Cultural Heritage Building and AI: Opportunities and Challenges (CHBAI)


Vocaturo Eugenio Vocaturo

Eugenio Vocaturo

Nanotec, National Research Council, Italy

Ruga Tommaso Ruga

Tommaso Ruga

University of Calabria, Italy

Zumpano Ester Zumpano

Ester Zumpano

University of Calabria, Italy

Rani Geeta Rani

Geeta Rani

Manipal University Jaipur, India

Singh Dhaka Vijaypal Singh Dhaka

Vijaypal Singh Dhaka

Manipal University Jaipur, India


The application of Artificial Intelligence (AI) to cultural heritage buildings is playing an increasingly significant role in supporting promotion and research activities. The spread of the pandemic has accelerated the use of Information and Communication Technologies (ICT) to promote and disseminate arts and cultural heritage.

The advent of digital technologies has paved the way for the application of AI for the development of new measurement and monitoring systems for the study, conservation, and accessibility of cultural heritage. This has improved our understanding of the past and the ability to preserve and transmit it to new generations, bridging the gap between heritage and the public and allowing heritage to play a role as a driver of cultural and social progress.

The cultural heritage sector utilizes measurements to address various issues related to conservation, accessibility, analysis, and awareness within a multidisciplinary context. This includes the reorganization of museums as building environment to make the experience more participative, the use of measurements, analytical methods and artificial intelligence techniques for the study and conservation of cultural assets, as well as the consideration of environmental impacts and risks, including climate change.

CHBAI aims to foster collaboration among researchers from various disciplines, presenting and exchanging ideas and progress related to the use of Big Data, Internet of Things (IoT), Social Media, and Artificial Intelligence in the field of management, conservation, and fruition of cultural heritage. The goal is to engage professionals in the information and technology management sector, discussing innovative technologies and end-to-end solutions to address challenges in the field of interest.

CHBAI will encourage discussions on ethical aspects and sustainability issues in the management, delivery, and conservation of cultural heritage. It will focus on engaging diverse perspectives and communities involved in various capacities in the conservation of cultural heritage.


Topics of interest include, but are not limited to:

  • Intelligent Measurement systems for the Management of CH Building: Implementing intelligent measurement systems for the efficient management of cultural heritage building resources.
  • Measurements for Cultural Landscapes and Building Tourism: Exploring the impact of cultural landscapes on building tourism, emphasizing architectural heritage.
  • Measurements for Acquisition, Conservation, and Restoration of Heritage Buildings: Measurement methods and strategies and technologies for acquiring, conserving, and restoring cultural heritage buildings.
  • Visualization Techniques and Extended Reality for Heritage Buildings: Use of advanced visualization methods and extended reality technologies to showcase and experience heritage buildings.
  • Multimedia and Multilingual Data Management for Heritage Buildings: Management of diverse multimedia and multilingual data related specifically to heritage buildings.
  • Measurements for Gamification and Storytelling in Heritage Building: measurements for integrating gamification and storytelling elements to enhance engagement with cultural heritage buildings.
  • Museum and Exhibition Applications for Heritage Buildings: Technological applications for improving museum and exhibition experiences focused on heritage buildings.
  • Libraries and Archives in Heritage Building: Utilization of libraries and archives specifically for the preservation and dissemination of cultural heritage buildings.
  • Preservation and Long-Term Accessibility of Heritage Buildings: Methods for preserving cultural heritage buildings and ensuring their long-term accessibility.
  • Tools for Education, Documentation, and Training in Heritage Buildings: Development of tools for educational purposes, documentation, and training specific to heritage buildings.
  • Learning and Reasoning on Heritage Building Data: Application of machine learning and reasoning techniques to analyze data related to cultural heritage buildings.
  • DRM and Legal Issues in Heritage Buildings: Consideration of digital rights management and legal aspects in handling data and content related to heritage buildings.
  • Societal, Professional, and Ethical Guidelines for Heritage Building Management: Discussion on societal, professional, and ethical guidelines in the management of cultural heritage buildings.
  • Intangible Heritage Representation and Processing in Buildings: Methods for representing and processing intangible aspects of cultural heritage within the context of heritage buildings.
  • Cultural Heritage Ontologies and Vocabularies for Buildings: Development and use of ontologies and vocabularies specific to the cultural heritage associated with buildings.
  • Linked Data and Knowledge Graphs for Heritage Buildings: Utilization of linked data and knowledge graphs to enhance information related to cultural heritage buildings.
  • Language Technologies for Cultural Heritage Buildings: Integration of language technologies for the analysis and interpretation of content specific to heritage buildings.
  • Semantic Social Networks in Heritage Building Data: Application of semantic social networks to understand relationships within data related to cultural heritage buildings.
  • Document Processing for Heritage Buildings: Techniques for processing and managing documents specifically related to cultural heritage buildings.
  • Accessibility and Inclusion in Heritage Buildings: Strategies to ensure accessibility and inclusion in initiatives related to cultural heritage buildings.
  • Mining and Indexing of Heritage Building Contents: Data mining and indexing methods for efficiently managing vast amounts of content specifically related to heritage buildings.
  • Workflow Management in Cultural Heritage Buildings: Efficient organization and management of workflows specific to cultural heritage building processes.


Eugenio Vocaturo, received a Laurea Degree in Management Engineering, a Master Degree in Design and Development of Web and Mobile Applications and a PhD Degree in Information and Communication Technologies at the University of Calabria, Italy. He also received a Master Degree in Industrial Process Management and a Master Degree in Finance issued by SDA Bocconi. He has decades of experience as company director, being head of editorial production of important IT publishing houses and co-founding partner of the start-up BigTech. He is currently researcher at CNR-Nanotec and contract professor of Informatics, Process Mining, Data Mining and Information Systems and DataBase at University of Calabria. His current research interests include Deep and Machine Learning, Optimization, Health Informatics, Process Mining, Cultural Heritage. He is member of Topical Advisory Panel and Editor Reviewer of several international journals and permanent member of the program committee of international conferences, being author of several papers in international journals, conferences and books. He is a member of SIBIM (Italian Scientific Society of Biomedical Informatics) and of HL7 Italy (formed in 2003 as part of HL7 International), company responsible for the localization of health standards aiming at promoting the modernization of Italian health IT.

Tommaso Ruga, graduated in Computer Engineering in 2023 at the University of Calabria with a thesis titled “An ensemble model for lesion diagnosis based on Machine Learning techniques and Deep Learning”. He is a Ph.D. Student in Information and Communication Technologies at the Department of Computer Engineering, Modeling, Electronics, and Systems Engineering (DIMES) of the University of Calabria, Italy. His research interest include artificial intelligence, knowledge representation, health Informatics. His main focus is on AI techniques and tools for health, personalized medicine and wellbeing.

Ester Zumpano, is an associate professor of Computer Engineering at the Department of Computer Engineering, Modeling, Electronics and Systems Engineering, University of Calabria (DIMES). She received a Phd in Computer Science from the University of Calabria in 2003. Her areas of research include health information systems, data integration, logic programming, view updating, distributed systems, artificial Intelligence, database management. She is member of the Scientific Board of the Ph.D. Course in Information and Communication Technologies, University of Calabria, Italy. She has many international collaborations. She is associate member of CNR Nanotec. She is associate member of National Research Council (CNR). She is a founding member of the ITACA S.r.l. spin-off. She is member of the Steering Committee of the European Conference on Advances in Databases and Information Systems (ADBIS) Conference (from 2007 until now). Member of the Editorial Board of the Journal ”Intelligent Information Systems”; Member of the Editorial Board of the Journal “Big Data and Cognitive Computing”. Guest Editor of the Intelligent Systems with Applications’ (ISWA) Journal - Special Issue of ``Artificial Intelligence for Clinical Decision Support", 2022; Editor of the Journal of Logic and Computation - Special Issue of the 35th edition of the Italian Conference on Computational Logic (CILC 2020), 2021; Editor of the Information Systems Journal - Special issue ``Managing, Mining and Learning in the Legal Data Domain", 2020; Lead Guest Editor of the Special Issue ``Mathematical Theories in the Era of Big Data" for the Mathematical Problems in Engineering journal – Hindawi; Co-guest Editor of the special issue ``Hybrid machine learning techniques in bioinformatics" Encyclopedia of Bioscience; Guest Editor of the Special Issue 'Application of Machine Learning Methods in Bio-medical Informatics' for the Mathematical Biosciences and Engineering journal. She has been program chair of the 22nd International Database Engineering & Applications Symposium -IDEAS 2018; program chair She was/is a member of the program committee of many conferences, among which IJCAI, ECAI, AAAI. She participated in international, national and local research/technical projects. She has been member of judging commissions of the final exam for PhD students. She teaches undergraduate, graduate and PhD level courses in Computer Science at the University of Calabria since 2002.

Geeta Rani, received her PhD degree in Computer Engineering from the University of Delhi, Delhi, India in 2017. She has teaching experience of more than 15 years. Currently, she is working as an Associate Professor at Manipal University Jaipur, India. She is the chief editor of two books, has published more than 50 research articles, and more than 15 patents. She has acquired more than 17 copyrights on the software applications and inventions. Her research interests include machine learning, artificial intelligence, image processing and data analytics. Dr. Geeta was a recipient of the ‘Women Scientist-IPR Fellowship’ in 2018 from the Department of Science and Technology, India.

Vijaypal Singh Dhaka, received his PhD degree in Computer Engineering from the Bhimrao Ambedkar University, Agra, India, in 2010. He has more than 20 years of industry and academic experience at various organizations of repute. Currently, he is working as Professor, and Director at School of Computer and Communication Engineering, Manipal University Jaipur, India. He has more than 80 publications in Journals of great repute in his name and guided 11 research scholars to earn PhD. He has published more than 12 patents and acquired more than 15 copyrights on the software applications and inventions. Dr. Dhaka received “World Eminence Awards 2017" for Leading Research Contribution in ICT for the Year 2016, at WS-4 in London on 15th Feb 2017 and conferences of repute. His research area is artificial intelligence and computer vision.