Cyber-Physical Systems Integration in Healthcare: AI-Enabled Decision Support Systems
DOI:
https://doi.org/10.56294/hl2025659Keywords:
Cyber, Physical System, Integration, Healthcare, Decision, Support Systems, Artificial Intelligence, Intrusion, Quantum, Predictive, Detection SystemAbstract
Abstract structured in: The convergence of Cyber-Physical Systems (CPS) and healthcare is bringing about a transformation in the delivery of patient care by bridging the gap between the digital and physical realms. By utilizing modern technologies, these systems make it possible to make intelligent decisions and gain insights that are driven by data in real time.
Introduction: The complexity of data integration, the mitigation of sophisticated cyber threats, and the guaranteeing of system scalability within a variety of healthcare infrastructures are among the most significant obstacles.
Methods: This research presents the Artificial Intelligence-Enabled Intrusion Quantum Predictive Detection System (AI-IQPDS), an innovative approach that is intended to improve the operational reliability of healthcare CPS, as well as the security and predictive analytics capabilities of the system. AI-IQPDS combine quantum computing and machine learning to provide accurate intrusion detection and predictive decision assistance. Intelligent patient monitoring systems powered by AI can optimize hospital resource management, transmit data securely between connected devices, and detect emergencies early working.
Results: Simulation results show that the system outperforms modern techniques in terms of precision of detection, speed of processing, and reduction of false-positives. The results of this research demonstrate the revolutionary possibilities of using CPS driven by AI in healthcare.
Conclusion: Healthcare ecosystems that are both intelligent and scalable may be possible as a result of this integration, which might lead to better efficiency, security, and patient outcomes.
References
1. Ramamoorthy SK, Sindhu L, Valarmathi K, Umaeswari P. Digital Twin-Driven Intrusion Detection for IoT and Cyber-Physical System. In2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS) 2024 Aug 23; 1-8. IEEE.
2. Alohali MA, Al-Wesabi FN, Hilal AM, Goel S, Gupta D, Khanna A. Artificial intelligence enabled intrusion detection systems for cognitive cyber-physical systems in industry 4.0 environment. Cognitive Neurodynamics. 2022 Oct;16(5):1045-57.
3. Shaikh TA, Rasool T, Verma P. Machine intelligence and medical cyber-physical system architectures for smart healthcare: Taxonomy, challenges, opportunities, and possible solutions. Artificial Intelligence in Medicine. 2023 Dec 1;146:102692.
4. Trivedi S, Aggarwal V, Rastogi R. Enhancing the Power of Cyber-Physical Systems Enabled with AI: An Introduction—Facts and Myths along with Modular Approach. Artificial Intelligence Solutions for Cyber-Physical Systems.:1-39.
5. Amiri Z. Leveraging AI-Enabled Information Systems for Healthcare Management. Journal of Computer Information Systems. 2024 Oct 17:1-28.
6. Gull KC, Kanakaraddi SG, Chikaraddi AK, Gull SC. A Scoping Review of Intelligent Cyber-Physical Systems in Healthcare. Intelligent Cyber-Physical Systems for Healthcare Solutions: From Theory to Practice. 2024 Dec 8:1-23.
7. Amiri Z, Taghavirashidizadeh A, Khorrami P. AI-driven decision-making in healthcare information systems: A comprehensive review. Journal of Systems and Software. 2025 Apr 24:112470.
8. Soms N, Azariya DS, Jeba Emilyn J, Saravanan A. Ensuring Ethical Standards and Equity in Explainable Artificial Intelligence Applications Within Healthcare. In International Conference on Artificial Intelligence and Smart Energy 2024 Mar 22:369-380.
9. Kaur K, Dhir R, Ouaissa M. SSAMH–A Systematic Survey on AI‐Enabled Cyber Physical Systems in Healthcare. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation. 2023 May 2:277-97.
10. Haldorai A. A review on artificial intelligence in internet of things and cyber physical systems. Journal of Computing and Natural Science. 2023 Jan;3(1):012-23.
11. Sodhro AH, Zahid N. AI-enabled framework for fog computing driven e-healthcare applications. Sensors. 2021 Dec 1;21(23):8039.
12. Umar S. Cyber-Physical Systems and Advanced Computing: Bridging the Gap Between Digital and Physical Worlds. Journal of Advanced Computing Systems. 2022 Oct 7;2(10):1-9.
13. Verma A, Gupta A, Katiyar K. Concerns and Future Prospects of Medical Devices and Sensors for Intelligent Cyber-Physical Healthcare Systems. InIntelligent Cyber-Physical Systems for Healthcare Solutions 2024 (pp. 111-133). Springer, Singapore.
14. Nweke LO, Yayilgan SY. Opportunities and Challenges of Using Artificial Intelligence in Securing Cyber-Physical Systems. Artificial Intelligence for Security: Enhancing Protection in a Changing World. 2024 Apr 17:131-64.
15. Xu W, Xu H, Zhang J. Cyber Physical System Based Smart Healthcare System with Deep Learning Architectures with Data Analytics. Wireless Personal Communications. 2024 Jun 5:1-20.
16. Gunasekaran K, Kumar VV, Kaladevi AC, Mahesh TR, Bhat CR, Venkatesan K. Smart decision-making and communication strategy in industrial Internet of Things. IEEE Access. 2023 Mar 16; 11:28222-35.
17. Mhapsekar RU, Umrani MI, Faizan M, Ali O, Abraham L. Building trust in AI-driven decision making for cyber-physical Systems (CPS): A comprehensive review. In2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA) 2024 Sep 10 (pp. 1-8). IEEE.
18. Arbi A, Israr M. Empowering cyber-physical systems through ai-driven fusion for enhanced health assessment. International Journal of Data Informatics and Intelligent Computing. 2024 Aug 31;3(3):16-23.
19. Srivastava J, Routray S. Cyber-Physical System in AI-Enabled Smart Healthcare System. InSecure and Smart Cyber-Physical Systems (pp. 118-134). CRC Press.
20. Khater HM, Sallabi F, Serhani MA, Barka E, Shuaib K, Tariq A, Khayat M. Empowering Healthcare with Cyber-Physical System–A Systematic Literature Review. IEEE Access. 2024 May 30.
21. Jayanthi J. Programming Language Support for Implementing Machine Learning Algorithms. InResearch Anthology on Machine Learning Techniques, Methods, and Applications 2022: 528-547. IGI Global Scientific Publishing.
22. Kokilavani T, Kannan K, Yamuna KS, Sangeetha B, Vetrivel M. 3 Machine in IoMT Learning for Decision Support Systems. Technological Advancement in Internet of Medical Things and Blockchain for Personalized Healthcare: Applications and Use Cases. 2024 May 8.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Archana Das , Padmavathy. S, Shilpa NS, R. Nagendran, Srithar. S, G. Nagalalli, S. Alagumuthukrishnan (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
