arrow
返回

The Smart in Smart Cities: A Framework for Image Classification Using Deep Learning

delete2022-06-10
delete4
delete
OA
AI
R
Rabiah Al-qudah
Y
Yaser Khamayseh *
M
Monther Aldwairi
S
Sarfraz Fayaz Khan
DOI:10.3390/s22124390delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
The need for a smart city is more pressing today due to the recent pandemic, lockouts, climate changes, population growth, and limitations on availability/access to natural resources. However, these challenges can be better faced with the utilization of new technologies. The zoning design of smart cities can mitigate these challenges. It identifies the main components of a new smart city and then proposes a general framework for designing a smart city that tackles these elements. Then, we propose a technology-driven model to support this framework. A mapping between the proposed general framework and the proposed technology model is then introduced. To highlight the importance and usefulness of the proposed framework, we designed and implemented a smart image handling system targeted at non-technical personnel. The high cost, security, and inconvenience issues may limit the cities' abilities to adopt such solutions. Therefore, this work also proposes to design and implement a generalized image processing model using deep learning. The proposed model accepts images from users, then performs self-tuning operations to select the best deep network, and finally produces the required insights without any human intervention. This helps in automating the decision-making process without the need for a specialized data scientist.
Keyword:
smart city
deep learning
zoning
transfer learning
images
automation
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Sensors 封面图
Sensors
IF:
3.5
论文数:
7.2W
被引数:
20.9W

机构

Z
zayed university
学者数:
1.3K
论文数: 1.6K
被引数: 5
C
concordia university - canada
学者数:
8.0K
论文数: 8.9K
被引数: 4
引用论文

引用论文

学者 查看更多内容