| Title |
Smart-City-based Data Fusion Algorithm for Internet of Things |
| ID_Doc |
37754 |
| Authors |
Khan, J; Khan, MA; Jhanjhi, NZ; Humayun, M; Alourani, A |
| Title |
Smart-City-based Data Fusion Algorithm for Internet of Things |
| Year |
2022 |
| Published |
Cmc-Computers Materials & Continua, 73.0, 2 |
| DOI |
10.32604/cmc.2022.026693 |
| Abstract |
Increasingly, Wireless Sensor Networks (WSNs) are contributing enormous amounts of data. Since the recent deployments of wireless sensor networks in Smart City infrastructures, significant volumes of data have been produced every day in several domains ranging from the environment to the healthcare system to transportation. Usingwireless sensor nodes, a Smart City environment may now be shown for the benefit of residents. The Smart City delivers intelligent infrastructure and a stimulating environment to citizens of the Smart Society, including the elderly and others. Weak, Quality of Service (QoS) and poor data performance are common problems inWSNs, caused by the data fusion method, where a small amount of bad data can significantly impact the total fusion outcome. In our proposed research, a WSN multisensor data fusion technique employing fuzzy logic for event detection. Using the new proposed Algorithm, sensor nodes will collect less repeated data, and redundant data will be used to increase the data's overall reliability. The network's fusion delay problem is investigated, and a minimum fusion delay approach is provided based on the nodes' fusion waiting time. The proposed algorithm performs well in fusion, according to the results of the experiment. As a result of these discoveries, It is concluded that the algorithm describe here is effective and dependable instrument with a wide range of applications. |
| Author Keywords |
Internet of things; data fusion; wireless sensor network; fuzzy inference system |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000853232800012 |
| WoS Category |
Computer Science, Information Systems; Materials Science, Multidisciplinary |
| Research Area |
Computer Science; Materials Science |
| PDF |
https://www.techscience.com/cmc/v73n2/48327/pdf
|