In the realm of IoT-based Intensive Care Unit (ICU) healthcare, the quest for precision and reliability in patient monitoring and treatment optimization is paramount. This study delves into the realm of advanced algorithms, particularly focusing on the Pelican Optimization Algorithm Long Short-Term Memory (POA-LSTM), known for its remarkable accuracy rates exceeding 95%. The POA-LSTM algorithm, fine-tuned through the Pelican Optimization Algorithm, emerges as a beacon of accuracy in ICU healthcare. By optimizing hyperparameters and leveraging the Pelican Optimization Algorithm's optimization prowess, POA-LSTM surpasses industry standards, offering unparalleled precision and recall rates. Its ability to make informed predictions and provide real-time insights significantly enhances the quality of patient care and clinical decision-making in ICU settings. Additionally, the study explores Context-Oriented Attention LSTM (COA-LSTM) and Particle Swarm Optimization Long Short-Term Memory (PSO-LSTM) algorithms, each contributing unique strengths to the landscape of IoT-based ICU healthcare. COA-LSTM's attention mechanism and PSO-LSTM's hyperparameter optimization further enrich the capabilities of predictive modeling and anomaly detection in critical care scenarios. Through the integration of these advanced algorithms, healthcare providers can harness the power of data-driven insights to revolutionize ICU healthcare, ensuring optimal patient outcomes and advancing the frontier of medical care in the digital age.
H. Wang, J. Huang, G. Wang, H. Lu and W. Wang, "Contactless Patient Care Using Hospital IoT: CCTV-Camera-Based Physiological Monitoring in ICU," in IEEE Internet of Things Journal, vol. 11, no. 4, pp. 5781-5797, 15 Feb.15, 2024, doi: 10.1109/JIOT.2023.3308477.
A. K M, S. Baskar, P. C and P. Yadav, "Computer Vision-Assisted Smart ICU Framework for Optimized Patient Care," in IEEE Sensors Letters, vol. 8, no. 1, pp. 1-4, Jan. 2024, Art no. 6001004, doi: 10.1109/LSENS.2023.3344472.
I. d. M. B. Filho, G. Aquino, R. S. Malaquias, G. Girão and S. R. M. Melo, "An IoT-Based Healthcare Platform for Patients in ICU Beds During the COVID-19 Outbreak," in IEEE Access, vol. 9, pp. 27262-27277, 2021, doi: 10.1109/ACCESS.2021.3058448.
N. A. Mudawi, "Integration of IoT and Fog Computing in Healthcare Based the Smart Intensive Units," in IEEE Access, vol. 10, pp. 59906-59918, 2022, doi: 10.1109/ACCESS.2022.3179704.
L. Caruccio, O. Piazza, G. Polese and G. Tortora, "Secure IoT Analytics for Fast Deterioration Detection in Emergency Rooms," in IEEE Access, vol. 8, pp. 215343-215354, 2020, doi: 10.1109/ACCESS.2020.3040914.
A. Aborujilah, A. -E. F. M. Elsebaie and S. A. Mokhtar, "IoT MEMS: IoT-Based Paradigm for Medical Equipment Management Systems of ICUs in Light of COVID-19 Outbreak," in IEEE Access, vol. 9, pp. 131120-131133, 2021, doi: 10.1109/ACCESS.2021.3069255.
M. Ammad et al., "A Novel Fog-Based Multi-Level Energy-Efficient Framework for IoT-Enabled Smart Environments," in IEEE Access, vol. 8, pp. 150010-150026, 2020, doi: 10.1109/ACCESS.2020.3010157.
A. Jaleel, T. Mahmood, M. A. Hassan, G. Bano and S. K. Khurshid, "Towards Medical Data Interoperability Through Collaboration of Healthcare Devices," in IEEE Access, vol. 8, pp. 132302-132319, 2020, doi: 10.1109/ACCESS.2020.3009783.
A. K. M. and S. Baskar, "LoRaWAN-Based Artificial Intelligence Intensive Care Unit Framework for Tracking Patients With Severe Pneumonia," in IEEE Sensors Letters, vol. 7, no. 12, pp. 1-4, Dec. 2023, Art no. 6009204, doi: 10.1109/LSENS.2023.3328608.
S. Chamideh, W. Tärneberg and M. Kihl, "A Safe and Robust Autonomous Intersection Management System Using a Hierarchical Control Strategy and V2I Communication," in IEEE Systems Journal, vol. 17, no. 1, pp. 50-61, March 2023, doi: 10.1109/JSYST.2022.3221620.
C. F. Frasser et al., "Fully Parallel Stochastic Computing Hardware Implementation of Convolutional Neural Networks for Edge Computing Applications," in IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 12, pp. 10408-10418, Dec. 2023, doi: 10.1109/TNNLS.2022.3166799.
H. E. Solayman and R. P. Qasha, "Portable Modeling for ICU IoT-based Application using TOSCA on the Edge and Cloud," 2022 International Conference on Computer Science and Software Engineering (CSASE), Duhok, Iraq, 2022, pp. 301-305, doi: 10.1109/CSASE51777.2022.9759684.
L. Nahar, S. S. Zafar and F. B. Rafiq, "IOT Based ICU Patient Health Monitoring System," 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, Canada, 2020, pp. 0407-0413, doi: 10.1109/IEMCON51383.2020.9284900.
A. S. R. M. Ahouandjinou, K. Assogba and C. Motamed, "Smart and pervasive ICU based-IoT for improving intensive health care," 2016 International Conference on Bioengineering for Smart Technologies (BioSMART), Dubai, United Arab Emirates, 2016, pp. 1-4, doi: 10.1109/BIOSMART.2016.7835599.
M. J. Hossain, M. A. Bari and M. M. Khan, "Development of an IoT Based Health Monitoring System for e-Health," 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2022, pp. 0031-0037, doi: 10.1109/CCWC54503.2022.9720825.
Durairaj S, Sridhar R. Task scheduling to a virtual machine using a multi‐objective mayfly approach for a cloud environment. Concurrency and Computation: Practice and Experience. 2022 Nov 1;34(24): e7236.
Acknowledgements
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Funding
No funding was received to assist with the preparation of this manuscript.
Ethics declarations
Conflict of interest
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Availability of data and materials
Data sharing is not applicable to this article as no new data were created or analysed in this study.
Author information
Contributions
All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.
Corresponding author
Thiyagu T
Thiyagu T
Department of Computer Science and Engineering, SRMIST, Kattankulathur, Tamil Nadu, India.
Open Access This article is licensed under a Creative Commons Attribution NoDerivs is a more restrictive license. It allows you to redistribute the material commercially or non-commercially but the user cannot make any changes whatsoever to the original, i.e. no derivatives of the original work. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
Cite this article
Thiyagu T and Krishnaveni S, “IoT Based ICU Healthcare: Optimizing Patient Monitoring and Treatment with Advanced Algorithms”, Journal of Machine and Computing, pp. 269-278, April 2024. doi: 10.53759/7669/jmc202404026.
