Metaverses through the lens of their purpose, data structure, immersion, and interactivity, while highlighting areas of convergence driven by emerging technologies in Artificial Intelligence (AI) and Extended Reality (XR).This study aims to investigate the convergence of DTs and the Metaverse in digital architecture, examining how emerging technologies—such as AI, XR, and Large Language Models (LLMs)—are blurring their traditional boundaries. By analyzing their divergent purposes, data structures, and interactivity modes, as well as hybrid applications (e.g., data-integrated virtual environments and AI-driven collaboration), this study seeks to define the opportunities and challenges of this integration for architectural design, decision-making, and immersive user experiences. Our research spans multiple projects utilizing XR and AI to develop DT and the Metaverse. The team assess the capabilities of AI in DT environments, such as reality capture and smart building management. Concurrently, the team evaluates metaverse platforms for online collaboration and architectural education, focusing on features facilitating multi-user engagement. The paper presents evaluations of various virtual environment development pipelines, comparing traditional BIM+IoT workflows with novel approaches such as Gaussian Splatting and generative AI for content creation. The team further explores the integration of Large Language Models (LLMs) in both domains, such as virtual agents or LLM-powered Non-Player-Controlled Characters (NPC), enabling autonomous interaction and enhancing user engagement within spatial environments. Finally, the paper argues that DTs and Metaverse’s once-distinct boundaries are becoming increasingly porous. Hybrid digital spaces—such as virtual buildings with data-integrated twins and immersive, social metaverses—demonstrate this convergence. As digital environments mature, architects are uniquely positioned to shape these dual-purpose ecosystems, leveraging AI, XR, and spatial computing to fuse data-driven models with immersive and user-centered experiences.
 
Keywords:  metaverse; digital twin; extended reality; AI

paper in JMS & NAMRC

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Anuj Gautam, Manish Raj Aryal, Sourabh Deshpande, Shailesh Padalkar, Mikhail Nikolaenko, Ming Tang, Sam Anand, IIoT-enabled digital twin for legacy and smart factory machines with LLM integration, Journal of Manufacturing Systems, Volume 80, 2025, Pages 511-523, ISSN 0278-6125

The paper is also published in the NAMRC 2025 conference.

Anuj Gautam , Manish Raj Aryal, Sourabh Deshpande, Shailesh Padalkar, Mikhail Nikolaenko, Ming Tang, Sam Anand. IIoT-enabled Digital Twin for legacy and smart factory machines with LLM integration. 53rd SME North American Manufacturing Research Conference (NAMRC), Clemson Univ. 06/2025.

 

Abstract

The recent advancement in Large Language Models (LLMs) has significantly transformed the field of natural data interpretation, translation, and user training. However, a notable gap exists when LLMs are tasked to assist with real-time context-sensitive machine data. The paper presents a multi-agent LLM framework capable of accessing and interpreting real-time and historical data through an Industrial Internet of Things (IIoT) platform for evidence-based inferences. The real-time data is acquired from several legacy machine artifacts (such as seven-segment displays, toggle switches, and knobs), smart machines (such as 3D printers), and building data (such as sound sensors and temperature measurement devices) through MTConnect data streaming protocol. Further, a multi-agent LLM framework that consists of four specialized agents – a supervisor agent, a machine-expertise agent, a data visualization agent, and a fault-diagnostic agent is developed for context-specific manufacturing tasks. This LLM framework is then integrated into a digital twin to visualize the unstructured data in real time. The paper also explores how LLM-based digital twins can serve as real time virtual experts through an avatar, minimizing reliance on traditional manuals or supervisor-based expertise. To demonstrate the functionality and effectiveness of this framework, we present a case study consisting of legacy machine artifacts and modern machines. The results highlight the practical application of LLM to assist and infer real-time machine data in a digital twin environment.

NCBDS conference

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Paper “Designing the Future of Retail: Cross-Disciplinary Collaboration in Industrial Design and Architecture Design” published at the 40th National Conference on Begining Design Students Conference proceedings.  North Carolina State University. Raleigh, NC. 2025.

Yong-Gyun Ghim, Ming Tang, University of Cincinnati

 

Abstract

The significance of design’s cross-disciplinary nature has increased alongside technological advancements as emerging technologies present new opportunities and challenges for complex socio-technical systems. Systems thinking has drawn attention to design as a holistic approach to tackling complex systems by examining the interrelationships between elements. This also necessitates cross-disciplinary collaboration to address the multifaceted nature of the problems comprehensively. These aspects of systems thinking further emphasize its importance in design education to help navigate the current era of technological innovation. The future of retail exemplifies this interconnected complexity in the context of emerging technologies because introducing them – such as robotics, artificial intelligence, and mixed reality – into retail environments requires a holistic consideration of the entire system, encompassing physical spaces, service processes, and human interactions.

This study examines a 15-week collaborative studio project between industrial design and architecture. By leveraging a systems thinking approach, the project facilitated cross-disciplinary collaboration to develop future retail concepts, enabling students to integrate their expertise and address the interconnectedness of artifacts, environments, and human interactions. Both disciplines followed a structured design process encompassing research, system design, space and robot design, visualization, and validation, while collaboration was organized around four key steps: planning, learning, prototyping, and communication. The project also involved collaboration with a supermarket chain, providing opportunities for onsite observations, employee interviews, and discussions with industry professionals. Students developed futuristic concepts for retail operations and customer experiences by leveraging the integration of mobile service robots, adaptive spaces, and mixed reality. Industrial design students focused on designing a product-service system of supermarket robots based on their redefinition of customer shopping experience and employee workflow, proposing an automated grocery order fulfillment system. Architecture students designed adaptive retail spaces that seamlessly blur the boundaries between physical and digital worlds, exploring how the Metaverse and mixed-reality interfaces can augment retail spaces and shopping experiences through dynamic, immersive interactions with digital avatars and robots. This cross-disciplinary collaboration resulted in holistic and integrative solutions for complex systems, presented through immersive VR experiences or animated scenarios.

This study’s contribution to design education is threefold. First, it proposes a systems thinking approach with cross-disciplinary collaboration for designing future retail experiences, demonstrating its effectiveness in addressing and designing complex socio-technical systems. Second, it offers insights into how industrial design and architecture can be integrated to create novel user experiences in digital transformation. Lastly, by examining the design and collaboration processes and reflecting on the opportunities and challenges, this study offers insights for its application to future studio courses. Given the increased complexity and dynamics between disciplines, thorough pre-planning and flexibility are critical for success.

Keywords:

Cross-disciplinary collaboration, Design education, Industrial design, Architecture, Future of retail

Project:  Future Service, Retail, Metaverse, and Robotics

 

paper on XR conference

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Two papers were presented and published at the 2024 International Conference on eXtended Reality. XR Salento 2024.

Tang, Ming, Mikhail Nikolaenko, Evv Boerwinkle, Samuel Obafisoye, Aayush Kumar, Mohsen Rezayat, Sven Lehmann, and Tamara Lorenz. “Evaluation of the Effectiveness of Traditional Training vs. Immersive Training: A Case Study of Building Safety & Emergency Training.” Paper presented at the International Conference on eXtended Reality (XR SALENTO 2024), Lecce, Italy, September 4-9, 2024. The paper is published in the Springer Link proceeding book. 

Virtual Reality (VR) has revolutionized training across healthcare, manufacturing, and service sectors by offering realistic simulations that enhance engagement and knowledge retention. However, assessments that allow for evaluation of the effectiveness of VR training are still sparse. Therefore, we examine VR’s effectiveness in emergency preparedness and building safety, comparing it to traditional training methods. The goal is to evaluate the impact of the unique opportunities VR enables on skill and knowledge development, using digital replicas of building layouts for immersive training experiences. To that end, the research evaluates VR training’s advantages and develops performance metrics by comparing virtual performance with actions in physical reality, using wearable tech for performance data collection and surveys for insights. Participants, split into VR and online groups, underwent a virtual fire drill to test emergency response skills. Findings indicate that VR training boosts urgency and realism perception despite similar knowledge and skill acquisition after more traditional lecture-style training. VR participants reported higher stress and greater effectiveness, highlighting VR’s immersive benefits. The study supports previous notions of VR’s potential in training while also emphasizing the need for careful consideration of its cognitive load and technological demands.

 

Tang, M., Nored, J., Anthony, M., Eschmann, J., Williams, J., Dunseath, L. (2024). VR-Based Empathy Experience for Nonprofessional Caregiver Training. In: De Paolis, L.T., Arpaia, P., Sacco, M. (eds) Extended Reality. XR Salento 2024. Lecture Notes in Computer Science, vol 15028. Springer, Cham. https://doi.org/10.1007/978-3-031-71704-8_28 

This paper presents the development of a virtual reality (VR) system designed to simulate various caregiver training scenarios, with the aim of fostering empathy by providing visual and emotional representations of the caregiver’s experience. The COVID-19 pandemic has increased the need for family members to assume caregiving roles, particularly for older adults who are at high risk for severe complications and death. This has led to a significant reduction in the availability of qualified home health workers. More than six million people aged 65 and older require long-term care, and two-thirds of these individuals receive all their care exclusively from family caregivers. Many caregivers are unprepared for the physical and emotional demands of caregiving, often exhibiting clinical signs of depression and higher stress levels.

The VR system, EVRTalk, developed by a multi-institutional team, addresses this gap by providing immersive training experiences. It incorporates theories of empathy and enables caregivers to switch roles with care recipients, navigating common scenarios such as medication management, hallucinations, incontinence, end-of-life conversations, and caregiver burnout. Research demonstrates that VR can enhance empathy, understanding, and communication skills among caregivers. The development process included creating believable virtual characters and interactive scenarios to foster empathy and improve caregiving practices. Initial evaluations using surveys showed positive feedback, indicating that VR training can reduce stress and anxiety for caregivers and improve care quality.

Future steps involve using biofeedback to measure physiological responses and further investigating the ethical implications of VR in caregiving training. The ultimate goal is to deploy VR training in homes, providing family caregivers with the tools and knowledge to manage caregiving responsibilities more effectively, thereby enhancing the quality of life for both caregivers and care recipients.