This paper discusses telemedicine and the employment of advanced mobile technologies in smart healthcare delivery. It covers the technological advances in connected smart healthcare, including the roles of artificial intelligence, machine learning, 5G and IoT platforms, and other enabling technologies. It also presents the challenges and potential risks that could arise from delivering connected smart healthcare services. Healthcare delivery is witnessing revolutions engineered by the developments in mobile connectivity and the plethora of platforms, applications, sensors, devices, and equipment that go along with it. Human society is evolving fast in response to these technological developments, which are also pushing the connectivity-providing sector to create and adopt new waves of network technologies. Consequently, new communications technologies have been introduced into the healthcare system and many novel applications have been developed to make it easier for sharing data in various forms and volumes within health-related services. These applications have also made it possible for telemedicine to be effectively adopted. This paper provides an overview of some of the recent developments within the space of mobile connectivity and telemedicine.
Khujamatov, K., Reypnazarov, E., Akhmedov, N. and Khasanov, D. (2020) Blockchain for 5G Healthcare Architecture. 2020 International Conference on Information Science and Communications Technologies, Tashkent, 4-6 November 2020, 1-5. https://doi.org/10.1109/ICISCT50599.2020.9351398
Khujamatov, K., Ahmad, K., Reypnazarov, E., et al. (2020) Markov Chain Based Modeling Bandwith States of the Wireless Sensor Networks of Monitoring System. International Journal of Advanced Science and Technology, 29, 4889.
Coombes, C.E. and Gregory, M.E. (2019) The Current and Future Use of Telemedicine in Infectious Diseases Practice. Current Infectious Disease Reports, 21, Article No. 41. https://doi.org/10.1007/s11908-019-0697-2
Sosnowski, R., Kamecki, H., Joniau, S., Walz, J., Klaassen, Z. and Palou, J. (2020) Introduction of Telemedicine During the COVID-19 Pandemic: A Challenge for Now, an Opportunity for the Future. European Urology, 78, 820-821. https://doi.org/10.1016/j.eururo.2020.07.007
Rajeswari, K., Vivekanandan, N., Amitaraj, P. and Fulambarkar, A. (2018) A Study on Redesigning Modern Healthcare Using Internet of Things. In: Ray, P. and Maiti, J., Eds., Healthcare Systems Management: Methodologies and Applications, Springer, Singapore, 59-69. https://doi.org/10.1007/978-981-10-5631-4_6
Ahmad, W.S.H.M.W., et al. (2020) 5G Technology: Towards Dynamic Spectrum Sharing Using Cognitive Radio Networks. IEEE Access, 8, 14460-14488. https://doi.org/10.1109/ACCESS.2020.2966271
Dahiya, M. (2017) Need and Advantages of 5G wireless Communication Systems. International Journal of Advance Research in Computer Science and Management Studies, 5, 48-51.
Musa, S.M., Eze, K.G., Sadiku, M.N.O. and Perry, R.G. (2018) 5G Wireless Technology: A Primer. International Journal of Scientific Engineering and Technology, 7, 62-64.
Latha, D.H., Reddy, D.R.K., Sudha, K., Mubeen, A. and Savita, T.S. (2014) A Study on 5th Generation Mobile Technology-Future Network Service. International Journal of Computer Science and Information Technologies, 5, 8309-8313.
Ahad, A., Tahir, M. and Yau, K.L.A. (2019) 5G-Based Smart Healthcare Network: Architecture, Taxonomy, Challenges and Future Research Directions. IEEE Access, 7, 100747-100762. https://doi.org/10.1109/ACCESS.2019.2930628
Boughaci, D. (2020) Solving Optimization Problems in the Fifth Generation of Cellular. Procedia Computer Science, 182, 56-62. https://doi.org/10.1016/j.procs.2021.02.008
Qureshi, H.N., et al. (2022) Communication Requirements in 5G-Enabled Healthcare Applications: Review and Considerations. Healthcare, 10, Article 293. https://doi.org/10.3390/healthcare10020293
Qureshi, H.N., Manalastas, M., Zaidi, S.M.A., Imran, A. and Al Kalaa, M.O. (2021) Service Level Agreements for 5G and Beyond: Overview, Challenges and Enablers of 5G-Healthcare Systems. IEEE Access, 9, 1044-1061. https://doi.org/10.1109/ACCESS.2020.3046927
Ullah, H., Gopalakrishnan Nair, N., Moore, A., Nugent, C., Muschamp, P. and Cuevas, M. (2019) 5G Communication: An Overview of Vehicle-to-Everything, Drones, and Healthcare Use-Cases. IEEE Access, 7, 37251-37268. https://doi.org/10.1109/ACCESS.2019.2905347
Mester, G. and Rodic, A. (2013) Simulation of Quad-Rotor Flight Dynamics for the Analysis of Control, Spatial Navigation and Obstacle Avoidance. IWACIII 2013 3rd International Workshop on Advanced Computational Intelligence and Intelligent Informatics, Shanghai, October 2013, 1-4.
Taboada, I. and Shee, H. (2021) Understanding 5G Technology for Future Supply Chain Management. International Journal of Logistics Research and Applications, 24, 392-406. https://doi.org/10.1080/13675567.2020.1762850
Liu, X., Jia, M., Zhang, X. and Lu, W. (2019) A Novel Multichannel Internet of Things Based on Dynamic Spectrum Sharing in 5G Communication. IEEE Internet of Things Journal, 6, 5962-5970. https://doi.org/10.1109/JIOT.2018.2847731
Zheng, K., Yang, Z., Zhang, K., Chatzimisios, P., Yang, K. and Xiang, W. (2016) Big Data-Driven Optimization for Mobile Networks toward 5G. IEEE Network, 30, 44-51. https://doi.org/10.1109/MNET.2016.7389830
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M. and Ayyash, M. (2015) Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications. IEEE Communications Surveys and Tutorials, 17, 2347-2376. https://doi.org/10.1109/COMST.2015.2444095
Palattella, M.R., et al. (2016) Internet of Things in the 5G Era: Enablers, Architecture, and Business Models. IEEE Journal on Selected Areas in Communications, 34, 510-527. https://doi.org/10.1109/JSAC.2016.2525418
Yusifov, S.I., Ragimova, N.A., Abdullayev, V.H. and Imanova, Z.B. (2020) 5G Technology: A New Step to IoT Platform. JINAV: Journal of Information and Visualization, 1, 74-82. https://doi.org/10.35877/454RI.jinav257
Vergutz, A., Noubir, G. and Nogueira, M. (2020) Reliability for Smart Healthcare: A Network Slicing Perspective. IEEE Network, 34, 91-97. https://doi.org/10.1109/MNET.011.1900458
Afolabi, I., Taleb, T., Samdanis, K., Ksentini, A. and Flinck, H. (2018) Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions. IEEE Communications Surveys and Tutorials, 20, 2429-2453. https://doi.org/10.1109/COMST.2018.2815638
You, X., Zhang, C., Tan, X., Jin, S. and Wu, H. (2019) AI for 5G: Research Directions and Paradigms. Science China Information Sciences, 62, Article No. 21301. https://doi.org/10.1007/s11432-018-9596-5
Hao, J.K. and Solnon, C. (2020) Meta-Heuristics and Artificial Intelligence. In: Marquis, P., Papini, O. and Prade, H., Eds., A Guided Tour of Artificial Intelligence Research, Springer, Cham, 27-52. https://doi.org/10.1007/978-3-030-06167-8_2
Saha, A., Rajak, S., Saha, J. and Chowdhury, C. (2022) A Survey of Machine Learning and Meta-Heuristics Approaches for Sensor-Based Human Activity Recognition Systems. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-022-03870-5
El-Kenawy, E.S.M., et al. (2021) Advanced Meta-Heuristics, Convolutional Neural Networks, and Feature Selectors for Efficient COVID-19 X-Ray Chest Image Classification. IEEE Access, 9, 36019-36037. https://doi.org/10.1109/ACCESS.2021.3061058
Le, H.A., Van Chien, T., Nguyen, T.H., Choo, H. and Nguyen, V.D. (2021) Machine Learning-Based 5G-and-Beyond Channel Estimation for MIMO-OFDM Communication Systems. Sensors, 21, Article 4861. https://doi.org/10.3390/s21144861
Lee, W., Kim, M. and Cho, D.H. (2018) Deep Power Control: Transmit Power Control Scheme Based on Convolutional Neural Network. IEEE Communications Letters, 22, 1276-1279. https://doi.org/10.1109/LCOMM.2018.2825444
Kim, J., Lee, J.K. and Lee, K.M. (2016) Accurate Image Super-Resolution Using Very Deep Convolutional Networks. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, 27-30 June 2016, 1646-1654. https://doi.org/10.1109/CVPR.2016.182
Guo, S., Yan, Z., Zhang, K., Zuo, W. and Zhang, L. (2019) Toward Convolutional Blind Denoising of Real Photographs. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Long Beach, CA,15-20 June 2019, 1712-1722. https://doi.org/10.1109/CVPR.2019.00181
Jin, Y., Zhang, J., Ai, B. and Zhang, X. (2020) Channel Estimation for mmWave Massive MIMO with Convolutional Blind Denoising Network. IEEE Communications Letters, 24, 95-98. https://doi.org/10.1109/LCOMM.2019.2952845
Ma, B., Guo, W. and Zhang, J. (2020) A Survey of Online Data-Driven Proactive 5G Network Optimisation Using Machine Learning. IEEE Access, 8, 35606-35637. https://doi.org/10.1109/ACCESS.2020.2975004
Kaur, J., Khan, M.A., Iftikhar, M., Imran, M. and Emad Ul Haq, Q. (2021) Machine Learning Techniques for 5G and beyond. IEEE Access, 9, 23472-23488. https://doi.org/10.1109/ACCESS.2021.3051557
Fourati, H., Maaloul, R. and Chaari, L. (2021) A Survey of 5G Network Systems: Challenges and Machine Learning Approaches. International Journal of Machine Learning and Cybernetics, 12, 385-431. https://doi.org/10.1007/s13042-020-01178-4
Morocho-Cayamcela, M.E., Lee, H. and Lim, W. (2019) Machine Learning for 5G/B5G Mobile and Wireless Communications: Potential, Limitations, and Future Directions. IEEE Access, 7, 137184-137206. https://doi.org/10.1109/ACCESS.2019.2942390
Moysen, J. and Giupponi, L. (2018) From 4G to 5G: Self-Organized Network Management Meets Machine Learning. Computer Communications, 129, 248-268. https://doi.org/10.1016/j.comcom.2018.07.015
Aldhyani, T.H.H., Alshebami, A.S. and Alzahrani, M.Y. (2020) Soft Clustering for Enhancing the Diagnosis of Chronic Diseases over Machine Learning Algorithms. Journal of Healthcare Engineering, 2020, Article ID: 4984967. https://doi.org/10.1155/2020/4984967
Challita, U., Dong, L. and Saad, W. (2018) Proactive Resource Management for LTE in Unlicensed Spectrum: A Deep Learning Perspective. IEEE Transactions on Wireless Communications, 17, 4674-4689. https://doi.org/10.1109/TWC.2018.2829773
Fernandez Maimo, L., Perales Gomez, A.L., Garcia Clemente, F.J., Gil Perez, M. and Martinez Perez, G. (2018) A Self-Adaptive Deep Learning-Based System for Anomaly Detection in 5G Networks. IEEE Access, 6, 7700-7712. https://doi.org/10.1109/ACCESS.2018.2803446
Santos, G.L., Endo, P.T., Sadok, D. and Kelner, J. (2020) When 5G Meets Deep Learning: A Systematic Review. Algorithms, 13, Article 208. https://doi.org/10.3390/a13090208
Lecun, Y., Bengio, Y. and Hinton, G. (2015) Deep Learning. Nature, 521, 436-444. https://doi.org/10.1038/nature14539
Luo, C., Ji, J., Wang, Q., Chen, X. and Li, P. (2020) Channel State Information Prediction for 5G Wireless Communications: A Deep Learning Approach. IEEE Transactions on Network Science and Engineering, 7, 227-236. https://doi.org/10.1109/TNSE.2018.2848960
Huang, C.W., Chiang, C.T. and Li, Q. (2018) A Study of Deep Learning Networks on Mobile Traffic Forecasting. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Montreal, QC, 8-13 October 2017, 1-6. https://doi.org/10.1109/PIMRC.2017.8292737
Chen, L., Yang, D., Zhang, D., Wang, C., Li, J. and Nguyen, T.M.T. (2018) Deep Mobile Traffic Forecast and Complementary Base Station Clustering for C-RAN Optimization. Journal of Network and Computer Applications, 121, 59-69. https://doi.org/10.1016/j.jnca.2018.07.015
Zhou, Y., Fadlullah, Z.M., Mao, B. and Kato, N. (2018) A Deep-Learning-Based Radio Resource Assignment Technique for 5G Ultra Dense Networks. IEEE Network, 32, no. 6, 28-34. https://doi.org/10.1109/MNET.2018.1800085
Brito, J.M.C. (2016) Trends in Wireless Communications towards 5G Networks—The Influence of e-Health and IoT Applications. 2016 International Multidisciplinary Conference on Computer and Energy Science, Split, 13-15 July 2016, 1-7.
Ahad, A., Tahir, M., Sheikh, M.A., Ahmed, K.I., Mughees, A. and Numani, A. (2020) Technologies Trend towards 5G Network for Smart Health-Care Using IoT: A Review. Sensors (Switzerland), 20, Article 4047. https://doi.org/10.3390/s20144047
Sundaravadivel, P., et al. (2018) Everything You Wanted to Know about Smart Health Care: Evaluating the Different Technologies and Components of the Internet of Things for Better Health. IEEE Consumer Electronics Magazine, 7, 19-28.
West, D.M. (2016) How 5G Technology Enables the Health Internet of Things. Center Technol. Innov., Brookings, Washington DC, USA, Tech. Rep., 1-20. https://www.brookings.edu/research/how-5g-technology-enables-the-health-internet-of-things/ https://www.brookings.edu/wp-content/uploads/2016/07/5G-Health-Internet-of-Things_West.pdf
Magsi, H., Sodhro, A.H., Chachar, F.A., Abro, S.A.K., Sodhro, G.H. and Pirbhulal, S. (2018) Evolution of 5G in Internet of Medical Things. 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), Sukkur, 3-4 March 2018, 1-7. https://doi.org/10.1109/ICOMET.2018.8346428
Karako, K., Song, P., Chen, Y. and Tang, W. (2020) Realizing 5G- and AI-Based Doctor-to-Doctor Remote Diagnosis: Opportunities, Challenges, and Prospects. BioScience Trends, 14, 314-317. https://doi.org/10.5582/bst.2020.03364
Adinoyi, A., Aljamae, M. and Aljlaoud, A. (2022) The Future of Broadband Connectivity: Terrestrial Networks vs Satellite Constellations. International Journal of Communications, Network and System Sciences, 15, 53-66. https://doi.org/10.4236/ijcns.2022.155005
Hameed, K., Bajwa, I.S., Sarwar, N., Anwar, W., Mushtaq, Z. and Rashid, T. (2021) Integration of 5G and Block-Chain Technologies in Smart Telemedicine Using IoT. Journal of Healthcare Engineering, 2021, Article ID: 8814364. https://doi.org/10.1155/2021/8814364
Selem, E., Fatehy, M. and El-Kader, S.M.A. (2019) E-Health Applications over 5G Networks: Challenges and State of the Art. 2019 6th International Conference on Advanced Control Circuits and Systems (ACCS) & 2019 5th International Conference on New Paradigms in Electronics & information Technology (PEIT), Hurgada, 17-20 November 2019, 111-118. https://doi.org/10.1109/ACCS-PEIT48329.2019.9062841
Latif, S., Qadir, J., Farooq, S. and Imran, M.A. (2017) How 5G Wireless (and Concomitant Technologies) Will Revolutionize Healthcare? Future Internet, 9, Article 93. https://doi.org/10.3390/fi9040093
Li, D. (2019) 5G and Intelligence Medicine—How the Next Generation of Wireless Technology Will Reconstruct Healthcare? Precision Clinical Medicine, 2, 205-208. https://doi.org/10.1093/pcmedi/pbz020
Dhinesh Kumar, R. and Chavhan, S. (2022) Shift to 6G: Exploration on Trends, Vision, Requirements, Technologies, Research, and Standardization Efforts. Sustainable Energy Technologies and Assessments, 54, Article ID: 102666. https://doi.org/10.1016/j.seta.2022.102666
Le, T.V., Lu, C.F., Hsu, C.L., Do, T.K., Chou, Y.F. and Wei, W.C. (2022) A Novel Three-Factor Authentication Protocol for Multiple Service Providers in 6G-Aided Intelligent Healthcare Systems. IEEE Access, 10, 28975-28990. https://doi.org/10.1109/ACCESS.2022.3158756
Nguyen, D.C., et al. (2022) 6G Internet of Things: A Comprehensive Survey. IEEE Internet of Things Journal, 9, 359-383. https://doi.org/10.1109/JIOT.2021.3103320
Gupta, R., Shukla, A. and Tanwar, S. (2021) BATS: A Blockchain and AI-Empowered Drone-Assisted Telesurgery System towards 6G. IEEE Transactions on Network Science and Engineering, 8, 2958-2967. https://doi.org/10.1109/TNSE.2020.3043262
El Khatib, M., Al-Nakeeb, A. and Ahmed, G. (2019) Integration of Cloud Computing with Artificial Intelligence and Its Impact on Telecom Sector—A Case Study. iBusiness, 11, 1-10. https://doi.org/10.4236/ib.2019.111001
Gill, S.S. (2022) A Manifesto for Modern Fog and Edge Computing: Vision, New Paradigms, Opportunities, and Future Directions. In: Nagarajan, R., Raj, P. and Thirunavukarasu, R., Eds., Operationalizing Multi-Cloud Environments. EAI/Springer Innovations in Communication and Computing, Springer, Cham, 237-253. https://doi.org/10.1007/978-3-030-74402-1_13
Wu, Y.S., Chen, C.W. and Samani, H. (2016) Development of Wireless Charging Robot for Indoor Environment Based on Probabilistic Roadmap. In: Ronzhin, A., Rigoll, G. and Meshcheryakov, R., Eds., Interactive Collaborative Robotics. ICR 2016. Lecture Notes in Computer Science, Vol. 9812, Springer, Cham, 55-62. https://doi.org/10.1007/978-3-319-43955-6_8
Dang, S., Amin, O., Shihada, B. and Alouini, M.-S. (2019) What Should 6G Be? TechRxiv. https://doi.org/10.36227/techrxiv.10247726
Siriwardhana, Y., Gür, G., Ylianttila, M. and Liyanage, M. (2021) The Role of 5G for Digital Healthcare against COVID-19 Pandemic: Opportunities and Challenges. ICT Express, 7, 244-252. https://doi.org/10.1016/j.icte.2020.10.002
Hall, J.L. and McGraw, D. (2014) For Telehealth to Succeed, Privacy and Security Risks Must Be Identified and Addressed. Health Affairs, 33, 216-221. https://doi.org/10.1377/hlthaff.2013.0997
Ng, C.L., Reaz, M.B.I. and Chowdhury, M.E.H. (2020) A Low Noise Capacitive Electromyography Monitoring System for Remote Healthcare Applications. IEEE Sensors Journal, 20, 3333-3342. https://doi.org/10.1109/JSEN.2019.2957068
Sengupta, S. and Bhunia, S.S. (2020) Secure Data Management in Cloudlet Assisted IoT Enabled e-Health Framework in Smart City. IEEE Sensors Journal, 20, 9581-9588. https://doi.org/10.1109/JSEN.2020.2988723
Chen, B., et al. (2021) A Security Awareness and Protection System for 5G Smart Healthcare Based on Zero-Trust Architecture. IEEE Internet of Things Journal, 8, 10248-10263. https://doi.org/10.1109/JIOT.2020.3041042
Rupprecht, D., Dabrowski, A., Holz, T., Weippl, E. and Popper, C. (2018) On Security Research towards Future Mobile Network Generations. IEEE Communications Surveys and Tutorials, 20, 2518-2542. https://doi.org/10.1109/COMST.2018.2820728
Akhunzada, A., ul Islam, S. and Zeadally, S. (2020) Securing Cyberspace of Future Smart Cities with 5G Technologies. IEEE Network, 34, 336-342. https://doi.org/10.1109/MNET.001.1900559