Cloud-Assisted Mood Fatigue Detection System

被引:4
|
作者
Shi, Xiaobo [1 ,2 ]
Hao, Yixue [1 ]
Zeng, Delu [3 ]
Wang, Lu [1 ]
Hossain, M. Shamim [4 ]
Rahman, Sk Md Mizanur [5 ]
Alelaiwi, Abdulhameed [4 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China
[2] Henan Normal Univ, Coll Comp & Informat Engn, Xinxiang 453007, Peoples R China
[3] South China Univ Technol, Sch Math, Guangzhou 510640, Guangdong, Peoples R China
[4] King Saud Univ, Software Engn Dept, Coll Comp & Informat Sci, Riyadh 11543, Saudi Arabia
[5] King Saud Univ, Dept Informat Syst, Coll Comp & Informat Sci, Riyadh 11543, Saudi Arabia
来源
MOBILE NETWORKS & APPLICATIONS | 2016年 / 21卷 / 05期
关键词
Mood fatigue; Deep learning; Convolution auto-encoder; CYBER-PHYSICAL SYSTEMS; FACE RECOGNITION; MOBILE; OPTIMIZATION; ARCHITECTURE; NETWORK;
D O I
10.1007/s11036-016-0757-x
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This paper introduces basic concept of mood fatigue detection and existing solutions as well as some typical solutions, such as mobile sensing and cloud computing technology. In the first place, we sum up main challenges of mood fatigue detection and the direction of future study. Then one type of system implementation is put forward, such system consists of: 1) Wearable devices used to detect the users' mood fatigue; 2) Clouds data center; 3) Application and service manager. We take overall consideration of many factors like the user's physiological information, external environment conditions and user behavior, evaluate accurately through big data analytic technology the users' state of mood fatigue and to what extent shall one keeps vigilant as well as what measures shall be adopted to improve the users' working performance and alert the users to keep themselves away from the danger. Finally a real system is established in this paper, it is composed of the smart clothing, cloud platform and mobile terminal application.
引用
收藏
页码:744 / 752
页数:9
相关论文
共 50 条
  • [31] Cloud-Assisted Mobile Computing and Pervasive Services
    Leung, Victor C. M.
    Chen, Min
    Guizani, Mohsen
    Vucetic, Branka
    IEEE NETWORK, 2013, 27 (05): : 4 - 5
  • [32] Artificial Intelligence for Cloud-Assisted Smart Factory
    Wan, Jiafu
    Yang, Jun
    Wang, Zhongren
    Hua, Qingsong
    IEEE ACCESS, 2018, 6 : 55419 - 55430
  • [33] Editorial to the special section on the Cloud-Assisted Services
    Stankovski, Vlado
    Trobec, Roman
    Elektrotehniski Vestnik/Electrotechnical Review, 2014, 81 (03):
  • [34] Delay-Aware Quality Optimization in Cloud-Assisted Video Streaming System
    Wu, Jiyan
    Cheng, Bo
    Yang, Yuan
    Wang, Ming
    Chen, Junliang
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2018, 14 (01)
  • [35] Cloud-assisted hugtive robot for affective interaction
    Ping Zhou
    Yixue Hao
    Jun Yang
    Wei Li
    Lu Wang
    Yiming Miao
    Jeungeun Song
    Multimedia Tools and Applications, 2017, 76 : 10839 - 10854
  • [36] CGMP: cloud-assisted green multimedia processing
    Ma, Yujun
    Zhang, Yin
    Sheng, Zhengguo
    Ruan, Hang
    Wang, Junfeng
    Sun, Yanming
    MULTIMEDIA TOOLS AND APPLICATIONS, 2016, 75 (21) : 13317 - 13332
  • [37] Cloud-assisted Augmented Reality Streaming Service System: Architecture Design and Implementation
    Noh, Hyunmin
    Song, Hwangjun
    2020 IEEE INTERNATIONAL CONFERENCE ON VISUAL COMMUNICATIONS AND IMAGE PROCESSING (VCIP), 2020, : 363 - 366
  • [38] Delegating Data Plane With Cloud-Assisted Routing
    Dey, Prasun Kanti
    Yuksel, Murat
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2023, 20 (03): : 3190 - 3204
  • [39] Security and Dependability of Cloud-Assisted Internet of Things
    Ali, Mazhar
    Khan, Samee U.
    Zomaya, Albert Y.
    IEEE CLOUD COMPUTING, 2016, 3 (02): : 24 - 26
  • [40] Cloud-assisted hugtive robot for affective interaction
    Zhou, Ping
    Hao, Yixue
    Yang, Jun
    Li, Wei
    Wang, Lu
    Miao, Yiming
    Song, Jeungeun
    MULTIMEDIA TOOLS AND APPLICATIONS, 2017, 76 (08) : 10839 - 10854