@inproceedings{d3ab05a91760418b83ee3dcd4a4ff544,
title = "A Federated Interactive Learning IoT-Based Health Monitoring Platform",
abstract = "Remote health monitoring is a trend for better health management which necessitates the need for secure monitoring and privacy-preservation of patient data. Moreover, accurate and continuous monitoring of personal health status may require expert validation in an active learning strategy. As a result, this paper proposes a Federated Interactive Learning IoT-based Health Monitoring Platform (FIL-IoT-HMP) which incorporates multi-expert feedback as {\textquoteleft}Human-in-the-loop{\textquoteright} in an active learning strategy in order to improve the clients{\textquoteright} Machine Learning (ML) models. The authors have proposed an architecture and conducted an experiment as a proof of concept. Federated learning approach has been preferred in this context given that it strengthens privacy by allowing the global model to be trained while sensitive data is retained at the local edge nodes. Also, each model{\textquoteright}s accuracy is improved while privacy and security of data has been upheld.",
keywords = "Federated, Healthcare, IoT, Machine learning",
author = "Sadi Alawadi and Kebande, {Victor R.} and Yuji Dong and Joseph Bugeja and Persson, {Jan A.} and Olsson, {Carl Magnus}",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 25th East-European Conference on Advances in Databases and Information Systems, ADBIS 2021 co-allocated with Workshops on DOING, SIMPDA, MADEISD, MegaData, CAoNS 2021 ; Conference date: 24-08-2021 Through 26-08-2021",
year = "2021",
doi = "10.1007/978-3-030-85082-1_21",
language = "English",
isbn = "9783030850814",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "235--246",
editor = "Ladjel Bellatreche and Marlon Dumas and Panagiotis Karras and Raimundas Matulevi{\v c}ius",
booktitle = "New Trends in Database and Information Systems - ADBIS 2021 Short Papers, Doctoral Consortium and Workshops",
}