Intelligent campus network dynamic optimization and intelligent decision support based on 5G + AIoT
基于5G+AIoT的智慧园区网络动态优化与智能决策支持

摘要

针对智慧园区网络管理与决策效率问题，本研究提出基于5G+AIoT的解决方案。通过设计融合5G基站、边缘计算节点的统一架构，利用机器学习实现流量预测、资源动态分配及故障自愈。构建多源数据处理体系，建立能耗优化、安防评估等决策模型。实践证明，该系统有效提升网络性能，缩短故障恢复时长，为园区智能化管理提供科学支撑，推动产业升级与城市数字化发展。

Abstract

To address network management and decision-making efficiency issues in smart parks, this study proposes a solution based on 5G+AIoT. A unified architecture integrating 5G base stations and edge computing nodes is designed to achieve traffic prediction, dynamic resource allocation, and fault self-healing via machine learning. A multi-source data processing system is built to establish decision models for energy optimization and security assessment. Practices show the system significantly enhances network performance, shortens fault recovery time, provides scientific support for intelligent park management, and boosts industrial upgrading and urban digital development.