Name
Abstract | ||
|---|---|---|
In recent years, Wireless Sensor Network (WSN) have been widely used in the Industrial Internet of Things (IIOT), especially in smart grid. The sensors not only extract the key attributes of the basic data onto operating state of various underground cables, but also remove the redundant description of the data onto the data systems. Further, the sensors can also deal with inconsistent information about the data systems. In order to ensure the reliable fusion data containing all the key information of the basic data and meeting the standard requirements of underground cable, we could overlap the sensing areas of the sensor nodes with each other. The deployment often has the problems of weak expansion ability, network delay and uneven energy consumption of nodes. Therefore, this paper focuses on the optimal weight data fusion analysis to improve the current situation. This method is more efficient for data fusion processing and data extraction. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICAIIC.2019.8668988 | 2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) |
Keywords | Field | DocType |
Wireless sensor networks,Data integration,Wireless communication,Clustering algorithms,Energy consumption,Optical fiber sensors | Data integration,Network delay,Smart grid,Data system,Computer science,Sensor fusion,Real-time computing,Data extraction,Cluster analysis,Wireless sensor network | Conference |
ISBN | Citations | PageRank |
978-1-5386-7822-0 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dengjun Zhu | 1 | 0 | 0.68 |
| Haiwei Yuan | 2 | 0 | 0.68 |
| Jinlong Yan | 3 | 4 | 1.93 |
| Yanping Qing | 4 | 0 | 0.34 |
| Weijie Yang | 5 | 0 | 0.34 |