TARU PUBLICATIONS
Journal of Discrete Mathematical Sciences and Cryptography cover

Journal of Discrete Mathematical Sciences and Cryptography

(Since 1998)
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

CiteScore 2025: 2.7 (Q1)

Powered by:Powered by

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
submissions@tarupublications.com
Taru Online First Current IssueSpecial IssuesBrowse all Issues
Journal of Discrete Mathematical Sciences and Cryptography
Open Access Research Article

Design of an IoT-based smart healthcare eco system for precise ageing illness detection and prognosis

* , ,

* Corresponding author · click or hover a name for details

pp. 1305–1316Vol. 26Issue 5August 2023DOI: 10.47974/JDMSC-1746 Crossmark XML
Published Online:
09 Sep 2023
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-1746
Pages:
1305–1316

Abstract

The article aims to provide a comprehensive review of the current state of smart healthcare systems, focusing on important topics such as the use of wearables and smartphones for health monitoring, the application of AI and machine learning for illness detection, and the integration of assistive frameworks like social robots for ambient-supported living. One of the key aspects discussed in the study is the software integration architectures required for the development of smart healthcare systems and the seamless integration of data. Analytics and various AI technologies are utilized in conjunction to create these systems. The article examines the different approaches employed in the development of these systems, highlighting the contributions of each framework, the overall functioning methodology, performance outputs, and comparative advantages and limitations. Moreover, the article also addresses current research challenges and identifies prospective future directions. It emphasizes the shortcomings of existing smart healthcare systems and proposes strategies for introducing innovative frameworks to overcome these limitations. The analysis aims to provide detailed insights into recent advancements in smart healthcare systems, enabling specialists to contribute to the field with their expertise. Overall, the article serves as a valuable resource for understanding the current landscape of smart healthcare systems, shedding light on recent breakthroughs, and encouraging further research and development in this rapidly evolving field.

Keywords

Smart healthcareInternet of ThingsArtificial intelligenceMachine learningEarly detectionDisease detection

Subject Classifications

Primary 68T05Secondary 68U35

References

[1] A. A. Nancy, D. Ravindran, P. M. D. Raj Vincent, K. Srinivasan, and D. Gutierrez Reina, “IoT-Cloud-Based Smart Healthcare Monitoring System for Heart Disease Prediction via Deep Learning,” Electronics, vol. 11, no. 15, p. 2292 (Jul. 2022), doi: 10.3390/electronics11152292.
[2] S. Yu and J. Wang, “An empirical study on the model of aged home-care service process improvement for the elders,” J. Inf. Optim. Sci., vol. 41, no. 5, pp. 1269–1290 (Jul. 2020), doi: 10.1080/02522667.2020.1721603.
[3] C.-Y. Liu et al., “Impacts of influenza vaccination policy for the elderly and the SARS epidemic on influenza-like illness in Taiwan,” J. Stat. Manag. Syst., vol. 12, no. 3, pp. 531–54, (May 2009), doi: 10.1080/09720510.2009.10701405.
[4] A. Kumari and P. Singh, “Impact of counseling on psychological health during lockdown of Covid-19,” J. Stat. Manag. Syst., vol. 24, no. 1, pp. 53–65 (Jan. 2021), doi: 10.1080/09720510.2020.1833448.
[5] Y. Qin, X. Li, J. Wu, and K. Yu, “A management method of chronic diseases in the elderly based on IoT security environment,” Comput. Electr. Eng., vol. 102, p. 108188 (Sep. 2022), doi: 10.1016/j.compeleceng.2022.108188.
[6] N. Semwal, M. Mukherjee, C. Raj, and W. Arif, “An IoT based smart e-health care system,” J. Inf. Optim. Sci., vol. 40, no. 8, pp. 1787–1800 (Nov. 2019), doi: 10.1080/02522667.2019.1703269.
[7] D. Mala, A. Anand, N. K. Tiwari, and M. Arvindhan, “Fog computing & IoT based smart healthcare system for detecting heart related problem,” p. 020060 (2022). doi: 10.1063/5.0095237.
[8] A. Krishan, C. Ashoda, D. Madhumali, and G. Pradeep, “Smart Health Care System for Elders’ Home to Monitor Physical and Mental Health in a Controlled Environment,” pp. 487–502 (2023). doi: 10.1007/978-981-19-4676-9_42.
[9] A. Kumar, R. Kumar, and S. S. Sodhi, “A novel privacy preserving blockchain based secure storage framework for electronic health records,” J. Inf. Optim. Sci., vol. 43, no. 3, pp. 549–570 (Apr. 2022), doi: 10.1080/02522667.2022.2042092.
[10] P. Pandey and R. Litoriya, “Securing and authenticating healthcare records through blockchain technology,” Cryptologia, vol. 44, no. 4, pp. 341–356 (2020), doi: 10.1080/01611194.2019.1706060.
[11] P. Pandey and R. Litoriya, “Securing E-health networks from counterfeit medicine penetration using Blockchain,” Wirel. Pers. Commun., vol. 117, pp. 7–25 (2020), doi: 10.1007/s11277-020-07041-7.
[12] S. Soner, R. Litoriya, and P. Pandey, “Integrating Blockchain Technology with IoT and ML to Avoid Road Accidents Caused by Drunk Driving,” Wirel. Pers. Commun. (Apr. 2022), doi: 10.1007/s11277-022-09695-x.
[13] I. Pavan Kumar, R. Mahaveerakannan, K. Praveen Kumar, I. Basu, T. C. Anil Kumar, and M. Choche, “A Design of Disease Diagnosis based Smart Healthcare Model using Deep Learning Technique,” in 2022 International Conference on Electronics and Renewable Systems (ICEARS), pp. 1444–1449 (Mar. 2022). doi: 10.1109/ICEARS53579.2022.9752063.
[14] A. Rahman et al., “Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues,” Cluster Comput. (Aug. 2022), doi: 10.1007/s10586-022-03658-4.
[15] Henry Okemiri, A. Uzoma, and N. Christopher, “Internet of Things based Framework for Smart Healthcare Using Hybrid Machine Learning,” Preprint (2022), doi: 10.21203/rs.3.rs-1428239/v1.
[16] F. J. Abdullayeva, “Internet of Things-based healthcare system on patient demographic data in Health 4.0,” CAAI Trans. Intell. Technol., vol. 7, no. 4, pp. 644–657 (Dec. 2022), doi: 10.1049/cit2.12128.
[17] V. Hayyolalam, M. Aloqaily, O. Ozkasap, and M. Guizani, “Edge Intelligence for Empowering IoT-Based Healthcare Systems,” IEEE Wirel. Commun., vol. 28, no. 3, pp. 6–14 (Jun. 2021), doi: 10.1109/MWC.001.2000345.
[18] M. Gupta, G. Chaudhary, and V. H. C. de Albuquerque, Smart Healthcare Monitoring Using IoT with 5G. Boca Raton: CRC Press (2021). doi: 10.1201/9781003171829.
[19] K. C. Suneetha, R. Shanmuka Shalini, V. Kumar Vadladi, and M. Mounica, “WITHDRAWN: Disease prediction and diagnosis system in cloud based IoT: A review on deep learning techniques,” Mater. Today Proc. (Oct. 2020), doi: 10.1016/j.matpr.2020.09.519.
[20] O. Taiwo and A. E. Ezugwu, “Smart healthcare support for remote patient monitoring during covid-19 quarantine,” Informatics Med. Unlocked, vol. 20, p. 100428 (2020), doi: 10.1016/j.imu.2020.100428.
[21]A. Souri, M. Y. Ghafour, A. M. Ahmed, F. Safara, A. Yamini, and M. Hoseyninezhad, “A new machine learning-based healthcare monitoring model for student’s condition diagnosis in Internet of Things environment,” Soft Comput., vol. 24, no. 22, pp. 17111–17121 (Nov. 2020), doi: 10.1007/s00500-020-05003-6.
[22] D. Kumar and U. Batra, “An ensemble algorithm for breast cancer histopathology image classification,” J. Stat. Manag. Syst., vol. 23, no. 7, pp. 1187–1198 (Oct. 2020), doi: 10.1080/09720510.2020.1818451.
[23] R. Soni, S. Riyal, and M. Tomar, “Concern, perceived risk and attitudes of the general public towards COVID-19: Special reference to Delhi-NCR,” J. Stat. Manag. Syst., vol. 24, no. 2, pp. 229–249 (Feb. 2021), doi: 10.1080/09720510.2020.1838063.
[24] S. U. Amin and M. S. Hossain, “Edge Intelligence and Internet of Things in Healthcare: A Survey,” IEEE Access, vol. 9, pp. 45–59 (2021), doi: 10.1109/ACCESS.2020.3045115.
[25] M. lata Sahu, M. Atulkar, and M. K. Ahirwal, “Comprehensive Investigation on IoT based Smart HealthCare System,” in 2020 First International Conference on Power, Control and Computing Technologies (ICPC2T), pp. 325–330 (Jan. 2020). doi: 10.1109/ICPC2T48082.2020.9071442.
[26] S. Akhbarifar, H. H. S. Javadi, A. M. Rahmani, and M. Hosseinzadeh, “A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment,” Pers. Ubiquitous Comput. (Nov. 2020), doi: 10.1007/s00779-020-01475-3.
[27] M. Bhatia, S. Kaur, S. K. Sood, and V. Behal, “Internet of things-inspired healthcare system for urine-based diabetes prediction,” Artif. Intell. Med., vol. 107, p. 101913 (Jul. 2020), doi: 10.1016/j.artmed.2020.101913.
[28] C. Comito, D. Falcone, and A. Forestiero, “Current Trends And Practices In Smart Health Monitoring And Clinical Decision Support,” in 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 2577–2584 (Dec. 2020). doi: 10.1109/BIBM49941.2020.9313449.

Views: 212Downloads: 70Citations: 0