Exploration and practice of AI-empowered smart campus

SU Xiaoming; ZHANG Siyu; JIANG Kaida

doi:10.11959/j.issn.1000-436x.2024254

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Exploration and practice of AI-empowered smart campus

Application of Artificial Intelligent | 更新时间：2024-12-31

- Exploration and practice of AI-empowered smart campus
- Journal on Communications Vol. 45, Issue Z2, Pages: 270-276(2024)
- 作者机构：
  
  上海交通大学网络信息中心，上海 200240
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-436x.2024254
  CLC： TN92
- Received：28 October 2024，
  
  Published：30 November 2024
- 稿件说明：
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苏小明,章思宇,姜开达.AI赋能智慧校园的探索与实践[J].通信学报,2024,45(Z2):270-276.

SU Xiaoming,ZHANG Siyu,JIANG Kaida.Exploration and practice of AI-empowered smart campus[J].Journal on Communications,2024,45(Z2):270-276.
苏小明,章思宇,姜开达.AI赋能智慧校园的探索与实践[J].通信学报,2024,45(Z2):270-276. DOI： 10.11959/j.issn.1000-436x.2024254.

SU Xiaoming,ZHANG Siyu,JIANG Kaida.Exploration and practice of AI-empowered smart campus[J].Journal on Communications,2024,45(Z2):270-276. DOI： 10.11959/j.issn.1000-436x.2024254.

摘要

围绕生成式人工智能技术在智慧校园建设中的应用进行了深入的系统研究与实践探索，聚焦于校园AI Hub——一款专为高校设计的智能应用集成与服务平台，重点剖析了校园AI Hub的两大核心功能：通用应用服务和场景化解决方案。通用应用服务涵盖智能翻译、论文阅读助手等工具，旨在为师生的日常学习与工作提供便捷支持；场景化解决方案则面向教学、科研与管理等特定需求，定制开发智能系统。在技术架构设计上，平台采用了3层结构：基础模型层依托开源大语言模型，提供强大的语言和推理能力；开发平台层通过流程编排工具提升系统的通用性和可扩展性；应用服务层则集成了AI工具，为师生提供便捷的智能化服务。基于此架构，进一步探讨了数据结构转换、可视化呈现及智能搜索等关键技术在场景化解决方案中的应用，提出了一种开源开放、共建共享的校园AI Hub发展模式。该模式具有较强的扩展性，不仅为高校智能化转型提供了切实可行的路径，也为高等教育领域的信息化建设贡献了新的思路与启示。

Abstract

According to the application and practice of generative AI technologies in smart campus development

focusing on the campus AI Hub—a smart application integration platform designed for higher education

two core functionalities of the campus AI Hub

such as general application services and scenario-based solutions were highlighted. General application services included tools like intelligent translation and reading assistants

enhancing daily learning and work efficiency. Scenario-based solutions address specific needed in teaching

research

and management through customized intelligent systems. The technical architecture featured a three-layer design

such as the foundational model layer leverages open-source large language models

the development platform layer enhances system scalability

and the application service layer integrates AI tools and optimizes processes. Key technologies such as data structure transformation

visualization

and intelligent search were applied in scenario-based solutions. An open-source

co-constructed development model for the campus AI Hub was proposed

offering a scalable approach that supports smart campus transformation and contributes to digitalizing higher education.

关键词

Keywords

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