Blockchain Federated Learning for In-Home Health Monitoring
This research combines two emerging technologies, the IoT and blockchain, and investigates their potential and use in the healthcare sector. In healthcare, IoT technology can be utilized for purposes such as remotely monitoring patients’ health. This paper details ongoing research towards individual...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/12/1/136 |
| _version_ | 1797625990996819968 |
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| author | Komal Farooq Hassan Jamil Syed Samar Othman Alqahtani Wamda Nagmeldin Ashraf Osman Ibrahim Abdullah Gani |
| author_facet | Komal Farooq Hassan Jamil Syed Samar Othman Alqahtani Wamda Nagmeldin Ashraf Osman Ibrahim Abdullah Gani |
| author_sort | Komal Farooq |
| collection | DOAJ |
| description | This research combines two emerging technologies, the IoT and blockchain, and investigates their potential and use in the healthcare sector. In healthcare, IoT technology can be utilized for purposes such as remotely monitoring patients’ health. This paper details ongoing research towards individualized health monitoring using wearable gadgets. The goal of improving healthcare facilities and improvement of the quality of life of citizens naturally brings up Internet of Things (IoT) technologies for consideration. Health observation is exceptionally critical in terms of avoidance, especially since the early determination of illnesses can minimize trouble and treatment costs. The cornerstones of intelligent, integrated, and individualized healthcare are continuous monitoring of physical signs and evaluation of medical data. To build a more reliable and robust IoMT model, the study will monitor the application of blockchain technology in federated learning (FL). A viable way to address the heterogeneity problem in federated learning is to design the system, data, and model tiers to lessen heterogeneity and produce a high-quality, tailored model for each endpoint. Blockchain-based federated learning allows for smarter simulations, lower latency, and lower power consumption while maintaining privacy at the same time. This solution provides another immediate benefit: in addition to having a shared model upgrade, the updated model on phones will now be used automatically, giving personalized knowledge about the phone is used. |
| first_indexed | 2024-03-11T10:04:15Z |
| format | Article |
| id | doaj.art-baa9eb3d21e94f8bacdcd2ad0faf4daa |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T10:04:15Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-baa9eb3d21e94f8bacdcd2ad0faf4daa2023-11-16T15:11:37ZengMDPI AGElectronics2079-92922022-12-0112113610.3390/electronics12010136Blockchain Federated Learning for In-Home Health MonitoringKomal Farooq0Hassan Jamil Syed1Samar Othman Alqahtani2Wamda Nagmeldin3Ashraf Osman Ibrahim4Abdullah Gani5Department of Computer Science, National University Computer and Emerging Sciences, Karachi 75030, PakistanDepartment of Computer Science, National University Computer and Emerging Sciences, Karachi 75030, PakistanDepartment of Information Systems, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, AL-Kharj 11942, Saudi ArabiaDepartment of Information Systems, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, AL-Kharj 11942, Saudi ArabiaFaculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, MalaysiaDepartment of Computer System & Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, MalaysiaThis research combines two emerging technologies, the IoT and blockchain, and investigates their potential and use in the healthcare sector. In healthcare, IoT technology can be utilized for purposes such as remotely monitoring patients’ health. This paper details ongoing research towards individualized health monitoring using wearable gadgets. The goal of improving healthcare facilities and improvement of the quality of life of citizens naturally brings up Internet of Things (IoT) technologies for consideration. Health observation is exceptionally critical in terms of avoidance, especially since the early determination of illnesses can minimize trouble and treatment costs. The cornerstones of intelligent, integrated, and individualized healthcare are continuous monitoring of physical signs and evaluation of medical data. To build a more reliable and robust IoMT model, the study will monitor the application of blockchain technology in federated learning (FL). A viable way to address the heterogeneity problem in federated learning is to design the system, data, and model tiers to lessen heterogeneity and produce a high-quality, tailored model for each endpoint. Blockchain-based federated learning allows for smarter simulations, lower latency, and lower power consumption while maintaining privacy at the same time. This solution provides another immediate benefit: in addition to having a shared model upgrade, the updated model on phones will now be used automatically, giving personalized knowledge about the phone is used.https://www.mdpi.com/2079-9292/12/1/136blockchainfederated learninghealth monitoringInternet of Medical Things (IoMT)personalized healthcare |
| spellingShingle | Komal Farooq Hassan Jamil Syed Samar Othman Alqahtani Wamda Nagmeldin Ashraf Osman Ibrahim Abdullah Gani Blockchain Federated Learning for In-Home Health Monitoring Electronics blockchain federated learning health monitoring Internet of Medical Things (IoMT) personalized healthcare |
| title | Blockchain Federated Learning for In-Home Health Monitoring |
| title_full | Blockchain Federated Learning for In-Home Health Monitoring |
| title_fullStr | Blockchain Federated Learning for In-Home Health Monitoring |
| title_full_unstemmed | Blockchain Federated Learning for In-Home Health Monitoring |
| title_short | Blockchain Federated Learning for In-Home Health Monitoring |
| title_sort | blockchain federated learning for in home health monitoring |
| topic | blockchain federated learning health monitoring Internet of Medical Things (IoMT) personalized healthcare |
| url | https://www.mdpi.com/2079-9292/12/1/136 |
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