RNN-Based Demand Awareness in Smart Library Using CRFID

作     者：Ruiqin Bai Jumin Zhao Dengao Li Xiaoyu Lv Qiang Wang Biaokai Zhu Ruiqin Bai;Jumin Zhao;Dengao Li;Xiaoyu Lv;Qiang Wang;Biaokai Zhu

作者机构：College of Information and ComputerTaiyuan University of TechnologyJinzhong 030600China College of Data ScienceTaiyuan University of TechnologyJinzhong 030600China Technology Research Center of Spatial Information Network Engineering of ShanxiJinzhong 030600China 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2020年第17卷第5期

页      面：284-294页

核心收录：

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 12[管理学] 13[艺术学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 0835[工学-软件工程] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Key Research and Development Project (2018YFB2200900): Broadband Optical Transceiver Integrated Devices and Modules for Data Center Applications The General Object of National Natural Science Foundation under Grants (61972273): Research on Adaptive Modulation Theory and Key Technologies for Passive Sensor Systems 

主　　题：demand awareness detection of phases CRFID RNN smart library 

摘      要：To provide more intelligence service in the smart library, we need to better perceive the reader’s preferences. In addition to perceiving online records based on readers’ search history and borrowing records, advanced information technologies give us more chance to perceive the behavior of readers in the actual reading process and further discover the need for reading. In this paper, we use CRFID and RNN deep learning network to recognize book motions in the reading process, so as to judge readers’ need degree for the book, which can provide a basis for library book purchases and readers personalized service. In order to improve the recognition accuracy, we use the RSS as well as acceleration magnitude gathered from CRFID as the input data for RNN, and design a new encoding scheme. We trained and tested the deep learning network using real-world data, recorded during actual reading in our lab environment which mimics a typical reading room, from the experimental results, we conclude that our approach is feasible to recognize different reading phase to perceiving the needs of the readers.