{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T17:33:22Z","timestamp":1769708002610,"version":"3.49.0"},"reference-count":28,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2023,8,24]]},"abstract":"<jats:p>For many, Covid-19 is a short-term, mildly debilitating disease. But some people are still struggling with monthly symptoms with persistent inflammation, chronic pain and shortness of breath. The situation of \u201clong-term cowardice\u201d has become so debilitating that it is now common for some to say that they are tired even if they walk a short distance. So far, the focus has been on saving lives from the plague. But now there are growing concerns about people facing the long-term consequences of the COVID epidemic. The fundamental question, with the uncertainty of whether those with chronic goiter, or all those affected, will fully recover is raised. In this paper a smart monitoring model was proposed to keep monitoring the COVID patient\u2019s health conditions. The smart method keep on watching the different changes reflected in the body conditions and ensure the changes in the database. In case any emergency is raised, then these smart monitoring tools inform the information to the doctors. This can very much helpful for the patients to communicate with the doctors.<\/jats:p>","DOI":"10.3233\/jifs-231899","type":"journal-article","created":{"date-parts":[[2023,6,27]],"date-time":"2023-06-27T11:41:55Z","timestamp":1687866115000},"page":"4383-4393","source":"Crossref","is-referenced-by-count":0,"title":["An application development for smart monitoring of COVID patients using six stage microbiological health systems"],"prefix":"10.1177","volume":"45","author":[{"given":"Padavala Sai","family":"Prasad","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, ST. Martin\u2019s Engineering College (Autonomous), Secunderabad, Telangana, India"}]},{"given":"Prabha Shreeraj","family":"Nair","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Noida Institute of Engineering and Technology (NIET), Greater Noida, Uttar Pradesh, India"}]},{"given":"Anagha","family":"Patil","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Vidyavardhini\u2019s College of Engineering and Technology, Vasai, K.T. Marg, Vasai (W), Maharashtra, India"}]},{"given":"Nilesh Madhukar","family":"Patil","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, SVKM\u2019s D J Sanghvi College of Engineering, Vile Parle West, Maharashtra, India"}]},{"given":"Abhay","family":"Chaturvedi","sequence":"additional","affiliation":[{"name":"Department of Electronics & Communication Engineering, GLA University, Mathura, Uttar Pradesh, India"}]},{"given":"Syed Noeman","family":"Taqui","sequence":"additional","affiliation":[{"name":"Department of VLSI Microelectronics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India"}]},{"given":"Hesham S.","family":"Almoallim","sequence":"additional","affiliation":[{"name":"Department of Oral and Maxillofacial Surgery, College of Dentistry, King Saud University, Riyadh, Saudi Arabia"}]},{"given":"Sulaiman Ali","family":"Alharbi","sequence":"additional","affiliation":[{"name":"Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia"}]},{"given":"S.S.","family":"Raghavan","sequence":"additional","affiliation":[{"name":"Department of Biology, University of Tennessee Health Science center, Memphis, USA"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-231899_ref1","doi-asserted-by":"crossref","unstructured":"Fakhry A. , Jiang X. , Xiao J. , Chaudhari G. , Han A. and Khanzada A. , Virufy: a multi-branch deep learning network for automated detection of COVID-19. (2021) arXiv preprint arXiv:2103.01806.","DOI":"10.21437\/Interspeech.2021-378"},{"key":"10.3233\/JIFS-231899_ref2","doi-asserted-by":"crossref","first-page":"105020","DOI":"10.1016\/j.compbiomed.2021.105020","article-title":"COVID-19 cough sound symptoms classification from scalogram image representation using deep learning models","volume":"139","author":"Loey","year":"2021","journal-title":"Computers in Biology and Medicine"},{"issue":"26","key":"10.3233\/JIFS-231899_ref3","doi-asserted-by":"crossref","first-page":"e1","DOI":"10.4108\/eai.28-1-2021.168505","article-title":"Intelligent internet of things and advanced machine learning techniques for covid-19","volume":"7","author":"Chakraborty","year":"2021","journal-title":"EAI Endorsed Transactions on Pervasive Health and Technology"},{"issue":"3","key":"10.3233\/JIFS-231899_ref4","first-page":"271","article-title":"Covid-19 disease diagnosis using smart deep learning techniques","volume":"24","author":"Kavitha","year":"2021","journal-title":"Journal of Applied Science and Engineering"},{"key":"10.3233\/JIFS-231899_ref5","doi-asserted-by":"crossref","unstructured":"Ponomarchuk A. , Burenko I. , Malkin E. , Nazarov I. , Kokh V. , Avetisian M. and Zhukov L. , Project Achoo: a practical model and application for COVID-19 detection from recordings of breath, voice, and cough, IEEE Journal of Selected Topics in Signal Processing (2022).","DOI":"10.1109\/JSTSP.2022.3142514"},{"issue":"3","key":"10.3233\/JIFS-231899_ref6","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1007\/s00354-021-00121-7","article-title":"XCOVNet: chest X-ray image classification for COVID-19 early detection using convolutional neural networks","volume":"39","author":"Madaan","year":"2021","journal-title":"New Generation Computing"},{"issue":"3","key":"10.3233\/JIFS-231899_ref7","doi-asserted-by":"crossref","first-page":"1117","DOI":"10.3390\/ijerph18031117","article-title":"Machine and deep learning towards COVID-19 diagnosis and treatment: survey, challenges, and future directions","volume":"18","author":"Alafif","year":"2021","journal-title":"International Journal of Environmental Research and Public Health"},{"key":"10.3233\/JIFS-231899_ref8","doi-asserted-by":"crossref","unstructured":"Akman A. , Coppock H. , Gaskell A. , Tzirakis P. , Jones L. and Schuller B.W. , Evaluating the covid-19 identification resnet (cider) on the interspeech covid-19 from audio challenges, (2021). arXiv preprint arXiv:2107.14549.","DOI":"10.3389\/fdgth.2022.789980"},{"key":"10.3233\/JIFS-231899_ref9","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.comcom.2021.06.011","article-title":"Efficient deep neural networks for classification of COVID-19 based on CT images: Virtualization via software defined radio","volume":"176","author":"Ouladi","year":"2021","journal-title":"Computer Communications"},{"key":"10.3233\/JIFS-231899_ref10","doi-asserted-by":"crossref","unstructured":"Coppock H. , Gaskell A. , Tzirakis P. , Baird A. , Jones L. and Schuller B. , End- to-end convolutional neural network enables COVID-19 detection from breath and cough audio: a pilot study, BMJ Innovations 7(2) (2021).","DOI":"10.1136\/bmjinnov-2021-000668"},{"key":"10.3233\/JIFS-231899_ref11","doi-asserted-by":"crossref","unstructured":"Fathan A. , Alam J. and Kang W.H. , An Ensemble Approach for the Diagnosis of COVID-19 from Speech and Cough Sounds, In International Conference on Speech and Computer (2021) (pp. 190\u2013201). Springer, Cham.","DOI":"10.1007\/978-3-030-87802-3_18"},{"key":"10.3233\/JIFS-231899_ref12","doi-asserted-by":"crossref","first-page":"103286","DOI":"10.1016\/j.bspc.2021.103286","article-title":"ENResNet: A novel residual neural network for chest X-ray enhancement based COVID-19 detection","volume":"72","author":"Ghosh","year":"2022","journal-title":"Biomedical Signal Processing and Control"},{"key":"10.3233\/JIFS-231899_ref13","doi-asserted-by":"crossref","first-page":"100378","DOI":"10.1016\/j.imu.2020.100378","article-title":"AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app","volume":"20","author":"Imran","year":"2020","journal-title":"Informatics in Medicine Unlocked"},{"issue":"3","key":"10.3233\/JIFS-231899_ref14","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1121\/1.1915893","article-title":"The mel scale equates the magnitude of perceived differences in pitch at different frequencies","volume":"8","author":"Stevens","year":"1937","journal-title":"Journal of the Acoustical Society of America"},{"key":"10.3233\/JIFS-231899_ref15","doi-asserted-by":"crossref","first-page":"14","DOI":"10.3389\/fdgth.2021.564906","article-title":"and Computer Audition: An Overview on What Speech &SoundAnalysis Could Contribute in the SARS-CoV-2 Corona Crisis","volume":"3","author":"Schuller","year":"2021","journal-title":"Frontiers in Digital Health"},{"key":"10.3233\/JIFS-231899_ref16","unstructured":"Wang Y. , Hu M. , Li Q. , Zhang X.P. , Zhai G. and Yao N. , Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner. (2020). arXiv preprint arXiv:2002.05534."},{"key":"10.3233\/JIFS-231899_ref17","doi-asserted-by":"crossref","unstructured":"Sharma N. , Krishnan P. , Kumar R. , Ramoji S. , Chetupalli S.R. , Ghosh P.K. and Ganapathy S. , Coswara\u2013a database of breathing, cough, and voice sounds for COVID-19 diagnosis. (2020). arXiv preprint arXiv:2005.10548.","DOI":"10.21437\/Interspeech.2020-2768"},{"issue":"1","key":"10.3233\/JIFS-231899_ref18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3381014","article-title":"FluSense: a contactless syndromic surveillance platform for influenza-like illness in hospital waiting areas","volume":"4","author":"Al Hossain","year":"2020","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"10.3233\/JIFS-231899_ref19","doi-asserted-by":"crossref","first-page":"6789","DOI":"10.1109\/ICASSP40776.2020.9054062","article-title":"Analysis of acoustic features for speech sound based classification of asthmatic and healthy subjects","author":"Yadav","year":"2020","journal-title":"ICASSP 2020\u20132020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"},{"key":"10.3233\/JIFS-231899_ref20","doi-asserted-by":"crossref","unstructured":"Simply R.M. , Dafna E. and Zigel Y. , Obstructive sleep apnea (OSA) classification using analysis of breathing sounds during speech. In 2018 26th European Signal Processing Conference (EUSIPCO) (2018) (pp. 1132\u20131136). IEEE.","DOI":"10.23919\/EUSIPCO.2018.8553353"},{"key":"10.3233\/JIFS-231899_ref21","doi-asserted-by":"crossref","unstructured":"Ramkumar M. , Basker N. , Pradeep D. , Prajapati R. , Yuvaraj N. , Raja R. Arshath and Alene A. , Healthcare Biclustering-Based Prediction on Gene Expression Dataset, BioMed Research International, 2022.","DOI":"10.1155\/2022\/2263194"},{"key":"10.3233\/JIFS-231899_ref22","doi-asserted-by":"crossref","unstructured":"Hannah S. , Deepa A.J. , Chooralil V.S. , BrillySangeetha S. Yuvaraj N. , Raja R. Arshath and Alene A. , Blockchain-Based Deep Learning to Process IoT Data Acquisition in Cognitive Data, BioMed Research International, 2022.","DOI":"10.1155\/2022\/5038851"},{"key":"10.3233\/JIFS-231899_ref23","doi-asserted-by":"crossref","unstructured":"Mohana J. , Yakkala B. , Vimalnath S. , Mansingh P.M. Benson , Srihari K. and Sundramurthy V.P. , Application of Internet of Things on the Healthcare Field Using Convolutional Neural Network Processing. Journal of Healthcare Engineering, 2022.","DOI":"10.1155\/2022\/1892123"},{"key":"10.3233\/JIFS-231899_ref24","doi-asserted-by":"crossref","unstructured":"Arivazhagan N. , Somasundaram K. , Babu D. Vijendra , Nayagam M. Gomathy , Bommi R.M. , Mohammad G.B. and Sundramurthy V. Prabhu , Cloud-Internet of Health Things (IOHT) Task Scheduling Using Hybrid Moth Flame Optimization with Deep Neural Network Algorithm for E Healthcare Systems, Scientific Programming, 2022.","DOI":"10.1155\/2022\/4100352"},{"issue":"2","key":"10.3233\/JIFS-231899_ref25","doi-asserted-by":"crossref","first-page":"76","DOI":"10.26599\/BDMA.2020.9020007","article-title":"Analysis of protein-ligand interactions of SARS-Cov-2 against selective drug using deep neural networks","volume":"4","author":"Yuvaraj","year":"2021","journal-title":"Big Data Mining and Analytics"},{"issue":"3\u20134","key":"10.3233\/JIFS-231899_ref26","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1504\/IJCAT.2021.120453","article-title":"Analysis of convolutional recurrent neural network classifier for COVID-19 symptoms over computerised tomography images","volume":"66","author":"Kannan","year":"2021","journal-title":"International Journal of Computer Applications in Technology"},{"key":"10.3233\/JIFS-231899_ref27","doi-asserted-by":"crossref","unstructured":"Maheshwari V. , Mahmood M.R. , Sravanthi S. , Arivazhagan N. , Gandhi A. Parimala , Srihari K. and Sundramurthy V.P. , Nanotechnology-Based Sensitive Biosensors for COVID-19 Prediction Using Fuzzy Logic Control, Journal of Nanomaterials, 2021.","DOI":"10.1155\/2021\/3383146"},{"key":"10.3233\/JIFS-231899_ref28","doi-asserted-by":"crossref","unstructured":"Aruna R.D. , Surendran S.D. , Yuvaraj N.D. and Debtera B. , An Enhancement on Convolutional Artificial Intelligent Based Diagnosis for Skin Disease Using Nanotechnology Sensors, Computational Intelligence and Neuroscience, 2022.","DOI":"10.1155\/2022\/9539503"}],"updated-by":[{"DOI":"10.3233\/jifs-219434","type":"retraction","label":"Retraction","source":"retraction-watch","updated":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"record-id":"64996"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-231899","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T05:26:12Z","timestamp":1769664372000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-231899"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,24]]},"references-count":28,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/jifs-231899","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,24]]}}}