IoT-Based Real-Time updating multi-layered learning system applied for a special care context during COVID-19

References

• Abbas, T., Khan, V.-J., & Marcopoulos, P. (2020). Investigating the crowd’s creativity for creating on-demand IoT scenarios. International Journal of Human-Computer Interaction, 36(11), 1022–24. https://doi.org/10.1080/10447318.2019.1709331
   Web of Science ®Google Scholar
• Ahmed, N., Michelin, R. A., Xue, W., Ruj, S., Malaney, R., Kanhere, S. S., Seneviratne, A., Hu, W., Janicke, H., & Jha, S. K. (2020). A survey of covid-19 contact tracing apps. IEEE Access, 8, 134577–134601. https://doi.org/10.1109/ACCESS.2020.3010226
   Web of Science ®Google Scholar
• Al-Ali, A., Zualkernan, I. A., Rashid, M., Gupta, R., & Alikarar, M. (2017, November). A smart home energy management system using IoT and big data analytics approach. IEEE Transactions on Consumer Electronics, 63(4), 426–434. https://doi.org/10.1109/TCE.2017.015014
   Web of Science ®Google Scholar
• Alaqra, A. S., Ciceri, E., Fischer-Hübner, S., Kane, B., Mosconi, M., & Vicini, S. (2020). Using PAPAYA for eHealth-Use case analysis and requirements. 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS) 28-30 July 2020 (IEEE) Rochester, MN, USA, pp. 437–442. https://doi.org/10.1109/CBMS49503.2020.00089 .
   Google Scholar
• Alsamhi, S. H., & Lee, B. (2021). Blockchain-Empowered multi-robot collaboration to fight COVID-19 and future pandemics. IEEE Access, 9, 44173–44197. https://doi.org/10.1109/ACCESS.2020.3032450
   PubMed Web of Science ®Google Scholar
• Ardito, C., Desolda, G., Lanzilotti, R., Malizia, A., Matera, M., Buono, P., & Piccinno, A. (2020). User-defined semantics for the design of IoT systems enabling smart interactive experiences. Personal and Ubiquitous Computing, 24(6), 781–796. https://doi.org/10.1007/s00779-020-01457-5
   Web of Science ®Google Scholar
• Bianchi, V., Bassoli, M., Lombardo, G., Fornacciari, P., Mordonini, M., & De Munari, I. (2019). IoT wearable sensor and deep learning: An integrated approach for personalized human activity recognition in a smart home environment. IEEE Internet Of Things Journal, 6(5), 8553–8562. https://doi.org/10.1109/JIOT.2019.292083
   Web of Science ®Google Scholar
• Brookfield, K., Fitzsimons, C., Scott, I., Mead, G., Starr, J., Thin, N., Tinker, A., & Ward Thompson, C. (2015). The home as enabler of more active lifestyles among older people. Building Research and Information, 43(5), 616–630. https://doi.org/10.1080/09613218.2015.1045702
   Web of Science ®Google Scholar
• Carpino, C., Loukou, E., Heiselberg, P., & Arcuri, N. (2020). Energy performance gap of a nearly zero energy building (nZEB) in Denmark: The influence of occupancy modelling. Building Research and Information, 48(8), 899–921. https://doi.org/10.1080/09613218.2019.1707639
   Web of Science ®Google Scholar
• Chadaga, K., Prabhu, S., Vivekananda, B. K., Niranjana, S., & Umakanth, S. (2021). Battling COVID-19 using machine learning: A review. Cogent Engineering, 8(1), 1958666. https://doi.org/10.1080/23311916.2021.1958666
   Google Scholar
• Chalmers, C., Hurts, W., Mackay, M., & Fergus, P. (2019). Identifying behavioural changes for health monitoring applications using the advanced metering infrastructure. Behaviour & Information Technology, 38(11), 1154–1166. https://doi.org/10.1080/0144929X.2019.1574900
   Web of Science ®Google Scholar
• Chaumon, M.-E. B., Michel, C., Bernard, F. T., & Croisile, B. (2014). Can ICT improve the quality of life of elderly adults living in residential home care units? From actual impacts to hidden artifacts. Behaviour & Information Technology, 33(6), 574–590. https://doi.org/10.1080/0144929X.2013.832382
   Web of Science ®Google Scholar
• Chen, L., Ahriz, I., & Ruyet, D. (2020). AoA-aware probabilistic indoor location fingerprinting using channel state information. IEEE Internet of Things Journal, 7(11), 10868–10883. https://doi.org/10.1109/JIOT.2020.2990314
   Web of Science ®Google Scholar
• Chen, M., Li, Y., Luo, X., Wang, W., Wang, L., & Zhao, W. (2019). A novel human activity recognition scheme for smart health using multilayer extreme learning machine. IEEE Internet of Things Journal, 6(2), 1410–1418. https://doi.org/10.1109/JIOT.2018.2856241
   Web of Science ®Google Scholar
• Choi, W., Kim, J., Lee, S., & Park, E. (2021). Smart home and Internet of Things: A bibliometric study. Journal of Cleaner Production, 301, 126908 . https://doi.org/10.1016/j.jclepro.2021.126908
   Web of Science ®Google Scholar
• Chui, K. T., Liu, R. W., Lytras, M. D., & Zhao, M. (2019). Big data and IoT solution for patient behavior monitoring. Behaviour & Information Technology, 38(9), 940–949. https://doi.org/10.1080/0144929X.2019.1584245
   Web of Science ®Google Scholar
• Chung, J., Hong, S., Kang, S., & Kim, C. (2021). Sequential UI behaviour prediction system based on long short-term memory networks. Behaviour & Information Technology, 1–12. https://doi.org/10.1080/0144929X.2021.1871954
   Google Scholar
• Claypool, M., Garcia, M., Retsin, G., & Soler, V. (2019). Robotic Building. Detail Business Information GmbH.
   Google Scholar
• Colmenares-Quintero, R. F., Quiroga-Parra, D. J., Rojas, N., Stansfield, K. E., & Colmenares-Quintero, J. C. (2021). Big data analytics in smart grids for renewable energy networks: Systematic review of information and communication technology tools. Cogent Engineering, 8(1), 1935410. https://doi.org/10.1080/23311916.2021.1935410
   Google Scholar
• D’Aeth, J. C., Ghosal, S., Grimm, F., Haw, D., Koca, E., Lau, K., Moret, S., Rizmie, D., Deeny, S. R., Perez-Guzman, P. N., Ferguson, N., Hauck, K., Smith, P. C., Forchini, G., Wiesemann, W., & Miraldo, M. (2021). Optimal national prioritization policies for hospital care during the SARS-CoV pandemic. Nature Computational Science, 1(8), 521–531. https://doi.org/10.1038/s43588-021-00111-1
   Google Scholar
• Dai, X., Zhao, X., Jin, P., Cai, X., Zhang, H., Yang, C., & Li, B. (2019). Opera-oriented character relations extraction for role interaction and behaviour understanding: A deep learning approach. Behaviour & Information Technology, 38(9), 900–912. https://doi.org/10.1080/0144929X.2019.1584246
   Web of Science ®Google Scholar
• Deen, M. (2015). Information and communications technologies for elderly ubiquitous healthcare in a smart home. Personal and Ubiquitous Computing, 19(3–4), 573–599. https://doi.org/10.1007/s00779-015-0856-x
   Web of Science ®Google Scholar
• Ergen, T., Mirza, A. H., & Kozat, S. S. (2020, August). Energy-efficient LSTM networks for online learning. IEEE Transactions on Neural Networks and Learning Systems, 31(8), 3114–3126. https://doi.org/10.1109/TNNLS.2019.2935796
   PubMed Web of Science ®Google Scholar
• Erişen, S. (2021). Incremental transformation of spatial intelligence from smart systems to sensorial infrastructures. Building Research and Information, 49(1), 113–126. https://doi.org/10.1080/09613218.2020.1794778
   Web of Science ®Google Scholar
• Guerra-Santin, O., & Itard, L. (2010). Occupants’ behaviour: Determinants and effects on residential heating consumption. Building Research and Information, 38(3), 318–338. https://doi.org/10.1080/09613211003661074
   Web of Science ®Google Scholar
• Habibzadeh, H., Dinesh, K., Rajabi Shishvan, O., Boggio-Dandry, A., Sharma, G., & Soyata, T. (2019). A survey of healthcare Internet of Things (HIoT): A clinical perspective. IEEE Internet of Things Journal, 7(1), 53–71. https://doi.org/10.1109/JIOT.2019.2946359
   PubMed Web of Science ®Google Scholar
• Haghi, M., Neubert, S., Geissler, A., Fleischer, H., Stoll, N., Stoll, R., & Thurow, K. (2020). A flexible and pervasive IoT- based healthcare platform for physiological and environmental parameters monitoring. IEEE Internet of Things Journal, 7(6), 5628–5647. https://doi.org/10.1109/JIOT.2020.2980432
   Web of Science ®Google Scholar
• Han, T., Muhammad, K., Hussain, T., Lloret, J., & Baik, S. W. (2021). An efficient deep learning framework for intelligent energy management in IoT networks. IEEE Internet of Things Journal, 8(5), 3170–3179. https://doi.org/10.1109/JIOT.2020.3013306
   Web of Science ®Google Scholar
• Hassanien, A. E., Dey, N., & Borra, S. (2019). Medical big data and Internet of medical things. Taylor & Francis.
   Google Scholar
• Hung, L.-P., Huang, W., Shih, J.-Y., & Liu, C.-L. (2021). A novel IoT based positioning and shadowing system for dementia training. International Journal of Environmental Research and Public Health, 18(4), 1–20. https://doi.org/10.3390/ijerph18041610
   Web of Science ®Google Scholar
• Jaimini, U., Banerjee, T., Romine, W., Thirunarayan, K., Sheth, A., & Kalra, M. (2017, April). Investigation of an indoor air quality sensor for asthma management in children. IEEE Sensors Letters, 1(2), 6000204. https://doi.org/10.1109/LSENS.2017.2691677
   PubMedGoogle Scholar
• Jelodar, H., Wang, Y., Orji, R., & Huang, H. (2020). Deep sentiment classification and topic discovery on novel coronavirus or Covid-19 online discussions: NLP using LSTM recurrent neural network approach. IEEE Journal of Biomedical and Health Informatics, 24(10), 2733–2742. https://doi.org/10.1109/JBHI.2020.3001216
   PubMed Web of Science ®Google Scholar
• Jens, K., & Gregg, J. S. (2021). The Impact on human behaviour in shared building spaces as a result of COVID-19 restrictions. Building Research and Information, 49(8), 827–841. https://doi.org/10.1080/09613218.2021.1926217
   Web of Science ®Google Scholar
• Jolfaei, A., Ostovari, P., Alazab, M., Gondal, I., & Kant, K. (2020). Special issue on privacy and security in distributed edge computing and evolving IoT. IEEE Internet of Things Journal, 7(4), 2496–2500. https://doi.org/10.1109/JIOT.2020.2980103
   Web of Science ®Google Scholar
• Kawser, M. T., & Ahmed, Z. N. (2020). Architect’s role to improve in-building wireless coverage. Cogent Engineering, 7(1), 1770912. https://doi.org/10.1080/23311916.2020.1770912
   Web of Science ®Google Scholar
• Kou, L., Zhang, D., & Liu, D. (2017). A novel medical e-nose signal analysis system. Sensors, 17(4), 402. https://doi.org/10.3390/s17040402
   PubMed Web of Science ®Google Scholar
• Lehman, M. L. (2017). Adaptive Sensory Environments. Routledge.
   Google Scholar
• Li, S., Xu, L. D., & Zhao, S. (2015). The Internet of Things: A survey. Information Systems Frontiers, 17(2), 243–259. https://doi.org/10.1007/s10796-014-9492-7
   Web of Science ®Google Scholar
• Liang, T., Zeng, B., Liu, J., Ye, L., & Zou, C. (2018). An unsupervised user behavior prediction algorithm based on machine learning and neural network for smart home. IEEE Access, 6, 49237–49247. https://doi.org/10.1109/ACCESS.2018.2868984
   Web of Science ®Google Scholar
• Luz, S., Masoodian, M., & Cesario, M. (2015). Disease surveillance and patient care in remote regions: An exploratory study of collaboration among health-care professionals in Amazonia. Behaviour & Information Technology, 36(6), 548–565. https://doi.org/10.1080/0144929X.2013.853836
   Web of Science ®Google Scholar
• Maceli, M. (2021). Low-cost physical computing platforms for end-user prototyping of smart home systems. Behaviour & Information Technology, 40(10), 997–1007. https://doi.org/10.1080/0144929X.2021.1918248
   Web of Science ®Google Scholar
• Mäkinen, H., Haavisto, E., Havola, S., & Koivisto, J.-M. (2020). User experiences of virtual reality technologies for healthcare in learning: An integral review. Behaviour & Information Technology, 1–17. https://doi.org/10.10/0144929X.2020.1788162
   Web of Science ®Google Scholar
• Mario, M.-O. (2019). Human activity recognition based on single sensor square HV acceleration images and convolutional neural networks. IEEE Sensors Journal, 19(4), 1487–1498. https://doi.org/10.1109/JSEN.2018.2882943
   Web of Science ®Google Scholar
• Nuhu, B. K., Aliyu, I., Adegboye, M. A., Ryu, J. K., Olaniyi, O. M., & Lim, C. G. (2021). Distributed network-based structural health monitoring expert system. Building Research and Information, 49(1), 144–159. https://doi.org/10.1080/09613218.2020.1854083
   Web of Science ®Google Scholar
• Ogbuabor, G. O., Augusto, J. C., Moseley, R., & van Wyk, A. (2020). Context-aware system for cardiac condition monitoring and management: A survey. Behaviour & Information Technology, 1–18. https://doi.org/10.1080/0144929X.2020.1836255
   Google Scholar
• Pham, M., Mengistu, Y., Do, H., & Sheng, W. (2018). Delivering home healthcare through a cloud-based smart home environment (CoSHE). Future Generation Computing Systems, 81, 129–140. https://doi.org/10.1016/j.future.2017.10.040
   Web of Science ®Google Scholar
• Roulet, C.-A., Flourentzou, F., Foradini, F., Bluyssen, P., Cox, C., & Aizlewood, C. (2006). Multicriteria analysis of health, comfort and energy efficiency in buildings. Building Research and Information, 34(5), 475–482. https://doi.org/10.1080/09613210600822402
   Web of Science ®Google Scholar
• Sarirete, A., Balfagih, Z., Brahimi, T., Lytras, M. D., & Visvizi, A. (2021). Artificial intelligence and machine learning research: Towards digital transformation at a global scale. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-021-03168-y
   Google Scholar
• Shah, A. S., Nasir, H., Fayaz, M., Lajis, A., Ullah, I., & Shah, A. (2020). Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and BAT algorithm. IEEE Access, 8, 204744–204762. https://doi.org/10.1109/ACCESS.2020.3037081
   Web of Science ®Google Scholar
• Shamsi, A., Asgharnezhad, H., Jokandan, S. S., Khosravi, A., Kebria, P. M., Nahavandi, D., Nahavandi, S., & Srinivasan, D. (2021). An uncertainty-aware transfer learning-based framework for COVID-19 diagnosis. IEEE Transactions on Neural Networks and Learning Systems, 32(4), 1408–1417. https://doi.org/10.1109/TNNLS.2021.3054306
   PubMed Web of Science ®Google Scholar
• Shang, C., Chang, C.-Y., Liu, J., Zhao, S., & Sinha Roy, D. (2020). FIID: Feature-based implicit irregularity detection using unsupervised learning from IoT data for homecare of elderly. IEEE Internet of Things Journal, 7(11), 10884–10896. https://doi.org/10.1109/JIOT.2020.2990556
   Web of Science ®Google Scholar
• Shao, W., Luo, H., Zhao, F., Tian, H., Yan, S., & Crivello, A. (2020). Accurate indoor positioning using temporal–spatial constraints based on Wi-Fi fine time measurements. IEEE Internet of Things Journal, 7(11), 11006–11019. https://doi.org/10.1109/JIOT.2020.2992069
   Web of Science ®Google Scholar
• Valks, B., Arkesteijn, M. H., Koutamanis, A., & den Heijer, A. C. (2021). Towards a smart campus: Supporting campus decisions with Internet of Things applications. Building Research and Information, 49(1), 1–20. https://doi.org/10.1080/09613218.2020.1784702
   Web of Science ®Google Scholar
• Vasiliou, C., Ioannou, A., & Zaphiris, P. (2020). From behaviour to design: Implications for artifact ecologies as shared spaces for design activities. Behaviour & Information Technology, 39(4), 463–480. https://doi.org/10.1080/0144929X.2019.1601258
   Web of Science ®Google Scholar
• Wang, S. L., & Lin, H. I. (2019). Integrating TTF and IDT to evaluate user intention of big data analytics in mobile cloud healthcare system. Behaviour & Information Technology, 38(9), 974–985. https://doi.org/10.1080/0144929X.2019.1626486
   Web of Science ®Google Scholar
• Wang, Y., & Shao, L. (2018). Understanding occupancy and user behaviour through Wi-Fi-based indoor positioning. Building Research and Information, 46(7), 725–737. https://doi.org/10.1080/09613218.2018.1378498
   Web of Science ®Google Scholar
• Weixian, L., Logenthiran, T., Van-Tung, P., & Woo, W. (2018). Implemented IoT-based self-learning home management system (SHMS) for Singapore. IEEE Internet of Things Journal, 5(3), 2212–2219. https://doi.org/10.1109/JIOT.2018.2828144
   Web of Science ®Google Scholar
• Wu, D., Jiang, Z., Xie, X., Wei, X., Yu, W., & Li, R. (2020). LSTM learning with Bayesian and Gaussian processing for anomaly detection in industrial IoT. IEEE Transactions on Industrial Informatics, 16(8), 5244–5253. https://doi.org/10.1109/TII.2019.2952917
   Web of Science ®Google Scholar
• Wu, T., Wu, F., Qiu, C., Redoute, J.-M., & Yuce, M. R. (2020). A rigid-flex wearable health monitoring sensor patch for IoT-Connected healthcare applications. IEEE Internet of Things Journal, 7(8), 6932–6945. https://doi.org/10.1109/JIOT.2020.2977164
   Web of Science ®Google Scholar
• Xu, L. D., He, W., & Li, S. (2014). Internet of things in industries: A survey. IEEE Transactions on Industrial Informatics, 10(4), 2233–2243. https://doi.org/10.1109/TII.2014.2300753
   Web of Science ®Google Scholar
• Zhang, Y., Tzortzopoulos, P., & Kagioglou, M. (2019). Healing built-environment effects on health outcomes: Environment-occupant-health framework. Building Research and Information, 47(6), 747–766. https://doi.org/10.10/09613218.2017.1411130
   Web of Science ®Google Scholar
• Zhou, X., Liang, W., Wang, K. I. K., Wang, H., Yang, L. T., & Jin, Q. (2020). Deep-learning-enhanced human activity recognition for Internet of healthcare things. IEEE Internet of Things Journal, 7(7), 6429–6438. https://doi.org/10.1109/JIOT.2020.2985082
   Web of Science ®Google Scholar