Cloud Robotics Architecture and Challenges on Disaster Management

被引:3
作者
Atmoko, R. A. [1 ,2 ]
Yang, D. [1 ]
Adhitya, R. Y. [3 ]
机构
[1] Guilin Univ Elect Technol, Sch Mech & Elect Engn, Guilin, Peoples R China
[2] Univ Jember, Fac Engn, Elect Dept, Jember Regency, Indonesia
[3] Shipbldg Inst Polytech Surabaya, Automat Engn, Surabaya, Indonesia
来源
CLIMATE CHANGE AND SUSTAINABILITY ENGINEERING IN ASEAN 2019 | 2020年 / 2278卷
关键词
D O I
10.1063/5.0014801
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Disaster management requires fast and efficient handling of information. To deal with this issue, it does not only involve humans as the primary resource but also the various tools involved, such as robots. Cloud robotics extends the computation and information sharing among several types of robots so that robots can work as teamwork to complete a mission. This paper provides an overview of cloud robotics implementation to help deal with disasters that occur. Robots are used to mapping disaster-affected areas, identifying objects, and sending data real-time to the cloud server. This paper also discusses the implementation of typical network architecture on disaster case using fog computing paradigm. We propose using the MQTT protocol for information distribution from the robot side to the cloud server. We compare its performance with the HTTP protocol. The latest challenges and problems are also discussed in this paper.
引用
收藏
页数:6
相关论文
共 13 条
[1]   IoT real time data acquisition using MQTT protocol [J].
Atmoko, R. A. ;
Riantini, R. ;
Hasin, M. K. .
INTERNATIONAL CONFERENCE ON PHYSICAL INSTRUMENTATION AND ADVANCED MATERIALS, 2017, 853
[2]  
Atmoko R.A., 2016, IPTEK J P SERIES, V2
[3]  
Atmoko RA, 2018, PROCEEDINGS OF THE 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS, BIOMIMETICS, AND INTELLIGENT COMPUTATIONAL SYSTEMS (ROBIONETICS), P12, DOI 10.1109/ROBIONETICS.2018.8674672
[4]   A High-Throughput and Power-Efficient FPGA Implementation of YOLO CNN for Object Detection [J].
Duy Thanh Nguyen ;
Tuan Nghia Nguyen ;
Kim, Hyun ;
Lee, Hyuk-Jae .
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, 2019, 27 (08) :1861-1873
[5]  
Erkmen I, 2002, IEEE ROBOT AUTOM MAG, V9, P17, DOI 10.1109/MRA.2002.1035210
[6]  
Hanggara PO, 2017, 2017 INTERNATIONAL SYMPOSIUM ON ELECTRONICS AND SMART DEVICES (ISESD), P85, DOI 10.1109/ISESD.2017.8253310
[7]   Tactical Cloudlets: Moving Cloud Computing to the Edge [J].
Lewis, Grace ;
Echeverria, Sebastian ;
Simanta, Soumya ;
Bradshaw, Ben ;
Root, James .
2014 IEEE MILITARY COMMUNICATIONS CONFERENCE: AFFORDABLE MISSION SUCCESS: MEETING THE CHALLENGE (MILCOM 2014), 2014, :1440-1446
[8]  
Mouradian C., 2018, 2018 15 IEEE ANN CON, P1
[9]   Evolutionary deployment and local search-based movements of 0th responders in disaster scenarios [J].
Reina, D. G. ;
Camp, T. ;
Munjal, A. ;
Toral, S. L. .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 88 :61-78
[10]   Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks [J].
Ren, Shaoqing ;
He, Kaiming ;
Girshick, Ross ;
Sun, Jian .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2017, 39 (06) :1137-1149