Parallel Museum Systems: Framework, Platform, Methods and Applications
LU Yue1,2, GUO Chao2, PAN Qing3, NI Qinghua4, LI Huabiao3, WANG Chunfa3, WANG Fei-Yue2
1. School of Control Science and Engineering, Shandong University, Jinan 250061; 2. The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190; 3. National Museum of China, Beijing 100006; 4. Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078
Abstract With the development of foundation models, blockchain and metaverse, museum construction in the new era faces the challenges of collection digitization, service integration and intelligent management. The parallel museum system is constructed with virtual-real interactions. Its framework, platform and methods are designed based on parallel systems and ACP theory to realize the intelligent construction and management of museums. The subsystems of the digital collection, scene engineering, multimodal human-computer interaction, the big model of the museum and digital asset management are utilized. The parallel museum system is built with the scenarios-engineering-based task construction, human-feedback-based knowledge enhancement model and decentralized-autonomous-organizations-based data resource management. The museum services of heritage research, heritage conservation, exhibition and management are utilized to improve the operation of typical museum tasks and scenarios. Finally, application scenarios and cases of parallel museum systems are introduced.
Corresponding Authors:
1. School of Control Science and Engineering, Shandong University, Jinan 250061; 2. The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190; 3. National Museum of China, Beijing 100006; 4. Faculty of Innovation Engineering, Macau University of Science and Technology, Macau 999078
About author:: LU Yue, Ph.D. His research interests include machine learning, few-shot learning and robotic systems. GUO Chao, Ph.D., assistant professor. His research interests include machine lear-ning, reinforcement learning, artificial intelligence for art and intelligent robotic system. PAN Qing, Ph.D., professor. Her research interests include exhibition curating, international exchanges, and the application of science and te-chnology in museum exhibitions. NI Qinghua, Ph.D. candidate. Her research interests include parallel intelligence, digital twins and intelligent systems. LI Huabiao, master, senior engineer. His research interests include smart museums and cultural relics digitization technology. WANG Chunfa, Ph.D., professor. His research interests include science and techno-logy policy and science culture, museum management and intelligent museums.
LU Yue,GUO Chao,PAN Qing等. Parallel Museum Systems: Framework, Platform, Methods and Applications[J]. Pattern Recognition and Artificial Intelligence, 2023, 36(7): 575-589.
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