Search Results (23)

The rapid advancement of digital technologies has reshaped tourism practices worldwide, positioning smart tourism as a key approach for enhancing user experience. Previous studies have either focused on conceptual discussions of smart tourism principles or examined isolated technological applications; limited research has systematically linked theoretical experiential dimensions with the actual tools and systems implemented in heritage contexts. In response to this gap, a structured review of Scopus-indexed studies published between 2015 and the present was conducted to examine smart tourism applications in historical urban areas, identifying the evolution of the term smart tourism, recurring trends, technological interventions, and operational strategies applied in historical urban destinations. Using an inductive comparative qualitative approach, a selected sample of archival studies was analyzed, classifying studies into two distinct yet potentially complementary research families: a philosophical stream and a practical implementation stream. The selected studies are analyzed through a dual lens: (1) Theoretical dimensions and themes discussed in conceptual literature, and (2) Practical tools and techniques applied in empirical case studies. The core contribution of this research is the critical perspective of these efforts and the bridging of these two domains through the Integrated Smart Tourism Transformation Framework (ISTTF). The findings contribute to both theory and practice by offering a framework for policymakers, designers, and heritage managers seeking to implement smart tourism solutions that enhance user experience while preserving cultural integrity. Full article

Metallic cultural heritage artifacts are highly susceptible to multi-factor electrochemical degradation, driven by chloride ions, humidity, acidic deposition, and heterogeneous material interfaces. Traditional conservation materials, including organic and inorganic coatings and corrosion inhibitors, often exhibit limited interfacial compatibility, poor long-term stability, and insufficient multifunctionality. Recent advances in protective materials—including nano-enhanced coatings, self-healing systems, smart-responsive polymers, green biodegradable formulations, and metal–organic framework (MOF)-based composites—offer multifunctional, long-lasting, and minimally invasive solutions. These materials enhance corrosion inhibition, barrier performance, structural reinforcement, and environmental responsiveness, while enabling in situ sensing, reversible application, and ethical deployment. Laboratory evaluation, accelerated aging tests, and field verification demonstrate their efficacy in preserving artifact integrity and aesthetics. This review systematically discusses degradation mechanisms, limitations of traditional materials, and the mechanisms, applications, and future perspectives of novel functional coatings, providing a roadmap for scientifically optimized and ethically responsible conservation of metallic heritage. Full article

We explored the application of spatial information technology in the assessment and optimization of cultural heritage resources within traditional settlements in Meizhou City, a core area of Hakka culture in China. By integrating methods such as geographic information systems and Kernel density estimation, it systematically evaluates the spatial distribution and socioeconomic conditions of these settlements. A multi-criteria evaluation model is constructed to quantify resource endowment across cultural, historical, and ecological dimensions, with particular emphasis on key factors influencing conservation effectiveness, such as infrastructure and economic vitality. Combining field investigations and literature review, we propose adaptive reuse strategies and policy recommendations to enhance settlement resilience and balance cultural preservation with regional development. Their expected outcomes include the engineering of a multidimensional geographic database for traditional settlements, the establishment of a spatial decision-support framework for heritage infrastructure conservation, and the development of systematic optimization protocols integrated with China’s rural revitalization technical policies. These results provide a computational and methodological foundation for interdisciplinary research in sustainable cultural heritage management and smart rural engineering. Full article

The digitisation of urban governance requires a context-sensitive method that balances operational efficiency, data security and transparency. This study proposes a context-sensitive QR code system as a conceptual framework for smart urban governance and real estate visualisation in Saudi Arabia, aligned with the strategic objectives of Vision 2030. Unlike traditional static QR code applications, the proposed system acts as a smart urban interface dynamically linking physical buildings to structured digital records and delivering role-specific information through a single scan. This system enables municipal authorities to retrieve compliance and regulatory data and allows emergency response teams to access real-time occupancy data with geographic coordinates. The proposed system enables visitors to explore curated heritage and site-based information, with each interface subject to policy-defined access rules. The proposed QR code system is evaluated by using a scenario-based computational simulation across three representative Saudi cities (Riyadh, Jeddah, and Dammam), and the results show that it significantly reduces service response time compared to manual processes while maintaining data integrity through role-based dynamic filtering. The proposed system enhances administrative efficiency and supports heritage preservation in sensitive areas such as the Al-Balad district in Jeddah city. By integrating governance, visualisation, and cultural sustainability within a simple, scalable and interactive model, the study provides an important framework for emerging smart cities in Saudi Arabia. Full article

The application prospects of photorealistic 3D reconstruction are broad in smart cities, cultural heritage preservation, and related domains. However, existing methods face persistent challenges in balancing reconstruction accuracy, computational efficiency, and robustness, particularly in complex scenes characterized by reflective surfaces, vegetation, sparse viewpoints, or large-scale structures. In this study, an enhanced 3D Gaussian Splatting (3DGS) framework that integrates three key innovations is proposed: (i) a depth-aware regularization module that leverages metric depth priors from the pre-trained Depth-Anything V2 model, enabling geometrically informed optimization through a dynamically weighted hybrid loss; (ii) a gradient-driven adaptive densification mechanism that triggers Gaussian adjustments based on local gradient saliency, reducing redundant computation; and (iii) a neighborhood density-based floating artifact detection method that filters outliers using spatial distribution and opacity thresholds. Extensive evaluations are conducted across four diverse datasets—ranging from architectures, urban scenes, natural landscapes with water bodies, and long-range linear infrastructures. Our method achieves state-of-the-art performance in both reconstruction quality and efficiency, attaining a PSNR of 34.15 dB and SSIM of 0.9382 on medium-sized scenes, with real-time rendering speeds exceeding 170 FPS at a resolution of 1600 × 900. It demonstrates superior generalization on challenging materials such as water and foliage, while exhibiting reduced overfitting compared to baseline approaches. Ablation studies confirm the critical contributions of depth regularization and gradient-sensitive adaptation, with the latter improving training efficiency by 38% over depth supervision alone. Furthermore, we analyze the impact of input resolution and depth model selection, revealing non-trivial trade-offs between quantitative metrics and visual fidelity. While aggressive downsampling inflates PSNR and SSIM, it leads to loss of high-frequency detail; we identify 1/4–1/2 resolution scaling as an optimal balance for practical deployment. Among depth models, Vitb achieves the best reconstruction stability. Despite these advances, memory consumption remains a challenge in large-scale scenarios. Future work will focus on lightweight model design, efficient point cloud preprocessing, and dynamic memory management to enhance scalability for industrial applications. Full article

As urban boundaries continue to expand and core city areas undergo optimization, megacities such as New York, London, Beijing, Shanghai, and Guangzhou exert a siphon effect on surrounding regions, intensifying population concentration and land demand. However, the imperative for coordinated production-living-ecological space development has placed limits on uncontrolled urban sprawl, highlighting the need for connotative, high-quality urban growth. Recent initiatives in urban village renewal and regeneration aim to enhance land-use efficiency but face persistent challenges—including preserving indigenous settlements and cultural heritage, while creating livable and friendly communities within high-density contexts. Utilizing a mixed-methods approach—combining bibliometrics analysis, questionnaire surveys, and enterprise interviews—this research investigates core challenges to urban renewal. Results indicate that multi-party collaborative governance integrating policy innovation, cultural preservation, human-centered planning, smart technologies, and sustainable development is essential for advancing “people-industry-city integration” in renewal models. Full article

Preservation of Cultural Heritage (CH) demands precise and comprehensive information representation to document, analyse, and manage assets effectively. While Building Information Modelling (BIM) facilitates as-is state documentation, challenges in semantic interoperability of complex cultural data often limit its potential in heritage contexts. This study investigates the integration of BIM tools with the buildingSMART Data Dictionary (bSDD) platform to enhance semantic interoperability for heritage assets. Using a proof-of-concept approach, the research focuses on a historic tenement house in Tarnów, Poland, modelled with the IFC schema standard and enriched with the MIDAS heritage classification system. The methodology includes transforming the classification system into bSDD data dictionary, publishing thesauri for components, materials, and monument types, and semantic enrichment of the model using Bonsai (formerly BlenderBIM) plugin for Blender. Results demonstrate improved consistency, accuracy, and usability of BIM data for heritage preservation. The integration ensures detailed documentation and facilitates interoperability across platforms, addressing preservation challenges with enriched narratives of cultural significance. This method supports future predictive models for heritage asset conservation, emphasizing the importance of data quality and interoperability in safeguarding shared cultural heritage for future generations. Full article

Cultural heritage tourism is a vital part of Malaysia’s tourism sector, attracting visitors to iconic UNESCO sites like George Town and Melaka. However, these heritage sites face growing challenges from overcrowding and environmental degradation, which accelerate the deterioration of historic architecture and cultural artifacts. Preservation efforts often require site closures, which negatively impact tourist experiences and satisfaction. Thus, augmented reality (AR) offers a solution by supporting heritage management and preservation, allowing visitors to engage with virtual representations via mobile AR apps, thereby enhancing visitor engagement and travel experience. Despite global adoption, mobile AR apps often suffer from low user retention, with many users abandoning them shortly after downloading them. Understanding what drives continued usage is crucial for successful AR implementation. This study integrates the expectation confirmation model (ECM) and the unified theory of acceptance and use of technology 2 (UTAUT2) to examine the determinants affecting user’s experiential satisfaction and continued usage intention of mobile AR apps. An online survey of 450 domestic tourists in George Town and Melaka was conducted. Data analysis using structural equation modeling with SmartPLS 4.0 revealed that the integrated model offers a stronger predictive power and significantly outperforms ECM and UTAUT2 individually. The findings contribute valuable insights for researchers, app developers, tourism stakeholders, and policymakers. Full article

Automated landmark recognition represents a cornerstone technology for advancing smart tourism systems, cultural heritage documentation, and enhanced visitor experiences. Contemporary deep learning methodologies have substantially transformed the accuracy and computational efficiency of destination classification tasks. Addressing critical gaps in existing approaches, we introduce an enhanced Samarkand_v2 dataset encompassing twelve distinct historical landmark categories with comprehensive environmental variability. Our methodology incorporates a systematic multi-threshold pixel intensification strategy, applying graduated enhancement transformations at intensity levels of 100, 150, and 225 to accentuate diverse architectural characteristics spanning from fine-grained textural elements to prominent reflective components. Four independent YOLO11 architectures were trained using original imagery alongside systematically enhanced variants, with optimal epoch preservation based on validation performance criteria. A key innovation lies in our intelligent selective ensemble mechanism that conducts exhaustive evaluation of model combinations, identifying optimal configurations through data-driven selection rather than conventional uniform weighting schemes. Experimental validation demonstrates substantial performance gains over established baseline architectures and traditional ensemble approaches, achieving exceptional metrics: 99.24% accuracy, 99.36% precision, 99.40% recall, and 99.36% F1-score. Rigorous statistical analysis via paired t-tests validates the significance of enhancement strategies, particularly demonstrating effectiveness of lower-threshold transformations in capturing architectural nuances. The framework exhibits remarkable resilience across challenging conditions including illumination variations, structural occlusions, and inter-class architectural similarities. These achievements establish the methodology’s substantial potential for practical smart tourism deployment, automated heritage preservation initiatives, and real-time mobile landmark recognition systems, contributing significantly to the advancement of intelligent tourism technologies. Full article

This study examines the role of cultural heritage sites as facilitators of place making within the evolving paradigm of smart city development. As cities worldwide adopt data-driven models of governance, integrating cultural identity and heritage becomes increasingly critical. This research addresses the conceptual and practical gap in understanding how heritage can support inclusive, sustainable, and meaningful urban transformation in smart city contexts. To do so, it selects Geelong in Australia as a case study. The study then employs a qualitative methodology drawing on semi-structured interviews with experts and professionals across urban planning, architecture, sustainability, and heritage management. Thematic analysis derived five key themes: heritage as an identity anchor, digital technologies enhancing cultural narratives, community engagement, adaptive reuse, and economic-policy integration. Findings highlight that heritage sites are dynamic assets that foster community identity, historical continuity, and digital storytelling. Digital tools enhance the visibility and accessibility of heritage, while adaptive reuse strategies align cultural preservation with environmental sustainability and economic growth. The resulting conceptual and assessment framework positions heritage both as a cultural and functional urban asset, offering actionable insights for planners, policymakers, and designers aiming to create smart cities that are not only technologically advanced but also socially inclusive and culturally grounded. Full article

In the context of sustainable architecture, buildings are no longer isolated entities but are integral components of a broader built environment that shapes and responds to human life. As part of this evolving architectural landscape, immersive digital cultural heritage spaces—such as virtual museums—are emerging as dynamic environments that contribute not only to cultural preservation but also to human well-being. This study examines how multisensory spatial design in virtual heritage environments can meet the physical, psychological, and emotional needs of users, aligning with the principles of smart, responsive architecture. A total of 325 participants experienced three immersive VR scenarios integrating different sensory inputs: visual–auditory, visual–auditory–tactile, and visual–auditory–olfactory. Through factor analyses, a three-dimensional model of user experience was identified, encompassing immersion, cultural engagement, and personalization. Structural equation modeling revealed that informational clarity significantly enhanced immersion (β = 0.617, p < 0.001), while emotional resonance was central to personalization (β = 0.571, p < 0.001). Moreover, ANOVA results indicated significant experiential differences among sensory conditions (F = 4.324, p = 0.014), with the visual–auditory modality receiving the highest user ratings. These findings demonstrate how digital cultural spaces—when designed with human sensory systems in mind—can foster emotionally rich, informative, and sustainable environments. By extending the role of architecture into the digital domain, this study offers insight into how technology, when guided by human-centered design, can create smart environments that support both ecological responsibility and enhanced human experience. Full article

Tourist destination classification is pivotal for enhancing the travel experience, supporting cultural heritage preservation, and enabling smart tourism services. With recent advancements in artificial intelligence, deep learning-based systems have significantly improved the accuracy and efficiency of landmark recognition. To address the limitations of existing datasets, we developed the Samarkand dataset, containing diverse images of historical landmarks captured under varying environmental conditions. Additionally, we created enhanced image variants by squaring pixel values greater than 225 to emphasize high-intensity architectural features, improving the model’s ability to recognize subtle visual patterns. Using these datasets, we trained two parallel YOLO11 models on original and enhanced images, respectively. Each model was independently trained and validated, preserving only the best-performing epoch for final inference. We then ensembled the models by averaging the model outputs from the best checkpoints to leverage their complementary strengths. Our proposed approach outperforms conventional single-model baselines, achieving an accuracy of 99.07%, precision of 99.15%, recall of 99.21%, and F1-score of 99.14%, particularly excelling in challenging scenarios involving poor lighting or occlusions. The model’s robustness and high performance underscore its practical value for smart tourism systems. Future work will explore broader geographic datasets and real-time deployment on mobile platforms. Full article

Traditional fermented foods are appreciated worldwide for their cultural significance and health-promoting properties. However, traditional fermentation production suffers from many obstacles such as microbial variability, varying quality, and lack of scalability. The implementation of smart fermentation technologies, including biosensors, the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), hold the key to the optimization of microbial process control, enhance product consistency, and improve production efficiency. This review summarizes modern developments in real-time microbial monitoring, IoT, AI, and ML tailored to traditional fermented foods. Despite significant technical advancements, challenges related to high costs, the absence of standardized frameworks, and access restrictions for small producers remain substantial limitations. This review proposed a future direction prioritizing modular, scalable solutions, open-source innovation, and environmental sustainability. In alignment with Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure), smart fermentation technologies advance sustainable industry through innovation and serve as a critical bridge between traditional craftsmanship and Industry 4.0, fostering inclusive development while preserving microbial biodiversity and cultural heritage. Full article

This study investigates the integration of digital technologies in leading European museums to enhance heritage interpretation, increase visitor engagement, and contribute to sustainable tourism. As museums increasingly adapt to the digital age, they seek innovative solutions to enrich the visitor experience while promoting sustainability. This research uses a content analysis approach to examine the strategies employed by four prominent museums—the Louvre, the British Museum, the Prado Museum, and the Rijksmuseum. Key digital initiatives, including virtual tours, educational apps, and online collections, are identified as central components of their efforts to improve accessibility, facilitate interactive learning, and attract a wider global audience. Our findings highlight that these digital innovations not only provide visitors with more engaging and informative experiences but also align with sustainability objectives such as reducing carbon footprints and supporting cultural preservation. This study concludes that by leveraging smart technologies, museums are evolving into dynamic, globally connected institutions that strike a balance between conservation and visitor engagement, thereby fostering a more sustainable and inclusive approach to heritage tourism. Full article

Historic Cairo, recognized as a UNESCO World Heritage Site in 1979, is renowned for its rich Islamic architecture, including sabils, which have played a crucial role in the urban fabric of this arid region. This study focuses on the oldest surviving Ottoman sabil in Cairo—the Sabil and Kutab of Khusru Pasha—as a case study for digital heritage preservation using advanced documentation technologies. We propose a flexible, dynamic documentation workflow based on the heritage digital twin (HDT) framework, which integrates both physical and digital-native processes. Through a hybrid methodology that combines 3D laser scanning, photogrammetry, and building information modeling (BIM), this study aims to transition from static heritage record-keeping to an interactive, semantically structured digital representation. This approach enhances the efficiency and accuracy of documentation, supports long-term conservation, and facilitates immersive public engagement. Quantitative data, including scan resolution and processing time, are used to assess the effectiveness of the adopted workflow. The digital twin created from this case study offers a replicable model for safeguarding similar mid-scale heritage assets across Islamic Cairo. Furthermore, integrating HDTs into virtual tourism frameworks creates new possibilities for cultural accessibility, education, and sustainable tourism development. By illustrating how historical buildings like the Khusru Pasha Sabil can be virtually preserved, monitored, and promoted, this study highlights the transformative potential of digital twin technology in heritage conservation. It contributes to the evolving discourse on smart documentation and management strategies, aligning with global sustainability goals and digital heritage preservation initiatives. Full article