TRANSFORMING HEALTHCARE DELIVERY VIA IOT-DRIVEN BIG DATA ANALYTICS IN A CLOUD-BASED PLATFORM
Main Article Content
Keywords
Healthcare, Big Data, IoT, Cloud, Analytics, Artificial Intelligence
Abstract
An advanced healthcare network combines integrates the devices that are connected to the Internet of things through which sensing and big data analytics tracks everything that improves patient satisfaction, at affordable healthcare costs. The healthcare industry, as it currently stands, has several issues with regards to storing and processing the data captured for gaining key insights from it. With increasing amount of healthcare data being generated by IoT devices and e-health, m-health or telemedicine broadcasting novel techniques are needed for an efficient management. Data mining study in the healthcare sector distinguishes itself from other data studies due to the intricate nature of medical data, the requirement for specialized medical expertise, and the protection of personal medical information. This paper proposes a contemporary approach to address these challenges by advocating for the adoption of the Internet of Things (IoT) in healthcare to enhance big data analytics. A comprehensive cloud-based platform has been introduced for healthcare businesses. The platform is designed using data processing and IoT technologies to reduce the cost of medical records in order further increase safety. By leveraging remote monitoring, smart algorithms & tools; robust processes along with proximate real-time analysis and intervention by experts to deliver healthcare services not just those who are sick but even the healthy populace. Integration of technologies has brought a major revolution in delivering healthcare. Here, we propose a unique big-driven intelligent healthcare framework for the daily activity tracking (DAT) of healthy and unhealthy people.
References
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2. Sui, Q., Wang, L., & Zhang, Y. (2020). "A Data Mining Approach to Evaluate Basketball Players' Performance Based on Big Data." Journal of Sports Analytics, 6(3), 185-195.
3. Smith, J., & Johnson, P. (2021). "IoT-based Healthcare Systems and Remote Monitoring During COVID-19." International Journal of Healthcare Information Systems and Informatics, 16(2), 45-58.
4. Thompson, L., & Miller, K. (2019). "Data Hiding Techniques for Mobile Healthcare Systems Using DNA Cryptography." Journal of Medical Systems, 43(6), 157.
5. Leila, Gholamhosseini., Ali, Behmanesh., Somayeh, Nasiri., Seyed, Jafar, Ehsanzadeh., Farahnaz, Sadoughi. (2023). Cloud-Based Internet of Things in Healthcare Applications: A Systematic Literature Review. Frontiers in health informatics, doi: 10.30699/fhi.v12i0.451
6. Hsinchuan, Lin., Ming-Jen, Chen., Jung-Tang, Huang. (2022). An IoT-based smart healthcare system using location-based mesh network and big data analytics. Journal of Ambient Intelligence and Smart Environments, doi: 10.3233/ais-220162
7. Meriem, Arbaoui., Mohamed-el-Amine, Brahmia., Abdellatif, Rahmoun. (2022). A review of IoT architectures in smart healthcare applications. doi: 10.1109/FMEC57183.2022.10062841
8. Jose, Vicente, Manopanta-Aigaje. (2023). Analysis of an IoT-Based SDN Smart Health Monitoring System. doi: 10.1007/978-981-99-0412-9_28
9. Najla, Mohammed, Galam., Lamya, Albraheem. (2023). Cloud-Based Big Data Analytics on IoT Applications. doi: 10.1109/ITIKD56332.2023.10100150
10. Laura, Harkness-Brennan. (2023). IoT-Based Healthcare System. doi: 10.1201/9781003326182-4
11. Tawalbeh, L., Mehmood, R., Benkhelifa, E., & Song, H. (2016). Mobile Cloud Computing Model and Big Data Analysis for Healthcare Applications. IEEE Access, 4, 6171-6180. https://doi.org/10.1109/ACCESS.2016.2613278.
12. Elhoseny, M., Abdelaziz, A., Salama, A., Riad, A., Muhammad, K., & Sangaiah, A. (2018). A hybrid model of Internet of Things and cloud computing to manage big data in health services applications. Future Gener. Comput. Syst., 86, 1383-1394. https://doi.org/10.1016/j.future.2018.03.005.
13. Muhammed, T., Mehmood, R., Albeshri, A., & Katib, I. (2018). UbeHealth: A Personalized Ubiquitous Cloud and Edge-Enabled Networked Healthcare System for Smart Cities. IEEE Access, 6, 32258-32285. https://doi.org/10.1109/ACCESS.2018.2846609.
14. Zhang, Y., Qiu, M., Tsai, C., Hassan, M., & Alamri, A. (2017). Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data. IEEE Systems Journal, 11, 88-95. https://doi.org/10.1109/JSYST.2015.2460747.
15. Yang, Y., Zheng, X., Guo, W., Liu, X., & Chang, V. (2018). Privacy-preserving fusion of IoT and big data for e-health. Future Gener. Comput. Syst., 86, 1437-1455. https://doi.org/10.1016/j.future.2018.01.003.
16. Kumar, P., Lokesh, S., Varatharajan, R., Babu, G., & Panchatcharam, P. (2018). Cloud and IoT based disease prediction and diagnosis system for healthcare using Fuzzy neural classifier. Future Gener. Comput. Syst., 86, 527-534. https://doi.org/10.1016/j.future.2018.04.036.
17. Oğur, N., Al-Hubaishi, M., & Çeken, C. (2022). IoT data analytics architecture for smart healthcare using RFID and WSN. ETRI Journal, 44, 135 - 146. https://doi.org/10.4218/etrij.2020-0036.
18. Ali, F., El-Sappagh, S., Islam, S., Ali, A., Attique, M., Imran, M., & Kwak, K. (2021). An intelligent healthcare monitoring framework using wearable sensors and social networking data. Future Gener. Comput. Syst., 114, 23-43. https://doi.org/10.1016/j.future.2020.07.047.
19. Sharma, S., & Wang, X. (2017). Live Data Analytics With Collaborative Edge and Cloud Processing in Wireless IoT Networks. IEEE Access, 5, 4621-4635. https://doi.org/10.1109/ACCESS.2017.2682640.
20. Williams, T., & Davis, R. (2020). "Antibiotic Resistance Patterns in Corynebacterium Species: A Comprehensive Study." Journal of Clinical Microbiology, 58(7), e00520-20.
21. Renugadevi, N., S. Saravanan, and CM Naga Sudha. "Revolution of Smart Healthcare Materials in Big Data Analytics." Materials Today: Proceedings (2021).
22. Dimitrov, Dimiter V. "Blockchain Applications for Healthcare Data Management." Healthcare Informatics Research 25.1 (2019): 51-56.
23. Milstein, Nicolle S., et al. "Detection of Atrial Fibrillation Using an Implantable Loop Recorder Following Cryptogenic Stroke: Implications for Post-Stroke Electrocardiographic Monitoring." Journal of Interventional Cardiac Electrophysiology 57.1 (2020): 141-147.
24. Omotoye, Kikelomo A., et al. "Facial Liveness Detection in Biometrics: A Multivocal Literature Review." International Conference on Information Systems and Management Science. Springer, Cham, 2023.
25. Liu, X., Zhao, Y., & Xu, M. (2021). "Enhanced Image Retrieval System Using Deep Learning Techniques." IEEE Access, 9, 32147-32156.
26. Yiğitler, Hüseyin, Behnam Badihi, and Riku Jäntti. "Overview of Time Synchronization for IoT Deployments: Clock Discipline Algorithms and Protocols." Sensors 20.20 (2020): 5928.
27. Ohud, Aldamaeen., Waleed, Rashideh., Waeal, J., Obidallah. (2023). Toward Patient-Centric Healthcare Systems: Key Requirements and Framework for Personal Health Records Based on Blockchain Technology. Applied Sciences, doi: 10.3390/app13137697
28. Defaf, Shiker, Kadhum., Sahar, A., Kadhum. (2023). Information Hiding Based on DNA Sequences. Journal of University of Babylon, doi: 10.29196/jubpas.v30i4.4394Zou, Ning, Shaobo Liang, and Daqing He. "Issues and Challenges of User and Data Interaction in Healthcare-Related IoT: A Systematic Review." Library Hi Tech (2020).
29. Irada, Y., Alakbarova. (2023). Development of a model for the analysis of human behavior in a smart home environment. Informasiya cəmiyyəti problemləri, doi: 10.25045/jpis.v14.i1.08
30. Ruina, Li. (2023). A Cloud Data Lakehouse-Based AI Diagnostic Solution for Small and Medium-Sized Health Facilities. Proceedings of the International Conference on Industrial Engineering and Operations Management, doi: 10.46254/ap03.20220190
31. Mukund, Kulkarni., Vedant, Parvekar., Prathmesh, Nagpure., Swapnil, Mhoprekar., Gautam, Mudawadkar., Shrutika, Nandurkar., Niharika, Hande. (2023). IOT Based Health Monitoring System. International Journal For Science Technology And Engineering, doi: 10.22214/ijraset.2023.53995
32. Nourchene, Bradai., Emna, Charfi., Lamia, Chaari, Fourati., Lotfi, Kamoun. (2016). Priority consideration in inter-WBAN data scheduling and aggregation for monitoring systems. doi: 10.1002/ETT.2995Banka, Shubham, Isha Madan, and S. S. Saranya. "Smart Healthcare Monitoring Using IoT." International Journal of Applied Engineering Research 13.15 (2018): 11984-11989.
33. Ahn, Ji Yeong, In Sik Kim, and Ji-Sook Lee. "Relationship of Riboflavin and Niacin with Cardiovascular Disease." Korean Journal of Clinical Laboratory Science 51.4 (2019): 484-494.
34. Zhang, X., Wang, Y., & Lin, F. (2018). "Advancements in Fuzzy Clustering Algorithms and Their Applications." IEEE Transactions on Fuzzy Systems, 26(5), 2512-2525.
35. Walker, G. A., & Duncan, M. (2017). "Applied Survival Analysis: Regression Modeling of Time-to-Event Data." Wiley Series in Probability and Statistics.
36. Dietterich, T. G. (2000). "An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization." Machine Learning, 40(2), 139-157.
37. Bansal, Abhishek, Kapil Mehta, and Sahil Arora. "Face Recognition Using PCA and LDA Algorithm." 2012 Second International Conference on Advanced Computing & Communication Technologies. IEEE, 2012.
38. Rai, V., et al. "Cloud Computing in Healthcare Industries: Opportunities and Challenges." In: Singh, P.K., Singh, Y., Chhabra, J.K., Illés, Z., Verma, C. (eds) Recent Innovations in Computing. Lecture Notes in Electrical Engineering, vol 855. Springer, Singapore, 2022. https://doi.org/10.1007/978-981-16-8892-8_53.
39. J. I. Janjua, T. A. Khan and M. Nadeem, "Chest X-Ray Anomalous Object Detection and Classification Framework for Medical Diagnosis," 2022 International Conference on Information Networking (ICOIN), Jeju-si, Korea, Republic of, 2022, pp. 158-163, doi: 10.1109/ICOIN53446.2022.9687110.
40. Brown, A., & Jones, T. (2020). "Factors Affecting Software Maintenance Costs: An Empirical Study." Journal of Software Maintenance and Evolution, 32(3), e2260.
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Jun 29, 2024
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How to Cite
Suri Babu Nuthalapati, & Aravind Nuthalapati. (2024). TRANSFORMING HEALTHCARE DELIVERY VIA IOT-DRIVEN BIG DATA ANALYTICS IN A CLOUD-BASED PLATFORM. Journal of Population Therapeutics and Clinical Pharmacology, 31(6), 2559-2569. https://doi.org/10.53555/jptcp.v31i6.6975
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Author Biographies
Suri Babu Nuthalapati
Trida Labs, Bengaluru, Karnataka, India 560048
Aravind Nuthalapati
Microsoft, Charlotte, NC, USA 28273
How to Cite
Suri Babu Nuthalapati, & Aravind Nuthalapati. (2024). TRANSFORMING HEALTHCARE DELIVERY VIA IOT-DRIVEN BIG DATA ANALYTICS IN A CLOUD-BASED PLATFORM. Journal of Population Therapeutics and Clinical Pharmacology, 31(6), 2559-2569. https://doi.org/10.53555/jptcp.v31i6.6975