The green hospital is an important part for constructing Sustainable Cities. In this paper, system optimization algorithms based on artificial intelligence technologies are proposed by studying the communication system of the green hospital in the smart sustainable city, and the overall architecture design and detailed functional module design were carried out. The functions in the system can be divided into basic information management function, patient monitoring function, and remote self-test, etc. The medical equipment management system is characterized by the combination of Internet of Things technology, so that equipment managers can control the operating status of the equipment at any time, and can remotely upgrade and control the equipment through the system, and medical staff can view the measurement data of the equipment at the system interface and grasp the real-time information of treating patients to improve work efficiency. The accuracy of the improved particle swarm optimization (PSO) algorithm was compared with that of a single BP neural network algorithm. According to the requirement analysis of the health monitoring software and the overall design scheme of the system, each functional module of the health monitoring software is designed and the specific implementation of each functional module is carried out.

绿色医院是建设可持续城市的重要组成部分。本文通过对可持续智慧城市绿色医院通信系统的研究，提出了基于人工智能技术的系统优化算法，并进行了整体架构设计和详细功能模块设计。系统中的功能可分为基本信息管理功能、患者监护功能、远程自检等。 医疗设备管理系统的特点是结合物联网技术，让设备管理人员可以控制操作随时了解设备状态，并可通过系统远程升级和控制设备，医务人员可以在系统界面查看设备的测量数据，掌握救治患者的实时信息，提高工作效率。将改进的粒子群优化（PSO）算法的精度与单一的 BP 神经网络算法的精度进行了比较。根据健康监测软件的需求分析和系统的总体设计方案，设计了健康监测软件的各个功能模块，并进行了各个功能模块的具体实现。