基于环境智能的建筑智能终端  

Ambient intelligence-based building intelligent terminal

作　　者：周迎[1] 徐亚寅 丁烈云[1] ZHOU Ying;XU Yayin;DING Lieyun(School of Civil and Hydraulic Engineering,Huazhong University of Science and Technology,Wuhan 430074,China;School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]华中科技大学土木与水利工程学院,湖北武汉430074 [2]华中科技大学人工智能与自动化学院,湖北武汉430074

出　　处：《华中科技大学学报（自然科学版）》2022年第8期1-10,共10页Journal of Huazhong University of Science and Technology(Natural Science Edition)

基　　金：国家重点研发计划资助项目(2020YFC2006000);国家自然科学基金资助项目(72122007,71821001);湖北省科技重大专项资助项目(2020ACA006)。

摘　　要：随着新一轮信息技术的发展,基于环境智能的建筑智能终端必将成为工程建造领域高质量发展的重要方向.阐述了建筑智能终端的基本概念与重要性,面向构建健康、安全、绿色节能的建筑环境需求,从感知、传输、应用、对象四个层面构建了建筑智能终端技术体系.统计了建筑环境智能中常用的传感器设备与其生成的数据类型,并介绍了处理这些的智能算法与对应用途,通过物联网、计算机视觉、深度学习等技术实现建筑智能终端在医疗、居家和公共建筑空间的关键场景应用.对实际应用过程中所面临的技术、管理、组织及伦理等问题,总结了现有建筑智能终端的发展方向与未来可能面临的挑战.With the new round of information technology development,the transformation of traditional buildings into intelligent buildings has become inevitable. The basic concept and importance of building intelligent terminals were explained, and the technical system of building intelligent terminals was constructed from four levels: sensing, transmission, application, and object, in order to build a healthy, safe, and green energy-saving building environment. The sensor devices commonly used in building environment intelligence and the types of data they generate were counted, and the intelligent algorithms and corresponding uses for processing these data were introduced. The key scenario applications of building intelligent terminals in medical,home and public building spaces were realized through technologies such as Internet of Things,computer vision and deep learning.In view of the technical,management,organizational and ethical issues faced in the practical application process,the development direction of the existing building intelligent terminals and the possible challenges faced in the future were summarized.

关 键 词：智能建筑 环境智能 人工智能 物联网 计算机视觉 深度学习 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]