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Future Edge: Journal of Progressive Research

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Revolutionizing Telehealth with Nanosensors: Transforming Diagnosis, Monitoring, and Remote Care

Published in October 2025 (Vol. 1, Issue 1, 2025)

Revolutionizing Telehealth with Nanosensors: Transforming Diagnosis, Monitoring, and Remote Care - Issue cover

Abstract

Nanosensors are redefining telehealth by combining advanced nanotechnology with computational intelligence to enable real-time monitoring, precise diagnosis and automated treatment support. Their integration with Internet of Medical Things (IoMT) architecture allow seamless collection, transmission and analysis of physiological data through cloud platform and edge computing system. These networks helps continuous remote patient monitoring, early anomaly detection using AI-driven analysis and reduced dependence on hospital-centric care model. The implementation of nanosensors in teleICU and hospital- at-home frameworks also addresses scalability and resource optimization in healthcare systems. However, challenges such as secure data transmission, interoperability between heterogeneous devices, fault tolerance and privacy protection must be resolved to ensure reliable deployment. This paper presents a comprehensive review of nanosensor technologies from computational perspective, detailing their communication protocols, data processing pipelines and cybersecurity requirement. Future research direction emphasize energy-efficient sensor design, federated learning for distributed analytics and blockchain-enabled security model for trustworthy remote healthcare ecosystems.

References

  1. [1]S. I. Khondakar, A. R. Chowdhury, and M. U. Islam, “Nanotechnology and nanosensors in personalized healthcare: A comprehensive review,” Sensing and Bio-Sensing Research, vol. 47, Feb. 2025, Art. no. 100648.
  2. [2]H. Sharma, P. Singh, and L. Verma, “Nanosensors in healthcare: Transforming real-time monitoring and disease management with cutting-edge nanotechnology,” RSC Pharmaceutics, vol. 2, Jun. 2025.
  3. [3]M. S. Mahmud, M. H. Kaiser, and A. Hussain, “A review of nanosensor applications in Internet of Medical Things (IoMT): Architecture, data processing, and security,” IEEE Access, vol. 12, pp. 11920–11935, Feb. 2024.
  4. [4]L. Zhou et al., “Security and privacy challenges in healthcare nanosensor networks,” IEEE Transactions on Nanobioscience, vol. 23, no. 3, pp. 245–254, Mar. 2024.
  5. [5]N. Patel and R. K. Gupta, “Blockchain-enabled secure communication for telehealth IoMT systems,” in Proc. IEEE Global Communications Conference (GLOBECOM), 2023, pp. 5590–5596.
  6. [6]J. Kim and D. H. Kim, “Wearable bioelectronics for remote patient monitoring: Advances and challenges,” IEEE Reviews in Biomedical Engineering, vol. 17, pp. 48–62, Jan. 2024.
  7. [7]A. K. Verma, P. Kumar, and M. S. A. Jan, “Federated learning for healthcare IoT systems: A secure and scalable framework,” IEEE Internet of Things Journal, vol. 11, no. 4, pp. 6912–6925, Feb. 2024.
  8. [8]G. C. Mukherjee and S. S. Saha, “Energy-efficient nanosensor designs for continuous healthcare monitoring,” in Proc. IEEE International Symposium on Circuits and Systems (ISCAS), 2023, pp. 213–218.
  9. [9]T. H. Lee and Y. C. Lee, “Nanomaterial-based sensors for biomedical applications,” IEEE Nanotechnology Magazine, vol. 18, no. 2, pp. 22–31, Apr. 2024.
  10. [10]S. K. Singh and V. Chaurasiya, “Edge computing for real-time healthcare monitoring systems,” IEEE Access, vol. 11, pp. 41256–41267, May 2023.
  11. [11]P. Thukral, S. R. Joshi, and A. Sharma, “Cloud-edge hybrid architectures for IoMT-based nanosensor networks,” in Proc. IEEE International Conference on Smart Healthcare (ICSH), 2023, pp. 98–104.
  12. [12]Y. Wang et al., “Artificial intelligence for nanosensor data analysis in personalized healthcare,” IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 8, pp. 3648–3657, Aug. 2023.
  13. [13]M. B. Mollah et al., “Privacy-preserving healthcare data sharing using blockchain and secure multiparty computation,” IEEE Access, vol. 10, pp. 87236–87249, Jul. 2022.
  14. [14]S. Sundararaman et al., “Communication protocols for nanosensor networks in IoT healthcare,” IEEE Communications Surveys & Tutorials, vol. 25, no. 2, pp. 1230–1251, 2023.
  15. [15]R. D. Misra and B. Patil, “Nanobiosensors for early detection of cancer: A computational approach,” IEEE Transactions on Nanobioscience, vol. 21, no. 4, pp. 512–520, Oct. 2023.
  16. [16]A. R. Javed and H. Jalil, “Secure IoMT systems using AI-based anomaly detection,” IEEE Internet of Things Magazine, vol. 6, no. 3, pp. 22–29, Sep. 2023.
  17. [17]C. H. Wu, Y. F. Lee, and J. C. Wang, “IoMT device authentication and lightweight encryption for nanosensor networks,” IEEE Sensors Journal, vol. 24, no. 9, pp. 15123–15132, May 2024.
  18. [18]L. Dzamesi and N. Elsayed, “Security vulnerabilities of IoMT against malware attacks and DDoS,” IEEE Access, vol. 13, pp. 11120–11135, Jan. 2025.
  19. [19]A. Ghubaish et al., “Recent advances in Internet of Medical Things (IoMT) systems security,” IEEE Access, vol. 11, pp. 9256–9274, Feb. 2023.
  20. [20]A. Awad Abdellatif et al., “Edge computing for smart health: Context-aware approaches, opportunities, and challenges,” IEEE Network, vol. 35, no. 5, pp. 38–45, Sep. 2021.
  21. [21]S. Tuli et al., “EdgeLens: Deep learning-based object detection in integrated IoT, fog, and cloud computing environments,” IEEE Transactions on Industrial Informatics, vol. 17, no. 7, pp. 4953–4962, Jul. 2021.
  22. [22]I. Nisarga et al., “Hybrid IoT-based hazard detection system for healthcare facilities,” IEEE Access, vol. 8, pp. 19520–19532, 2020.
  23. [23]W. Iqbal et al., “IoT security requirements, challenges, and countermeasures via software-defined security,” IEEE Internet of Things Journal, vol. 7, no. 9, pp. 9248–9270, 2020.
  24. [24]P. Chanal and M. S. Kakkasageri, “A provably-secure authenticated key agreement protocol for remote patient monitoring IoMT,” Journal of Systems Architecture, vol. 138, pp. 102914, 2023.
  25. [25]M. H. Ansari et al., “Sensor-cloud integration for healthcare monitoring: Trends and challenges,” IEEE Sensors Journal, vol. 19, no. 23, pp. 11322–11330, Dec. 2019.
  26. [26]F. B. Shaikh et al., “Review of Internet of Medical Things systems: Insights into non-functional factors,” IEEE Access, vol. 13, pp. 4512–4530, Jan. 2025.
  27. [27]T. Haque et al., “DeepCAD: Deep neural network-based anomaly detection in smart healthcare systems,” in Proc. IEEE ICDH, 2022, pp. 182–189.
  28. [28]T. Haque et al., “BIOCAD: Bio-inspired classification and anomaly detection in digital healthcare systems,” in Proc. IEEE ICDH, 2021, pp. 159–167.
  29. [29]K. Mehta et al., “BFT-IOMT: Blockchain-based trust mechanism to mitigate Sybil attacks in IoMT,” Sensors, vol. 23, no. 12, pp. 1–14, Jun. 2023.
  30. [30]J. Suhonen et al., “Low-power wireless sensor networks: Protocols, services and applications,” Springer Journal of Wireless Networks, vol. 18, no. 2, pp. 73–84, 2012.
  31. [31]R. K. Nambiar and P. Agarwal, “Integration of cloud computing and IoT: A survey,” Future Generation Computer Systems, vol. 63, pp. 365–378, 2016.
  32. [32]G. Xu et al., “Self-detection and self-diagnosis methods for intelligent sensor networks in healthcare,” IEEE Sensors Journal, vol. 21, no. 14, pp. 15623–15631, Jul. 2021.
  33. [33]D. F. Gomes et al., “Privacy and interoperability in cloud-based nanosensor systems,” IEEE Cloud Computing, vol. 10, no. 3, pp. 65–75, May 2023.
  34. [34]A. Panwar et al., “5G-enabled IoMT for smart healthcare: Challenges and future directions,” IEEE Network, vol. 36, no. 4, pp. 84–91, Aug. 2022.
  35. [35]N. A. Ali et al., “Lightweight cryptography solutions for nanosensor networks in medical applications,” IEEE Access, vol. 10, pp. 116452–116465, Oct. 2022.

Authors (2)

Prof. Mahesh V. Shastri

Padm. Dr. V. B. Kolte College ...

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Prof. Ketki R. Tayde

Padm. Dr. V. B. Kolte College ...

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Article Information

JPR110003

JPR-01-000003

16-25

2025-10-10

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How to Cite

Prof. Mahesh V. Shastri & Prof. Ketki R. Tayde (2025). Revolutionizing Telehealth with Nanosensors: Transforming Diagnosis, Monitoring, and Remote Care. Future Edge: Journal of Progressive Research, 1(1), 16-25. https://jpr.scholarjms.com/articles/JPR110003

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