A Neighborhood and Machine Learning-Enabled Information Fusion Approach for the WSNs and Internet of Medical Things

• Main Authors: Zard Ali Khan, Sheneela Naz, Rahim khan, Jason Teo, Abdullah Ghani, Mohammed Amin Almaiah
• Format: Article
• Language: English; English
• Published: Hindawi 2022
• Subjects: TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television
• Online Access: https://eprints.ums.edu.my/id/eprint/33312/1/A%20Neighborhood%20and%20Machine%20Learning-Enabled%20Information%20Fusion%20Approach%20for%20the%20WSNs%20and%20Internet%20of%20Medical%20Things.pdf; https://eprints.ums.edu.my/id/eprint/33312/2/A%20Neighborhood%20and%20Machine%20Learning-Enabled%20Information%20Fusion%20Approach%20for%20the%20WSNs%20and%20Internet%20of%20Medical%20Things1.pdf; https://eprints.ums.edu.my/id/eprint/33312/; https://www.hindawi.com/journals/cin/2022/5112375/; https://doi.org/10.1155/2022/5112375

Data redundancy or fusion is one of the common issues associated with the resource-constrained networks such as Wireless Sensor Networks (WSNs) and Internet of Things (IoTs). To resolve this issue, numerous data aggregation or fusion schemes have been presented in the literature. Generally, it is us...