Intelligent One-Stop Student Communities Based on AIoT and Big Data: A Cross-Case Study

DOI

10.2991/978-94-6239-691-3_53How to use a DOI?

Keywords

AIoT; One-stop student community; Data governance; Smart campus

Abstract

With the integration of AI, IoT, big data, and cloud computing, “one-stop” student communities are undergoing an intelligent transformation. This study conducts a cross-case comparison of Yale University (USA) and Zhejiang University (China) to examine how intelligent student-community models evolve under different institutional contexts. To strengthen analytical consistency, the comparison is organized through a five-dimensional framework that maps observable technical and governance indicators to: (i) technical system architecture, (ii) service/workflow integration, (iii) data platforms and governance, (iv) AI-enabled student support, and (v) digital community governance. The study finds that Yale tends to adopt a privacy- and compliance-oriented, decentralized smart-campus approach, whereas ZJU develops a highly integrated, AIoT-driven governance model supported by a unified data platform and mobile service hub. Importantly, the findings do not interpret integration as a purely technical advantage; instead, they highlight how data architecture choices, governance constraints, and accountability mechanisms jointly shape administrative efficiency, student-facing responsiveness, and the feasible scope of predictive analytics in student communities.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Jie Gao
AU  - Xuefang Long
AU  - Chen Xin
PY  - 2026
DA  - 2026/05/31
TI  - Intelligent One-Stop Student Communities Based on AIoT and Big Data: A Cross-Case Study
BT  - Proceedings of the 2026 5th International Conference on Educational Innovation and Multimedia Technology (EIMT 2026)
PB  - Atlantis Press
SP  - 524
EP  - 541
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6239-691-3_53
DO  - 10.2991/978-94-6239-691-3_53
ID  - Gao2026
ER  -