Publications

@inproceedings{tsai_development_2025,

title = {The Development of an Interactive IoT Cross-Media Survey System and Real-Time Re-presentation of Mass Learning},

author = {Y. -J. Tsai and S. -T. Liu and S. -C. Hsu},

editor = {Wei J. and Margetis G.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105008756188&doi=10.1007%2f978-3-031-93061-4_10&partnerID=40&md5=c487828eeacfdf18cf4e726e6ce28146},

doi = {10.1007/978-3-031-93061-4_10},

isbn = {03029743 (ISSN); 978-303193060-7 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {15823 LNCS},

pages = {145–157},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {In this study, we propose the Interactive IoT Cross-Media Survey System, integrating tangible interaction in a game-like manner with real-time data re-presentation. This system was implemented in the “STEM with A” Interactive Exploration Hall at National Tsing Hua University in 2020. It enabled participants to use their smartphones as tangible user interfaces to “scoop-up questions” from interactive sensing points within the exhibition areas. After completing the questions, participants could “pour-in” their responses and observe digital data re-presentation artworks generated from survey results, showcasing mass learning outcomes. Furthermore, the data re-presentation content was tailored to participants’ group characteristics, showing how their responses impact the group’s overall learning outcomes with each “pour-in response.” The study achieved several key outcomes: (1) transforming traditional surveys into a gamified survey system, enhancing participants’ engagement, (2) providing real-time, group-based data re-presentations, enabling participants to contribute to the group’s learning outcomes, and (3) implementing a grouping mechanism to foster collaboration within groups and healthy competition between them. This system provides flexible and customizable data re-presentation, making it suitable for diverse environments requiring real-time data-driven engagement. Future applications can integrate emerging technologies, such as generative AI to dynamically generate questions or virtual reality to offer immersive experiences. Additionally, data re-presentations can be designed as dynamic mass artistic creations, allowing participants to become co-creators of an evolving collective masterpiece. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},

keywords = {Cross-media, Data Re-presentation, Internet of Things, IoT Cross-Media System, IoT cross-medium system, Learning outcome, Learning systems, Mass Learning, Media systems, Smart phones, Smartphone, Smartphones, STEM with A, Survey System, Survey systems, Surveying, Tangible User Interface, Tangible user interfaces, User interfaces, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{arevalo_espinal_extended_2025,

title = {An eXtended Reality Data Transformation Framework for Internet of Things Devices Integration},

author = {W. Y. Arevalo Espinal and J. Jimenez and L. Corneo},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002862430&doi=10.1145%2f3703790.3703792&partnerID=40&md5=6ba7d70e00e3b0803149854b5744e55e},

doi = {10.1145/3703790.3703792},

isbn = {979-840071285-2 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {IoT - Proc. Int. Conf. Internet Things},

pages = {10–18},

publisher = {Association for Computing Machinery, Inc},

abstract = {The multidisciplinary nature of XR applications makes device and data integration a resource-intensive and time-consuming task, especially in the context of the Internet of Things (IoT). This paper presents Visualize Interactive Objects, VIO for short, a data transformation framework aimed at simplifying visualization and interaction of IoT devices and their data into XR applications. VIO comprises a software runtime (VRT) running on XR headsets, and a JSON-based syntax for defining VIO Descriptions (VDs). The VRT interprets VDs to facilitate visualization and interaction within the application. By raising the level of abstraction, VIO enhances interoperability among XR experiences and enables developers to integrate IoT data with minimal coding effort. A comprehensive evaluation demonstrated that VIO is lightweight, incurring in negligible overhead compared to native implementations. Ten Large Language Models (LLM) were used to generate VDs and native source-code from user intents. The results showed that LLMs have superior syntactical and semantical accuracy in generating VDs compared to native XR application development code, thus indicating that the task of creating VDs can be effectively automated using LLMs. Additionally, a user study with 12 participants found that VIO is developer-friendly and easily extensible. © 2024 Copyright held by the owner/author(s).},

keywords = {Application programs, Comprehensive evaluation, Data integration, Data Transformation, Device and Data Integration, Devices integration, Extended reality, Generative AI, Interactive objects, Internet of Things, Language Model, Software runtime, Time-consuming tasks},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{liang_iknowisee_2024,

title = {iKnowiSee: AR Glasses with Language Learning Translation System and Identity Recognition System Built Based on Large Pre-trained Models of Language and Vision and Internet of Things Technology},

author = {Q. Liang and Y. Chen and W. Li and M. Lai and W. Ni and H. Qiu},

editor = {Zhang L. and Yu W. and Wang Q. and Laili Y. and Liu Y.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200663840&doi=10.1007%2f978-981-97-3948-6_2&partnerID=40&md5=a0324ba6108674b1d39a338574269d60},

doi = {10.1007/978-981-97-3948-6_2},

isbn = {18650929 (ISSN); 978-981973947-9 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Commun. Comput. Info. Sci.},

volume = {2139 CCIS},

pages = {12–24},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {AR glasses used in daily life have made good progress and have some practical value.However, the current design concept of AR glasses is basically to simply port the content of a cell phone and act as a secondary screen for the phone. In contrast, the AR glasses we designed are based on actual situations, focus on real-world interactions, and utilize IoT technology with the aim of enabling users to fully extract and utilize the digital information in their lives. We have created two innovative features, one is a language learning translation system for users to learn foreign languages, which integrates a large language model with an open vocabulary recognition model to fully extract the visual semantic information of the scene; and the other is a social conferencing system, which utilizes the IoT cloud, pipe, edge, and end development to reduce the cost of communication and improve the efficiency of exchanges in social situations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.},

keywords = {Augmented Reality, Glass, Identity recognition, Internet of Things, Internet of things technologies, IoT, Language learning, Learning systems, LLM, Object Detection, Objects detection, Open Vocabulary Object Detection, Recognition systems, Semantics, Telephone sets, Translation (languages), Translation systems, Visual languages, Wearable computers, Wearable device, Wearable devices},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{joseph_iot_2023,

title = {IoT Empowered AI: Transforming Object Recognition and NLP Summarization with Generative AI},

author = {S. Joseph and B. S. Priya and R. Poorvaja and M. Santhosh Kumaran and S. Shivaraj and V. Jeyanth and R. P. Shivesh},

editor = {Arya K.V. and Wada T.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189754688&doi=10.1109%2fCVMI59935.2023.10465077&partnerID=40&md5=9c1a9d7151c0b04bab83586f515d30aa},

doi = {10.1109/CVMI59935.2023.10465077},

isbn = {979-835030514-2 (ISBN)},

year  = {2023},

date = {2023-01-01},

booktitle = {Proc. IEEE Int. Conf. Comput. Vis. Mach. Intell., CVMI},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {In anticipation of the widespread adoption of augmented reality in the future, this paper introduces an advanced mobile application that seamlessly integrates AR and IoT technologies. The application aims to make these cutting-edge technologies more affordable and accessible to users while highlighting their immense benefits in assisting with household appliance control, as well as providing interactive and educational experiences. The app employs advanced algorithms such as object detection, Natural Language Processing (NLP), and Optical Character Recognition (OCR) to scan the smartphone's camera feed. Upon identification, AR controls for appliances, their power consumption, and electric bill tracking are displayed. Additionally, the application makes use of APIs to access the internet, retrieving relevant 3D generative models, 360-degree videos, 2D images, and textual information based on user interactions with detected objects. Users can effortlessly explore and interact with the 3D generative models using intuitive hand gestures, providing an immersive experience without the need for additional hardware or dedicated VR headsets. Beyond home automation, the app offers valuable educational benefits, serving as a unique learning tool for students to gain hands-on experience. Medical practitioners can quickly reference organ anatomy and utilize its feature-rich functionalities. Its cost-effectiveness, requiring only installation, ensures accessibility to a wide audience. The app's functionality is both intuitive and efficient, detecting objects in the camera feed and prompting user interactions. Users can select objects through simple hand gestures, choosing desired content like 3D generative models, 2D images, textual information, 360-degree videos, or shopping-related details. The app then retrieves and overlays the requested information onto the real-world view in AR. In conclusion, this groundbreaking AR and IoT -powered app revolutionizes home automation and learning experiences, leveraging only a smartphone's camera, without the need for additional hardware or expensive installations. Its potential applications extend to education, industries, and health care, making it a versatile and valuable tool for a broad range of users. © 2023 IEEE.},

keywords = {2D, 3D, Application program interface, Application Program Interface (API), Application program interfaces, Application programming interfaces (API), Application programs, Augmented Reality, Augmented Reality(AR), Automation, Cameras, Cost effectiveness, Domestic appliances, GenAl, Internet of Things, Internet of Things (IoT) technologies, Internet of things technologies, Language processing, Natural Language Processing, Natural language processing systems, Natural languages, Object Detection, Object recognition, Objects detection, Optical character recognition, Optical Character Recognition (OCR), Smartphones},

pubstate = {published},

tppubtype = {inproceedings}

}