Situation Awareness Data Fusion Method Based on Library Events

被引:0
作者
Xi, Haixu [1 ,2 ]
Gao, Wei [2 ]
Park, Gyun Yeol [3 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Econ & Management, Nanjing 210094, Jiangsu, Peoples R China
[2] Jiangsu Univ Technol, Sch Comp Engn, Changzhou 213001, Peoples R China
[3] Gyeongsang Natl Univ, Jinju 52828, South Korea
来源
COMPUTER SYSTEMS SCIENCE AND ENGINEERING | 2022年 / 42卷 / 03期
关键词
Intelligent library; internet of things; situational awareness; information fusion; data fusion; BLOCKCHAIN; SMART;
D O I
10.32604/csse.2022.022051
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Microelectronic technology and communication technology are developed in deep manner; the computing mode has been transferred from traditional computer-centered to human centered pervasive. So, the concept of Internet of things (IoT) is gradually put forward, which allows people to access information about their surroundings on demand through different terminals. The library is the major public space for human to read and learn. How to provide a more comfortable library environment to better meet people's learning requirements is a place where the Internet of things plays its role. The purpose of this paper is to solve the difference between the data fusion of library environment and the data fusion of other environments by the method of data fusion oriented to library. This paper presents a general technical framework of situational awareness for smart library system which includes a data fusion middleware. It can process data and inform the upper module of the changed library environment after deploying the smart library system in a library, including data collection and processing, how to judge whether events are triggered, how the system reacts, and the acquisition and update of user preferences. This paper presents a situational awareness recommendation method based on an effective data fusion model and algorithm for library after conducting experimental in service of library, which give more accurate of book recommendation than traditional method and good learning service environment of library for readers.
引用
收藏
页码:1047 / 1061
页数:15
相关论文
共 35 条
  • [31] Wang J., 2017, LIBRALY J, V36, P82
  • [32] Data fusion in data scarce areas using a back-propagation artificial neural network model: a case study of the South China Sea
    Wang, Zheng
    Mao, Zhihua
    Xia, Junshi
    Du, Peijun
    Shi, Liangliang
    Huang, Haiqing
    Wang, Tianyu
    Gong, Fang
    Zhu, Qiankun
    [J]. FRONTIERS OF EARTH SCIENCE, 2018, 12 (02) : 280 - 298
  • [33] Improvement of Mammographic Mass Classification Performance Using an Intelligent Data Fusion Method
    Xi, Dongdong
    Li, Lihua
    Zhang, Juan
    Shan, Yanna
    Dai, Gang
    Fan, Ming
    Zheng, Bin
    [J]. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2018, 8 (02) : 275 - 283
  • [34] BAGKD: A Batch Authentication and Group Key Distribution Protocol for VANETs
    Xu, Guangquan
    Li, Xiaotong
    Jiao, Litao
    Wang, Weizhe
    Liu, Ao
    Su, Chunhua
    Zheng, Xi
    Liu, Shaoying
    Cheng, Xiaochun
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2020, 58 (07) : 35 - 41
  • [35] Zhang B., 2017, J ACOUST SOC AM, V142, P2732