{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T00:12:47Z","timestamp":1778544767232,"version":"3.51.4"},"reference-count":28,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2019,7,9]],"date-time":"2019-07-09T00:00:00Z","timestamp":1562630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Soonchunhyang University Research Fund","award":["IITP-2019-2014-1-00720"],"award-info":[{"award-number":["IITP-2019-2014-1-00720"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>According to the survey on various health centres, smart log-based multi access physical monitoring system determines the health conditions of humans and their associated problems present in their lifestyle. At present, deficiency in significant nutrients leads to deterioration of organs, which creates various health problems, particularly for infants, children, and adults. Due to the importance of a multi access physical monitoring system, children and adolescents\u2019 physical activities should be continuously monitored for eliminating difficulties in their life using a smart environment system. Nowadays, in real-time necessity on multi access physical monitoring systems, information requirements and the effective diagnosis of health condition is the challenging task in practice. In this research, wearable smart-log patch with Internet of Things (IoT) sensors has been designed and developed with multimedia technology. Further, the data computation in that smart-log patch has been analysed using edge computing on Bayesian deep learning network (EC-BDLN), which helps to infer and identify various physical data collected from the humans in an accurate manner to monitor their physical activities. Then, the efficiency of this wearable IoT system with multimedia technology is evaluated using experimental results and discussed in terms of accuracy, efficiency, mean residual error, delay, and less energy consumption. This state-of-the-art smart-log patch is considered as one of evolutionary research in health checking of multi access physical monitoring systems with multimedia technology.<\/jats:p>","DOI":"10.3390\/s19133030","type":"journal-article","created":{"date-parts":[[2019,7,10]],"date-time":"2019-07-10T03:05:26Z","timestamp":1562727926000},"page":"3030","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":191,"title":["Wearable IoT Smart-Log Patch: An Edge Computing-Based Bayesian Deep Learning Network System for Multi Access Physical Monitoring System"],"prefix":"10.3390","volume":"19","author":[{"given":"Gunasekaran","family":"Manogaran","sequence":"first","affiliation":[{"name":"University of California Davis, Davis, CA 95616, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P.","family":"Shakeel","sequence":"additional","affiliation":[{"name":"Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal 76100, Melaka, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"H.","family":"Fouad","sequence":"additional","affiliation":[{"name":"Biomedical Engineering Department, Faculty of Engineering, Helwan University, Helwan 11792, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3318-9394","authenticated-orcid":false,"given":"Yunyoung","family":"Nam","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Soonchunhyang University, Asan 31538, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S.","family":"Baskar","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu 641021, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5396-8897","authenticated-orcid":false,"given":"Naveen","family":"Chilamkurti","sequence":"additional","affiliation":[{"name":"Department of Computer Science and IT, La Trobe University, Melbourne 3086, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Revathi","family":"Sundarasekar","sequence":"additional","affiliation":[{"name":"Anna University, Tamil Nadu 600025, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1007\/s10916-018-1045-z","article-title":"Maintaining security and privacy in health care system using learning based Deep-Q-Networks","volume":"42","author":"Shakeel","year":"2018","journal-title":"J. Med. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1007\/s10916-019-1255-z","article-title":"Construction of medical equipment-based doctor health monitoring system","volume":"43","author":"Wang","year":"2019","journal-title":"J. Med. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s12652-017-0598-x","article-title":"Remote patient monitoring: A comprehensive study","volume":"10","author":"Malasinghe","year":"2019","journal-title":"J. Ambient Intell. Humaniz. Comput."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sridhar, K.P., Baskar, S., Shakeel, P.M., and Dhulipala, V.S. (2018). Developing brain abnormality recognize system using multi-objective pattern producing neural network. J. Ambient. Intell. Humaniz. Comput., 1\u20139.","DOI":"10.1007\/s12652-018-1058-y"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Maria, A.R., and Sever, P. (2018, January 28\u201330). MIoT Applications for Wearable Technologies Used for Health Monitoring. Proceedings of the 2018 10th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), Iasi, Romania.","DOI":"10.1109\/ECAI.2018.8679069"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.future.2017.10.045","article-title":"A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system","volume":"82","author":"Manogaran","year":"2018","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1007\/s13755-018-0054-0","article-title":"Cloud based framework for diagnosis of diabetes mellitus using K-means clustering","volume":"6","author":"Shakeel","year":"2018","journal-title":"Health Inf. Sci. Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.pmcj.2018.07.007","article-title":"System for monitoring and supporting the treatment of sleep apnea using IoT and big data","volume":"50","author":"Yacchirema","year":"2018","journal-title":"Pervasive Mob. Comput."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Erdeniz, S.P., Maglogiannis, I., Menychtas, A., Felfernig, A., and Tran, T.N.T. (2018, January 25\u201327). Recommender systems for IoT enabled m-health applications. Proceedings of the IFIP International Conference on Artificial Intelligence Applications and Innovations, Rhodes, Greece.","DOI":"10.1007\/978-3-319-92016-0_21"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Ma, X., Wang, Z., Zhou, S., Wen, H., and Zhang, Y. (2018). Intelligent healthcare systems assisted by data analytics and mobile computing. Wirel. Commun. Mob. Comput., 2018.","DOI":"10.1109\/IWCMC.2018.8450377"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Shakeel, P.M., and Manogaran, G. (2018). Prostate cancer classification from prostate biomedical data using ant rough set algorithm with radial trained extreme learning neural network. Health Technol., 1\u20139.","DOI":"10.1007\/s12553-018-0279-6"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.robot.2019.01.011","article-title":"Deep 3D perception of people and their mobility aids","volume":"114","author":"Kollmitz","year":"2019","journal-title":"Robot. Auton. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.inffus.2018.09.012","article-title":"Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities","volume":"50","author":"Zitnik","year":"2019","journal-title":"Inf. Fusion"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1007\/s12553-019-00302-x","article-title":"Robot technology for future welfare: Meeting upcoming societal challenges\u2014An outlook with offset in the development in Scandinavia","volume":"19","author":"Bodenhagen","year":"2019","journal-title":"Health Technol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Yuan, Y., Shi, Y., Su, X., Zou, X., Luo, Q., Feng, D.D., and Han, Z.G. (2018). Cancer type prediction based on copy number aberration and chromatin 3D structure with convolutional neural networks. BMC Genom., 19.","DOI":"10.1186\/s12864-018-4919-z"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1166\/jmihi.2019.2587","article-title":"Numerical Function Optimization in Brain Tumor Regions Using Reconfigured Multi-Objective Bat Optimization Algorithm","volume":"9","author":"Gomathi","year":"2019","journal-title":"J. Med. Imaging Health Inf."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1007\/978-3-319-75390-4_14","article-title":"Active Learning Approaches to Structural Health Monitoring","volume":"Volume 5","author":"Bull","year":"2019","journal-title":"Proceedings of the Special Topics in Structural Dynamics"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.inffus.2018.06.002","article-title":"Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions","volume":"46","author":"Nweke","year":"2019","journal-title":"Inf. Fusion"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1177\/1475921718757405","article-title":"Computer vision and deep learning\u2013based data anomaly detection method for structural health monitoring","volume":"18","author":"Bao","year":"2019","journal-title":"Struct. Health Monit."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.engstruct.2019.03.103","article-title":"Updating probabilities of bridge reinforcement corrosion using health monitoring data","volume":"190","author":"Heitner","year":"2019","journal-title":"Eng. Struct."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e152","DOI":"10.1016\/S2214-109X(17)30472-2","article-title":"Monitoring universal health coverage within the Sustainable Development Goals: Development and baseline data for an index of essential health services","volume":"6","author":"Hogan","year":"2018","journal-title":"Lancet Glob. Health"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"5577","DOI":"10.1109\/ACCESS.2018.2883957","article-title":"Neural Network Based Brain Tumor Detection Using Wireless Infrared Imaging Sensor","volume":"7","author":"Shakeel","year":"2019","journal-title":"IEEE Access"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Gu, J., Huang, R., Jiang, L., Qiao, G., Du, X., and Guizani, M. (2019). A Fog Computing Solution for Context-Based Privacy Leakage Detection for Android Healthcare Devices. Sensors, 19.","DOI":"10.3390\/s19051184"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.cct.2019.01.001","article-title":"iAmHealthy: Rationale, design and application of a family-based mHealthpediatric obesity intervention for rural children","volume":"78","author":"Davis","year":"2019","journal-title":"Contemp. Clin. Trials"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"13129","DOI":"10.1109\/ACCESS.2017.2789329","article-title":"Enabling technologies for the internet of health things","volume":"6","author":"Rodrigues","year":"2018","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1080\/10408363.2018.1536111","article-title":"Deep learning for image analysis: Personalizing medicine closer to the point of care","volume":"56","author":"Xie","year":"2019","journal-title":"Crit. Rev. Clin. Lab. Sci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1711","DOI":"10.1109\/JBHI.2017.2776351","article-title":"IoT-based remote pain monitoring system: From device to cloud platform","volume":"22","author":"Yang","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Bassoli, M., Bianchi, V., and Munari, I. (2018). A plug and play IoT Wi-Fi smart home system for human monitoring. Electronics, 7.","DOI":"10.3390\/electronics7090200"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/13\/3030\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:04:03Z","timestamp":1760187843000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/13\/3030"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,9]]},"references-count":28,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["s19133030"],"URL":"https:\/\/doi.org\/10.3390\/s19133030","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,9]]}}}