Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
Intelligent System Architecture for Smart City and its Applications Based Edge Computing. / Al-Gaashani, Mehdhar; Ali Muthanna, Mohammed Saleh; Abdukodir, Khakimov; Muthanna, Ammar; Kirichek, Ruslan.
2020 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2020. Institute of Electrical and Electronics Engineers Inc., 2020. стр. 269-274 9222460 (International Congress on Ultra Modern Telecommunications and Control Systems and Workshops; Том 2020-October).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
}
TY - GEN
T1 - Intelligent System Architecture for Smart City and its Applications Based Edge Computing
AU - Al-Gaashani, Mehdhar
AU - Ali Muthanna, Mohammed Saleh
AU - Abdukodir, Khakimov
AU - Muthanna, Ammar
AU - Kirichek, Ruslan
N1 - Publisher Copyright: © 2020 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - There is no doubt that smart city applications dramatically increase and the need for smart cities in our modern life becomes a demand. Smart cities will enable various applications and introduce many market innovations. However, the dramatic increase in wireless devices and network traffic puts many constraints in designing such networks. To this end, we provide to develop a reliable smart city system that enables various heterogeneous applications and provides the communication infrastructure for the expected enormous number of wireless devices. The proposed system is scalable so that the increase in network traffic will be supported with no degradation in network performances. The system deploys edge computing servers and artificial intelligence. In this study, we simulated a model for the structure of a smart city based on heterogeneous edge computing and defined evaluation parameters. Finally, according to the analysis of the results will be developed a prototype for the practical implementation of the selected method using a specific example is based on a neural network algorithm to generate forecasts of Internet of Things traffic activity.
AB - There is no doubt that smart city applications dramatically increase and the need for smart cities in our modern life becomes a demand. Smart cities will enable various applications and introduce many market innovations. However, the dramatic increase in wireless devices and network traffic puts many constraints in designing such networks. To this end, we provide to develop a reliable smart city system that enables various heterogeneous applications and provides the communication infrastructure for the expected enormous number of wireless devices. The proposed system is scalable so that the increase in network traffic will be supported with no degradation in network performances. The system deploys edge computing servers and artificial intelligence. In this study, we simulated a model for the structure of a smart city based on heterogeneous edge computing and defined evaluation parameters. Finally, according to the analysis of the results will be developed a prototype for the practical implementation of the selected method using a specific example is based on a neural network algorithm to generate forecasts of Internet of Things traffic activity.
KW - AI
KW - architecture
KW - Edge computing
KW - Smart city
UR - http://www.scopus.com/inward/record.url?scp=85094885071&partnerID=8YFLogxK
U2 - 10.1109/ICUMT51630.2020.9222460
DO - 10.1109/ICUMT51630.2020.9222460
M3 - Conference contribution
AN - SCOPUS:85094885071
T3 - International Congress on Ultra Modern Telecommunications and Control Systems and Workshops
SP - 269
EP - 274
BT - 2020 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2020
Y2 - 5 October 2020 through 7 October 2020
ER -
ID: 87324583