Integrating cultural heritage education into digital platforms is crucial for advancing the knowledge-based economy, as it introduces innovative methods for information dissemination and economic growth stimulation. This study investigates the synergy between advanced digital technologies and cultural heritage principles, focusing on developing an interactive platform for the Xiannong Altar in China. Utilizing the Applied Games Engagement Model (AGEM), the project created an interactive instructional program on traditional agricultural culture, transforming static cultural resources into dynamic knowledge. We conducted a between-subjects user study involving 100 participants. The findings demonstrate that the platform significantly enhanced participants’ understanding of cultural heritage and farming practices, positively influencing their perceptions. This study underscores the potential of digital technology to foster sustainable behaviors and effectively convey information, establishing it as a powerful educational tool for transformative learning. By illustrating how digitizing cultural material can drive innovation and create commercial value, this research contributes valuable insights for governments, cultural organizations, and entrepreneurs to leverage digital advancements to improve accessibility, engagement, and economic opportunities in the cultural and creative industries. Furthermore, it highlights the role of digital transformation in cultural heritage education as a catalyst for innovation and value generation within the knowledge-based economy.

Microplastics (MPs) will cause compound pollution by combining with organic pollutants in the aqueous environment. It is important for environmental protection to study the adsorption mechanism of different MPs for pollutants. In this study, the adsorption behaviors of malachite green (MG) and rhodamine B (RhB) on polyethylene (PE) and polyvinyl chloride (PVC) were studied in single systems and binary systems, separately. The results show that in single system, the adsorptions of between MPs for pollutants (MG and RhB) are more consistent with the pseudo-second-order kinetics and Freundlich isotherm model, the adsorption capacity of both MPs for MG is greater than that of RhB. The adsorption capacities of MG and RhB were 7.68 mg/g and 2.83 mg/g for PVC, 4.52 mg/g and 1.27 mg/g for PE. In the binary system, there exist competitive adsorption between MG and RhB on MPs. And the adsorption capacities of PVC for the two dyes are stronger than those of PE. This is attributed to the strong halogen-hydrogen bond between the two dyes and PVC, and the larger specific surface area of PVC. This study revealed the interaction and competitive adsorption mechanism between binary dyes and MPs, which is of great significance for understanding the interactions between dyes and MPs in the multi-component systems.

With the advancement of artificial intelligence, the home care environment for elderly users is becoming increasingly intelligent and systematic. The context aware human–computer interaction technology of sustainable aging-friendly smart homes can effectively identify user needs, enhance energy efficiency, and optimize resource utilization, thereby improving the convenience and sustainability of smart home care services. This paper reviews literature and analyzes cases to summarize the background and current state of context-aware interaction experience research in aging-friendly smart homes. Targeting solitary elderly users aged 60–74, the study involves field observations and user interviews to analyze their characteristics and needs, and to summarize the interaction design principles for aging-friendly smart homes. We explore processes for context-aware and methods for identifying user behaviors, emphasizing the integration of green, eco-friendly, and energy-saving principles in the design process. Focusing on the living experience and quality of life for elderly users living alone, this paper constructs a context-aware user experience model based on multimodal interaction technology. Using elderly falls as a case example, we design typical scenarios for aging-friendly smart homes from the perspectives of equipment layout and innovative hardware and software design. The goal is to optimize the home care experience for elderly users, providing theoretical and practical guidance for smart home services in an aging society. Ultimately, the study aims to develop safer, more convenient, and sustainable home care solutions.

This study introduces a design transformation model for AI-generated Chinese traditional architectural images (SD Lora&Canny) based on Stable Diffusion (SD). By integrating parameterization techniques such as Low-Rank Adaptation (Lora) and edge detection algorithms (Canny), the model achieves precise restoration of the architectural form, color elements, and decorative symbols in Chinese traditional architecture. Using the Beijing Drum Tower as the experimental subject, statistical analysis software (SPSS V28.0) was employed to conduct a quantitative evaluation and comparative analysis of architectural images generated by the DALL-E, MidJourney, SD, and SD Lora&Canny models. The results demonstrate that the SD Lora&Canny model significantly outperforms traditional generation tools in restoration accuracy and visual fidelity. Finally, this study applied the SD Lora&Canny model to create the digital cultural product AR Drum and Bell Tower Fridge Magnet, showcasing its practical application in digital cultural creation and verifying its innovative potential in the digital preservation and transmission of Chinese traditional architecture.

Deep learning technology can improve sensing efficiency and has the ability to discover potential patterns in data; the efficiency of user behavior recognition in the field of smart homes has been further improved, making the recognition process more intelligent and humanized. This paper analyzes the optical sensors commonly used in smart homes and their working principles through case studies and explores the technical framework of user behavior recognition based on optical sensors. At the same time, CiteSpace (Basic version 6.2.R6) software is used to visualize and analyze the related literature, elaborate the main research hotspots and evolutionary changes of optical sensor-based smart home user behavior recognition, and summarize the future research trends. Finally, fully utilizing the advantages of cloud computing technology, such as scalability and on-demand services, combining typical life situations and the requirements of smart home users, a smart home data collection and processing technology framework based on elderly fall monitoring scenarios is designed. Based on the comprehensive research results, the application and positive impact of optical sensors in smart home user behavior recognition were analyzed, and inspiration was provided for future smart home user experience research.

Augmented reality (AR) technology, with its unique immersive interactive experience of virtual reality integration, can show children abstract concepts and theories in an intuitive way. In this paper, we improve the high-precision position and low delay interaction of AR recognition area through edge calculation, so as to enhance the immersion of children’s chord knowledge learning. Meanwhile, multisource fusion perception of audio and touch is used, and the AI algorithm model is used to monitor physical events (cloud AI training and edge execution) and effectively realize intelligent services such as chord combination, melody perception, and control. Chord knowledge in music theory is presented to children through multichannels (kinesthetic, visual, auditory, etc.) situationally, to improve children’s learning efficiency and experience. We invited 12 children to participate in user experiments to test usability of ChordAR. The test results showed that children can master the method of playing the game through simple learning, ultimately correctly imitating C, G, and E chords, and experience full immersion in the game. Finally, we discuss the positive effects of ChordAR on children’s learning and creativity and make suggestions for future AR games.