An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0

被引:223
|
作者
Pace, Pasquale [1 ]
Aloi, Gianluca [1 ]
Gravina, Raffaele [1 ]
Caliciuri, Giuseppe [1 ]
Fortino, Giancarlo [1 ]
Liotta, Antonio [2 ]
机构
[1] Univ Calabria, Dept Informat Modeling Elect & Syst, I-87036 Arcavacata Di Rende, Italy
[2] Univ Derby, Dept Elect Comp & Math, Derby DE22 1GB, England
基金
欧盟地平线“2020”;
关键词
Body sensor networks; cloud computing; edge computing; heart rate variability; internet of things; HEART-RATE-VARIABILITY;
D O I
10.1109/TII.2018.2843169
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and the huge amount of data coming from Internet of Things (IoT) devices toward the Internet. In the next future, Edge-based approaches will be essential to support time-dependent applications in the Industry 4.0 context; thus, the paper proposes BodyEdge, a novel architecture well suited for human-centric applications, in the context of the emerging healthcare industry. It consists of a tiny mobile client module and a performing edge gateway supporting multiradio and multitechnology communication to collect and locally process data coming from different scenarios; moreover, it also exploits the facilities made available from both private and public cloud platforms to guarantee a high flexibility, robustness, and adaptive service level. The advantages of the designed software platform have been evaluated in terms of reduced transmitted data and processing time through a real implementation on different hardware platforms. The conducted study also highlighted the network conditions (data load and processing delay) in which BodyEdge is a valid and inexpensive solution for healthcare application scenarios.
引用
收藏
页码:481 / 489
页数:9
相关论文
共 50 条
  • [1] Status of Industry 4.0 applications in healthcare 4.0 and Pharma 4.0
    Inuwa, Haruna Muhd
    Raja, Avinash Ravi
    Kumar, Anil
    Singh, Bhim
    Singh, Sudesh
    MATERIALS TODAY-PROCEEDINGS, 2022, 62 : 3593 - 3598
  • [2] Efficient edge-based object tracking
    Zhu, Guopu
    Zeng, Qingshuang
    Wang, Changhong
    PATTERN RECOGNITION, 2006, 39 (11) : 2223 - 2226
  • [3] Industry 4.0 Applications for Medical/Healthcare Services
    Paul, Shuva
    Riffat, Muhtasim
    Yasir, Abrar
    Mahim, Mir Nusrat
    Sharnali, Bushra Yasmin
    Naheen, Intisar Tahmid
    Rahman, Akhlaqur
    Kulkarni, Ambarish
    JOURNAL OF SENSOR AND ACTUATOR NETWORKS, 2021, 10 (03)
  • [4] An edge-based architecture to support the execution of ambience intelligence tasks using the IoP paradigm
    Alanezi, Khaled
    Mishra, Shivakant
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2021, 114 : 349 - 357
  • [5] HARDWARE SUPPORT FOR FAST EDGE-BASED STEREO
    COURTNEY, P
    THACKER, NA
    BROWN, CR
    LECTURE NOTES IN COMPUTER SCIENCE, 1992, 588 : 902 - 906
  • [6] Robust and efficient edge-based visual odometry
    Feihu Yan
    Zhaoxin Li
    Zhong Zhou
    Computational Visual Media, 2022, 8 (03) : 467 - 481
  • [7] Industry 4.0 and healthcare: Context, applications, benefits and challenges
    Kotzias, Konstantinos
    Bukhsh, Faiza A.
    Arachchige, Jeewanie Jayasinghe
    Daneva, Maya
    Abhishta, Abhishta
    IET SOFTWARE, 2023, 17 (03) : 195 - 248
  • [8] Efficient, Customizable and Edge-Based WebGIS System
    He, Honglei
    Zhu, Wenming
    IEEE ACCESS, 2020, 8 : 126164 - 126177
  • [9] Robust and efficient edge-based visual odometry
    Feihu Yan
    Zhaoxin Li
    Zhong Zhou
    Computational Visual Media, 2022, 8 : 467 - 481
  • [10] Robust and efficient edge-based visual odometry
    Yan, Feihu
    Li, Zhaoxin
    Zhou, Zhong
    COMPUTATIONAL VISUAL MEDIA, 2022, 8 (03) : 467 - 481