https://m2.mtmt.hu/ eng 2026-04-15 10:31 BookChapter 36234878 APPROVED true 0 false 2025-07-08T10:10:17.509+0000 2025-07-08T10:09:56.334+0000 2025-07-08T09:08:39.606+0000 true 10088017 Szatmári Erika /api/admin/10088017 Admin Erika Szatmári (BME admin4) true 2025-07-08T10:09:56.883+0000 2025-07-08T10:09:56.883+0000 false false true 25 25 /api/publicationtype/25 PublicationType Chapter in Book 2 true 25 BookChapter true 10000312 Conference paper true 25 25 /api/publicationtype/25 PublicationType Chapter in Book 2 true 25 BookChapter /api/subtype/10000312 Konferenciaközlemény SubType Conference paper (Chapter in Book) 228 true 10000312 true 1 /api/category/1 Category Scientific true 1 Chuma, Euclides Lourenco 1 4 1 4 2020 The increase in the number world population of elderly citizens, as well as those who live in solitude, needs an immediate solution with an intelligent monitoring system at home. In this work, we present an intelligent fall-detection system based on IoT to monitor the elderly with your privacy-protected. Currently, fall detection has attracted significant research attention and deep learning has shown promising performance in this task using conventional cameras. However, these traditional methods pose a risk of the leakage of personal privacy. This work proposes a novel fall-detection system that uses a continuous-wave Doppler radar sensor to acquisition the elderly movements and sends this information thought the internet to a server with deep learning using a convolutional neural network (CNN) that identifies the fall. The radar sensor is inexpensive, completely camera-free, and collects no personally identifiable information, thereby allaying privacy concerns. Additionally, unlike traditional cameras, it has environmental robustness and dark/light-independence. The proposed system obtained 99.9% accuracy in detecting falls by using the GoogleNet convolutional neural network. The proposed system is also capable of detecting other types of movements in addition to those tested, including the detection of diseases such as COVID-19 through the cough movement. true 2025 true true true true false false NONE 2025-07-08 false 0 0 0 0 0 0 0 0 0 0 0 0 2 2 false false false false 2025-10-06T10:09:56.186+0000 2 9 0 5 0 true true 10002 English /api/language/10002 Angol Language English true 2 false true 10939 true 10017 /api/country/10017 Country United States of America true 13 /api/city/10939 City Piscataway (NJ), United States of America true 2054246 true 18780614 /api/publicationidentifier/18780614 https://www.worldcat.org/search?q=isbn%3A9781728182940 9781728182940 PublicationIdentifier ISBN: 9781728182940 true 122 ISBN https://www.worldcat.org/search?q=isbn%3A@@@ /api/publicationsource/122 ISBN PlainSource ISBN true true 10002 /api/publicationsourcetype/10002 PublicationSourceType Egyéb true false 122 true false /api/publication/32014424 IEEE ,. 2020 IEEE International Smart Cities Conference, ISC2 2020. (2020) ISBN:9781728182940 true true 23 23 /api/publicationtype/23 PublicationType Book 3 true 23 Book false false 32014424 false true true true true 10000144 Conference proceedings true 23 23 /api/publicationtype/23 PublicationType Book 3 true 23 Book /api/subtype/10000144 Konferenciakötet SubType Conference proceedings (Book) 345 true 10000144 false Book 2020 true 1 /api/category/1 Category Scientific true 1 false Language 10002 /api/language/10002 English Angol English true 2 true PersonAuthorship 127173801 /api/authorship/127173801 Chuma, Euclides Lourenco 1 0.2 true false false Chuma Euclides Lourenco true false false AuthorshipType 1 /api/authorshiptype/1 Author 0 true 0 true false true PersonAuthorship 127173802 /api/authorship/127173802 Bravo, Roger Leonardo Lorenzo 2 0.2 false false false Bravo Roger Leonardo Lorenzo true false false AuthorshipType 1 /api/authorshiptype/1 Author 0 true 0 true false true PersonAuthorship 127173803 /api/authorship/127173803 de Oliveira, Gabriel Gomes 3 0.2 false false false de Oliveira Gabriel Gomes true false false AuthorshipType 1 /api/authorshiptype/1 Author 0 true 0 true false true PersonAuthorship 127173804 /api/authorship/127173804 Iano, Yuzo 4 0.2 false false false Iano Yuzo true false false AuthorshipType 1 /api/authorshiptype/1 Author 0 true 0 true false true PersonAuthorship 127173805 /api/authorship/127173805 Pajuelo, Diego 5 0.2 false true false Pajuelo Diego true false false AuthorshipType 1 /api/authorshiptype/1 Author 0 true 0 true false true PublicationIdentifier 21680728 /api/publicationidentifier/21680728 DOI: 10.1109/ISC251055.2020.9239074 PlainSource 6 /api/publicationsource/6 DOI PublicationSourceType 10001 /api/publicationsourcetype/10001 DOI true true true DOI DOI https://doi.org/@@@ true true 6 true 10.1109/ISC251055.2020.9239074 https://doi.org/10.1109/ISC251055.2020.9239074 false true PublicationIdentifier 29571533 /api/publicationidentifier/29571533 WoS: 000853879300064 PlainSource 1 /api/publicationsource/1 WoS PublicationSourceType 10003 /api/publicationsourcetype/10003 Indexelő adatbázis false true true WoS WoS https://www.webofscience.com/wos/woscc/full-record/@@@ true true 1 true 000853879300064 https://www.webofscience.com/wos/woscc/full-record/000853879300064 false true PublicationIdentifier 21680727 /api/publicationidentifier/21680727 Scopus: 85097141994 PlainSource 3 /api/publicationsource/3 Scopus PublicationSourceType 10003 /api/publicationsourcetype/10003 Indexelő adatbázis false true true Scopus Scopus http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-@@@ true true 3 true 85097141994 http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85097141994 false true Keyword 1097201 /api/keyword/1097201 Healthcare true 1097201 true Keyword 1180843 /api/keyword/1180843 Privacy true 1180843 true Keyword 1265582 /api/keyword/1265582 IoT true 1265582 true Keyword 1427322 /api/keyword/1427322 Deep learning true 1427322 true Keyword 1493264 /api/keyword/1493264 Computer Science, Interdisciplinary Applications true true Keyword 1504346 /api/keyword/1504346 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY true true Keyword 1548309 /api/keyword/1548309 Computer Science, Artificial Intelligence true true /api/publication/36234878 Chuma Euclides Lourenco et al. Internet of Things (IoT) Privacy-Protected, Fall-Detection System for the Elderly Using the Radar Sensors and Deep Learning. (2020) In: 2020 IEEE International Smart Cities Conference, ISC2 2020 pp. 1-4<div class="BookChapter Publication long-list"> <div class="authors"> <img title="Idézőközlemény" style="float: left" src="/frontend/resources/grid/publication-citation-icon.png"> <div class="autype autype0"> <span class="author-name" >Chuma Euclides Lourenco </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Bravo Roger Leonardo Lorenzo </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >de Oliveira Gabriel Gomes </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Iano Yuzo </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Pajuelo Diego </span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;36234878" target="_blank">Internet of Things (IoT) Privacy-Protected, Fall-Detection System for the Elderly Using the Radar Sensors and Deep Learning</a></div> <div class="InBook"><div class="chapter-in">In:</div> <div class="authors"> <div class="autype autype-1"> <span class="author-name" >IEEE , </span> (eds.) </div> </div> <div class="booktitle"><a href="/gui2/?mode=browse&params=publication;32014424" target="_blank">2020 IEEE International Smart Cities Conference, ISC2 2020 </a></div> <div class="conference"> Conference: <span class="conference-date">2020.09.28. - 2020.10.01.</span> </div> <span class="publishedAt">Piscataway (NJ): <span class="publishers">IEEE</span>, <span class="page"> pp 1-4 </span> <span class="year">(2020)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Language: English | </span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:black" title="10.1109/ISC251055.2020.9239074" target="_blank" href="https://doi.org/10.1109/ISC251055.2020.9239074"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:black" title="000853879300064" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/000853879300064"> WoS </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:black" title="85097141994" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85097141994"> Scopus </a> </span> </span> <span class="bookchapter-ids">Book link(s):</span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <span class="isbnOrIssn"> ISBN: </span> <a style="color:black" title="9781728182940" target="_blank" href="https://www.worldcat.org/search?q=isbn%3A9781728182940"> 9781728182940 </a> </span> </span> <div class="publication-citation"> <a target="_blank" href="/api/publication?cond=citations.related;eq;36234878&sort=publishedYear,desc&sort=title"> Number of cited publications: 2 </a> </div> <div class="mtid"><span class="long-pub-mtid">Publication: 36234878</span> | <span class="status-data status-APPROVED"> Published </span> <span class="long-book-mtid">Book: 32014424</span> Citing | <span class="type-subtype">Chapter in Book ( Conference paper ) </span> | <span class="pub-category">Scientific</span> | <span class="publication-sourceOfData">WOS TAGGED</span> </div> <div class="lastModified">Last Modified: 2025.07.08. 12:09 Erika Szatmári (BME admin4) </div> </div> </div>