Emerging Trends and Challenges of IoT in Smart Healthcare Systems, Smart Cities and Education
Conflicts of Interest
List of Contributions
- Al-Kahtani, M.S.; Khan, F.; Taekeun, W. Application of internet of things and sensors in healthcare. Sensors 2022, 22, 5738.
- Al-Atawi, A.A.; Khan, F.; Kim, C.G. Application and Challenges of IoT Healthcare System in COVID-19. Sensors 2022, 22, 7304.
- Butt, M.J.; Malik, A.K.; Qamar, N.; Yar, S.; Malik, A.J.; Rauf, U. A survey on COVID-19 data analysis using AI, IoT, and social media. Sensors 2023, 23, 5543.
- Kanwal, A.; Abbas, S.; Ghazal, T.M.; Ditta, A.; Alquhayz, H.; Khan, M.A. Towards parallel selective attention using psychophysiological states as the basis for functional cognition. Sensors 2022, 22, 7002.
- Naseem, M.T.; Hussain, T.; Lee, C.S.; Khan, M.A. Classification and Detection of COVID-19 and Other Chest-Related Diseases Using Transfer Learning. Sensors 2022, 22, 7977.
- Hijji, M.; Ahmad, B.; Alam, G.; Alwakeel, A.; Alwakeel, M.; Alharbi, L.A.; Aljarf, A.; Khan, M.U. Cloud servers: Resource optimization using different energy saving techniques. Sensors 2022, 22, 8384.
- Mokhamed, T.; Abu Talib, M.; Moufti, M.A.; Abbas, S.; Khan, F. The potential of blockchain technology in dental healthcare: A literature review. Sensors 2023, 23, 3277.
- Hijji, M.; Alam, G. Cybersecurity Awareness and Training (CAT) framework for remote working employees. Sensors 2022, 22, 8663.
- Li, P.; Cao, J. A virtual machine consolidation algorithm based on dynamic load mean and multi-objective optimization in cloud computing. Sensors 2022, 22, 9154.
- Vanhaeverbeke, J.; Deprost, E.; Bonte, P.; Strobbe, M.; Nelis, J.; Volckaert, B.; Ongenae, F.; Verstockt, S.; Van Hoecke, S. Real-time estimation and monitoring of covid-19 aerosol transmission risk in office buildings. Sensors 2023, 23, 2459.
- Sun, Y.; Sheng, D.; Liu, D. Analysis of the Improvement of Engineering Mechanics Experimental Methods Based on IoT and Machine Learning. Sensors 2023, 23, 3416.
- Mamieva, D.; Abdusalomov, A.B.; Kutlimuratov, A.; Muminov, B.; Whangbo, T.K. Multimodal emotion detection via attention-based fusion of extracted facial and speech features. Sensors 2023, 23, 5475.
- Priyadharshini, M.; Banu, A.F.; Sharma, B.; Chowdhury, S.; Rabie, K.; Shongwe, T. Hybrid multi-label classification model for medical applications based on adaptive synthetic data and ensemble learning. Sensors 2023, 23, 6836.
References
- Khan, F.; Tarimer, I.; Taekeun, W. Factor model for online education during the COVID-19 pandemic using the IoT. Processes 2022, 10, 1419. [Google Scholar] [CrossRef]
- Khan, H.U.; Ali, Y.; Khan, F. A Features-Based Privacy Preserving Assessment Model for Authentication of Internet of Medical Things (IoMT) Devices in Healthcare. Mathematics 2023, 11, 1197. [Google Scholar] [CrossRef]
- Nasir, M.U.; Khan, S.; Mehmood, S.; Khan, M.A.; Rahman, A.U.; Hwang, S.O. IoMT-based osteosarcoma cancer detection in histopathology images using transfer learning empowered with blockchain, fog computing, and edge computing. Sensors 2022, 22, 5444. [Google Scholar] [CrossRef]
- Chen, J.; Li, K.; Zhang, Z.; Li, K.; Yu, P.S. A survey on applications of artificial intelligence in fighting against COVID-19. ACM Comput. Surv. CSUR 2021, 54, 158. [Google Scholar] [CrossRef]
- Ghaderzadeh, M.; Asadi, F. Deep learning in the detection and diagnosis of COVID-19 using radiology modalities: A systematic review. J. Healthc. Eng. 2021, 2021, 6677314. [Google Scholar] [PubMed]
- Habib, G.; Sharma, S.; Ibrahim, S.; Ahmad, I.; Qureshi, S.; Ishfaq, M. Blockchain technology: Benefits, challenges, applications, and integration of blockchain technology with cloud computing. Future Internet 2022, 14, 341. [Google Scholar] [CrossRef]
- Kemmerer, R.A. Cybersecurity. In Proceedings of the 25th International Conference on Software Engineering, Portland, OR, USA, 3–10 May 2003; pp. 705–715. [Google Scholar]
- Hijji, M.; Alam, G. A Multivocal Literature Review on Growing Social Engineering Based Cyber-Attacks/Threats During the COVID-19 Pandemic: Challenges and Prospective Solutions. IEEE Access 2021, 9, 7152–7169. [Google Scholar] [CrossRef] [PubMed]
- Sabillon, R.; Serra-Ruiz, J.; Cavaller, V. An effective cybersecurity training model to support an organizational awareness program: The Cybersecurity Awareness TRAining Model (CATRAM). A Case Study in Canada. J. Cases Inf. Technol. JCIT 2019, 21, 26–39. [Google Scholar] [CrossRef]
- Morawska, L.; Milton, D.K. It Is Time to Address Airborne Transmission of Coronavirus Disease 2019 (COVID-19). Clin. Infect. Dis. 2020, 71, 2311–2313. [Google Scholar] [CrossRef] [PubMed]
- Peng, Z.; Jimenez, J.L. Exhaled CO2 as a COVID-19 Infection Risk Proxy for Different Indoor Environments and Activities. Environ. Sci. Technol. Lett. 2021, 8, 392–397. [Google Scholar] [CrossRef] [PubMed]
- Bazant, M.Z.; Kodio, O.; Cohen, A.E.; Khan, K.; Gu, Z.; Bush, J.W.M. Monitoring carbon dioxide to quantify the risk of indoor airborne transmission of COVID-19. medRxiv 2021, 1, E10. [Google Scholar] [CrossRef]
- Bjelajac, Z.; Filipovic, A.M. COVID-19 Pandemic-Security Challenges, Risks, and Threats. Kult. Polisa 2020, 17, 9. [Google Scholar]
- Troisi, O.; Kashef, M.; Visvizi, A. Managing safety and security in the smart city: COVID-19, emergencies and smart surveillance. In Managing Smart Cities: Sustainability and Resilience Through Effective Management; Springer International Publishing: Cham, Switzerland, 2022; pp. 73–88. [Google Scholar]
- Shahidi, F. Does COVID-19 affect food safety and security? J. Food Bioact. 2020, 9, 1–3. [Google Scholar] [CrossRef]
- Kahramanoğlu, İ.; Rengasamy, K.R.; Usanmaz, S.; Alas, T.; Helvacı, M.; Okatan, V.; Aşkın, M.A.; Wan, C. Improving the safety and security of fruits and vegetables during COVID-19 pandemic with postharvest handling. Crit. Rev. Food Sci. Nutr. 2022, 62, 8855–8865. [Google Scholar] [CrossRef] [PubMed]
- Cable, J.; Jaykus, L.A.; Hoelzer, K.; Newton, J.; Torero, M. The impact of COVID-19 on food systems, safety, and security—A symposium report. Ann. N. Y. Acad. Sci. 2021, 1484, 3–8. [Google Scholar] [CrossRef] [PubMed]
- Yu, S.; Munthali, G.N.C.; Xuelian, W.; Kudzala, J.F. Effects of government actions on safety and security perceptions of international students during COVID-19 pandemic in China. Asian J. Med. Health 2021, 19, 70–82. [Google Scholar] [CrossRef]
- Uddin, M.N.; Alam, B.; Islam, S.S.; Arif, M.; Alam, M.M.; Kabir, S.L. Impact of COVID-19 on food safety and security in low and middle income countries. Asian J. Med. Biol. Res. 2020, 6, 130–137. [Google Scholar] [CrossRef]
- Khan, S.U.; Khan, A.W.; Khan, F.; Khan, M.A.; Whangbo, T.K. Critical success factors of component-based software outsourcing development from vendors’ perspective: A systematic literature review. IEEE Access 2021, 10, 1650–1658. [Google Scholar] [CrossRef]
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Khan, F. Emerging Trends and Challenges of IoT in Smart Healthcare Systems, Smart Cities and Education. Sensors 2024, 24, 5735. https://doi.org/10.3390/s24175735
Khan F. Emerging Trends and Challenges of IoT in Smart Healthcare Systems, Smart Cities and Education. Sensors. 2024; 24(17):5735. https://doi.org/10.3390/s24175735
Chicago/Turabian StyleKhan, Faheem. 2024. "Emerging Trends and Challenges of IoT in Smart Healthcare Systems, Smart Cities and Education" Sensors 24, no. 17: 5735. https://doi.org/10.3390/s24175735