| Title |
A survey of data fusion in smart city applications |
| ID_Doc |
45405 |
| Authors |
Lau, BPL; Marakkalage, SH; Zhou, YR; Ul Hassan, N; Yuen, C; Zhang, M; Tan, UX |
| Title |
A survey of data fusion in smart city applications |
| Year |
2019 |
| Published |
|
| DOI |
10.1016/j.inffus.2019.05.004 |
| Abstract |
The advancement of various research sectors such as Internet of Things (IoT), Machine Learning, Data Mining, Big Data, and Communication Technology has shed some light in transforming an urban city integrating the aforementioned techniques to a commonly known term - Smart City. With the emergence of smart city, plethora of data sources have been made available for wide variety of applications. The common technique for handling multiple data sources is data fusion, where it improves data output quality or extracts knowledge from the raw data. In order to cater evergrowing highly complicated applications, studies in smart city have to utilize data from various sources and evaluate their performance based on multiple aspects. To this end, we introduce a multi-perspectives classification of the data fusion to evaluate the smart city applications. Moreover, we applied the proposed multi-perspectives classification to evaluate selected applications in each domain of the smart city. We conclude the paper by discussing potential future direction and challenges of data fusion integration. |
| Author Keywords |
Data fusion; Sensor fusion; Smart city; Big data; Internet of things; Multi-perspectives classification |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000473800600028 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
https://arxiv.org/pdf/1905.11933
|