Rights statement: This is the author’s version of a work that was accepted for publication in Computer Communications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Communications, 149, 2020 DOI: 10.1016/j.comcom.2019.10.012
Accepted author manuscript, 863 KB, PDF document
Available under license: CC BY-NC-ND
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Cognitive computing and wireless communications on the edge for healthcare service robots
AU - Wan, S.
AU - Gu, Z.
AU - Ni, Qiang
N1 - This is the author’s version of a work that was accepted for publication in Computer Communications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Communications, 149, 2020 DOI: 10.1016/j.comcom.2019.10.012
PY - 2020/1/1
Y1 - 2020/1/1
N2 - In recent years, we have witnessed dramatic developments of mobile healthcare robots, which enjoy many advantages over their human counterparts. Previous communication networks for healthcare robots always suffer from high response latency and/or time-consuming computing demands. Robust and high-speed communications and swift processing are critical, sometimes vital in particular in the case of healthcare robots, to the healthcare receivers. As a promising solution, offloading delay-sensitive and communicating-intensive tasks to the robot is expected to improve the services and benefit users. In this paper, we review several state-of-the-art technologies, such as the human–robot interface, environment and user status perceiving, navigation, robust communication and artificial intelligence, of a mobile healthcare robot and discuss in details the customized demands over offloading the computation and communication tasks. According to the intrinsic demands of tasks over the network usage, we categorize abilities of a typical healthcare robot into alternative classes: the edge functionalities and the core functionalities. Many latency-sensitive tasks, such as user interaction, or time-consuming tasks including health receiver status recognition and autonomous moving, can be processed by the robot without frequent communications with data centers. On the other hand, several fundamental abilities, such as radio resource management, mobility management, service provisioning management, need to update the main body with the cutting-edge artificial intelligence. Robustness and safety, in this case, are the primary goals in wireless communications that AI may provide ground-breaking solutions. Based on this partition, this article refers to several state-of-the-art technologies of a mobile healthcare robot and reviews some challenges to be met for its wireless communications.
AB - In recent years, we have witnessed dramatic developments of mobile healthcare robots, which enjoy many advantages over their human counterparts. Previous communication networks for healthcare robots always suffer from high response latency and/or time-consuming computing demands. Robust and high-speed communications and swift processing are critical, sometimes vital in particular in the case of healthcare robots, to the healthcare receivers. As a promising solution, offloading delay-sensitive and communicating-intensive tasks to the robot is expected to improve the services and benefit users. In this paper, we review several state-of-the-art technologies, such as the human–robot interface, environment and user status perceiving, navigation, robust communication and artificial intelligence, of a mobile healthcare robot and discuss in details the customized demands over offloading the computation and communication tasks. According to the intrinsic demands of tasks over the network usage, we categorize abilities of a typical healthcare robot into alternative classes: the edge functionalities and the core functionalities. Many latency-sensitive tasks, such as user interaction, or time-consuming tasks including health receiver status recognition and autonomous moving, can be processed by the robot without frequent communications with data centers. On the other hand, several fundamental abilities, such as radio resource management, mobility management, service provisioning management, need to update the main body with the cutting-edge artificial intelligence. Robustness and safety, in this case, are the primary goals in wireless communications that AI may provide ground-breaking solutions. Based on this partition, this article refers to several state-of-the-art technologies of a mobile healthcare robot and reviews some challenges to be met for its wireless communications.
KW - Healthcare robot
KW - Wireless communication
KW - Edge computing
KW - Artificial intelligence
U2 - 10.1016/j.comcom.2019.10.012
DO - 10.1016/j.comcom.2019.10.012
M3 - Journal article
VL - 149
SP - 99
EP - 106
JO - Computer Communications
JF - Computer Communications
SN - 0140-3664
ER -