Smart Nanomaterials in Medicine: Integrating Ai and Iot for Real-Time Health Monitoring and Therapeutics
DOI:
https://doi.org/10.63682/jns.v14i32S.8763Keywords:
Intelligent Materials, Artificial Intelligence, Internet of Things, Medical Care, Monitoring In Real-Time, Quantitative ResearchAbstract
Background: The integration of smart nanomaterials with artificial intelligence (AI) and the Internet of Things (IoT) represents a transformative opportunity in healthcare, offering the potential to significantly enhance real-time health monitoring and therapeutic interventions. These emerging technologies promise more precise diagnostics, personalized treatment, and improved patient outcomes.
Objective: The purpose of this research is to explore the adoption of innovative nanomaterials, artificial intelligence(AI), and the Internet of Things in healthcare — perceptions, challenges, and possibilities. This paper looks at how these technologies help improve the efficiency of real-time health tracking and therapy and the possible hurdles that will prevent these instruments from working effectively.
Methods: A cross-sectional quantitative survey involved 250 participants including healthcare professionals, researchers, and technologists. A formalized questionnaire containing both the Likert scale and closed questions was used to gather the data on awareness of the technologies, perceived efficiency, and identified difficulties. Descriptive statistics, correlation analysis, and reliability tests were conducted in data analysis.
Results: According to the results obtained, there was a fair level of awareness of AI and IoT in healthcare, highlighting that data privacy was the most significant challenge (35%), followed by cost at 30%. The respondents are aware of the benefits in which the utilization of nanomaterials can be practical, specifically in monitoring health, since the results are not generally distributed according to the Shapiro-Wilk test. In addition, while finding a Cronbach's Alpha value of (0.13), it can be understood that there is poor internal consistency with the survey questions measured using the Likert scale format and poor survey design.
Conclusion: Intelligent materials, AI, and IoT have a wide range of applications in healthcare but have not been fully implemented because of privacy and cost issues. The only way to reduce this will be by gaining further awareness of the problems addressed here through education and improved data protection mechanisms. Therefore, there is a need to conduct more research and refine the methodologies that can successfully explain the attributes that characterize the adoption of the technologies into medical practice.
Downloads
Metrics
References
Afolalu, O. O., Akpor, O. A., Afolalu, S. A., & Afolalu, O. F. (2024). Internet of Things Applications in Health Systems' Equipment: Challenges and Trends in the Fourth Industrial Revolution. Paper presented at the 2024 International Conference on Science, Engineering, and Business for Driving Sustainable Development Goals (SEB4SDG).
Agyralides, G. (2024). The future of medicine: an outline attempt using state-of-the-art business and scientific trends. Frontiers in Medicine, 11, 1391727.
Apoorva, S., Nguyen, N.-T., & Rajan, S. K. (2024). Recent developments and future perspectives of microfluidics and smart technologies in wearable devices. Lab on a Chip.
Awotunde, J. B., Folorunso, S. O., Ajagbe, S. A., Garg, J., & Ajamu, G. J. (2022). AiIoMT: IoMT-based system-enabled artificial intelligence for enhanced smart healthcare systems. Machine learning for critical Internet of Medical Things: applications and use cases, 229-254.
Awotunde, J. B., Imoize, A. L., Jimoh, R. G., Adeniyi, E. A., Abdulraheem, M., Oladipo, I. D., & Falola, P. B. (2024). AIoMT enabling real-time monitoring of healthcare systems: security and privacy considerations. Handbook of Security and Privacy of AI-Enabled Healthcare Systems and Internet of Medical Things, 97-133.
Bag, S., & Mandal, D. Revolutionizing Healthcare: The Role of Biosensors in Modern Medicine.
Banerjee, A., Chakraborty, C., Kumar, A., & Biswas, D. (2020). Emerging trends in IoT and big data analytics for biomedical and health care technologies. Handbook of data science approaches for biomedical engineering, 121-152.
Banerjee, A., Chakraborty, C., & Rathi Sr, M. (2020). Medical imaging, artificial intelligence, Internet of things, wearable devices in terahertz healthcare technologies. In Terahertz biomedical and healthcare technologies (pp. 145-165): Elsevier.
Bommu, R. (2022). Advancements in Medical Device Software: A Comprehensive Review of Emerging Technologies and Future Trends. Journal of Engineering and Technology, 4(2), 1− 8-1− 8.
Chakraborty, C., Pani, S., Ahad, M. A., & Xin, Q. (2022). Implementation of Smart Healthcare Systems Using AI, IoT, and Blockchain: Academic Press.
Chen, M., Cui, D., Haick, H., & Tang, N. (2024). Artificial Intelligence‐Based Medical Sensors for Healthcare System. Advanced Sensor Research, 3(3), 2300009.
Chugh, V., Basu, A., Kaushik, A., Bhansali, S., & Basu, A. K. (2024). Employing nano-enabled artificial intelligence (AI)-based smart technologies for prediction, screening, and detection of cancer. Nanoscale, 16(11), 5458-5486.
Darwish, D. (2024). Machine Learning and IoT in Health 4.0. In IoT and ML for Information Management: A Smart Healthcare Perspective (pp. 235-276): Springer.
Dhanalakshmi, M., Das, K., Iqbal, M., Mohanan, V., & Dave, S. Artificial Intelligence–The Imperative Tool in Healthcare Innovations Employing Nanotechnology. In Nanomaterials and Point of Care Technologies (pp. 195-213): CRC Press.
Eswaran, U., ESWARAN, V., MURALI, K., & ESWARAN, V. (2024). ELEVATING HEALTHCARE: THE SYNERGY OF AI AND BIOSENSORS IN DISEASE MANAGEMENT. i-Manager's Journal on Artificial Intelligence & Machine Learning (JAIM), 2(1).
Ghosh, A., Nag, S., Gomes, A., Gosavi, A., Ghule, G., Kundu, A., . . . Srivastava, R. (2022). Applications of smart material sensors and soft electronics in healthcare wearables for better user compliance. Micromachines, 14(1), 121.
Haick, H., & Tang, N. (2021). Artificial intelligence in medical sensors for clinical decisions. ACS nano, 15(3), 3557-3567.
Haleem, A., Javaid, M., Singh, R. P., & Suman, R. (2022). Medical 4.0 technologies for healthcare: Features, capabilities, and applications. Internet of Things and Cyber-Physical Systems, 2, 12-30.
Haroun, A., Le, X., Gao, S., Dong, B., He, T., Zhang, Z., . . . Lee, C. (2021). Progress in micro/nano sensors and nano energy for future AIoT-based smart home applications. Nano Express, 2(2), 022005.
Hassan, S., Almaliki, M., Hussein, Z. A., Albehadili, H. M., Banoon, S. R., Al-Abboodi, A., & Al-Saady, M. (2023). Development of Nanotechnology by Artificial Intelligence: A Comprehensive Review. Journal of Nanostructures, 13(4), 915-932.
Hassani, F. A., Shi, Q., Wen, F., He, T., Haroun, A., Yang, Y., . . . Lee, C. (2020). Smart materials for smart healthcare–moving from sensors and actuators to self-sustained nano energy nanosystems. Smart Materials in Medicine, 1, 92-124.
Hoang, D. T., & Nguyen, D. N. (2024). CNN-FL for Biotechnology Industry Empowered by Internet-of-BioNano Things and Digital Twins. arXiv preprint arXiv:2402.00238.
Ibrahim, H. K. (2024). From Nanotech to AI: The Cutting-Edge Technologies Shaping the Future of Medicine. African Journal of Advanced Pure and Applied Sciences (AJAPAS), 410-427.
Israni, D. K., & Chawla, N. S. (2023). Human‐Machine Interaction in Leveraging the Concept of Telemedicine. Human‐Machine Interface: Making Healthcare Digital, 211-245.
Jamshidi, M., Hoang, D. T., & Nguyen, D. N. (2024). CNN-FL for Biotechnology Industry Empowered by Internet-of-BioNano Things and Digital Twins. IEEE Internet of Things Magazine, 7(5), 54-63.
Jyothi, A., Shankar, A., Narayan JR, A., Gaur, P., & Kumar, S. S. (2023). Smart Non-Invasive Real-Time Health Monitoring using Machine Learning and IoT. Paper presented at the 2023 IEEE International Symposium on Smart Electronic Systems (iSES).
Kasture, K., & Shende, P. (2023). Amalgamation of artificial intelligence with nanoscience for biomedical applications. Archives of Computational Methods in Engineering, 30(8), 4667-4685.
Kaushik, S., Soni, V., & Skotti, E. (2022). Nanosensors for Futuristic Smart and Intelligent Healthcare Systems: CRC Press.
Kumar, H., Kumar, G., Kumari, S., Raturi, A., Saraswat, M., & Khan, A. K. (2024). Nanomaterials for Precision Diagnostics and Therapeutic Interventions in Modern Healthcare. Paper presented at the E3S Web of Conferences.
Kumar, S., Mohan, A., Sharma, N. R., Kumar, A., Girdhar, M., Malik, T., & Verma, A. K. (2024). Computational Frontiers in Aptamer-Based Nanomedicine for Precision Therapeutics: A Comprehensive Review. ACS omega, 9(25), 26838-26862.
Mamidala, B. N. ADVANCEMENTS IN WEARABLE AND HARDWARE TECHNOLOGIES FOR HEALTH MONITORING AND MANAGEMENT. Development, 1, 4.
Manickam, P., Mariappan, S. A., Murugesan, S. M., Hansda, S., Kaushik, A., Shinde, R., & Thipperudraswamy, S. (2022). Artificial intelligence (AI) and the Internet of Medical Things (IoMT) assisted biomedical systems for intelligent healthcare. Biosensors, 12(8), 562.
Mbunge, E., Muchemwa, B., & Batani, J. (2021). Sensors and Healthcare 5.0: transformative shift in virtual care through emerging digital health technologies. Global Health Journal, 5(4), 169-177.
Menaj, K. L. (2024). Advancements in Cancer Therapy: Integrating Medical Engineering Solutions with AI Precision. Journal Environmental Sciences And Technology, 3(1), 282-301.
Mujawar, M., Gohel, H., Bhardwaj, S., Srinivasan, S., Hickman, N., & Kaushik, A. (2020). Materials Today Chemistry. Materials Today, 17, 100306.
Mujawar, M. A., Gohel, H., Bhardwaj, S. K., Srinivasan, S., Hickman, N., & Kaushik, A. (2020). Nano-enabled biosensing systems for intelligent healthcare: towards COVID-19 management. Materials Today Chemistry, 17, 100306.
Naik, G. G., & Jagtap, V. A. Nano TransMed.
Naik, G. G., & Jagtap, V. A. (2024). Two Heads Are Better than One: Unravelling the Potential Impact of Artificial Intelligence in Nanotechnology. Nano TransMed, 100041.
Nayak, M. R., Bayannavar, P. K., & Kamble, R. R. Design of Medicinally Pertinent Multifunctional Inorganic Nanomaterials Using Artificial Intelligence. In Multifunctional Inorganic Nanomaterials for Energy Applications (pp. 395-412): CRC Press.
Pandurangan, P., Dinesh, R. A., MohanaSundaram, A., Samrat, A. V., Meenambika, S., Vedanarayanan, V., . . . Moovendhan, M. (2023). Integrating cutting-edge technologies: AI, IoT, blockchain, and nanotechnology for enhanced diagnosis and treatment of colorectal cancer-A review. Journal of Drug Delivery Science and Technology, 105197.
Parashar, R., Prasad, S., Hemnani, N., & Suresh, P. K. (2024). Smart Development of Nano Materials and Nanomedicine Formulations. In Nanomaterials for Drug Delivery and Neurological Diseases Management (pp. 63-79): Springer.
Peddi, A., & Ramana, T. V. (2024). Influences and challenges of the Internet of Things and artificial intelligence on wearable data for smart healthcare and smart hearing devices. Paper presented at the AIP Conference Proceedings.
Prakashan, D., Kaushik, A., & Gandhi, S. (2024). Smart sensors and wound dressings: Artificial intelligence-supported chronic skin monitoring–A review. Chemical Engineering Journal, 154371.
Pramanik, P. K. D., Solanki, A., Debnath, A., Nayyar, A., El-Sappagh, S., & Kwak, K.-S. (2020). Advancing modern healthcare with nanotechnology, nanosensors, and Internet of nano things: Taxonomies, applications, architecture, and challenges. IEEE Access, 8, 65230-65266.
Rahman, M. Z. U., Raza, A. H., AlSanad, A. A., Akbar, M. A., Liaquat, R., Riaz, M. T., . . . Alsagri, H. S. (2022). Real-time artificial intelligence-based health monitoring, diagnosing, and environmental control system for COVID-19 patients. Mathematical Biosciences and Engineering, 19(8), 7586-7605.
Rana, A., Gautam, D., Kumar, P., & Das, A. K. (2024). Architectures, Benefits, Security and Privacy Issues of Internet of Nano Things: A Comprehensive Survey, Opportunities, and Research Challenges. IEEE Communications Surveys & Tutorials.
Rani, S. (2024). The role of IoT devices and Artificial Intelligence-based health care monitoring systems. In Convergence of Artificial Intelligence and Internet of Things for Industrial Automation (pp. 74-85): CRC Press.
Sadique, M. A., Yadav, S., Khan, R., & Srivastava, A. K. (2024). Engineered two-dimensional nanomaterials-based diagnostics integrated with the Internet of Medical Things (IoMT) for COVID-19. Chemical Society Reviews.
Sagdic, K., Eş, I., Sitti, M., & Inci, F. (2022). Smart materials: rational design in biosystems via artificial intelligence. Trends in Biotechnology, 40(8), 987-1003.
Sahi, K. S. S., & Kaushik, S. (2022). Smart Nanosensors for Healthcare Monitoring and Disease Detection using AIoT Framework. In Nanosensors for Futuristic Smart and Intelligent Healthcare Systems (pp. 387-400): CRC Press.
Sarojini, Y., Pithode, K., Sandhya, D., Sivadharshini, B., Singh, K. R., & Choubey, S. B. (2024). The Latest Technology and its Integration for the Development of Healthcare (Medical). Paper presented at the 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE).
Shafik, W. (2024). Smart Health Revolution: Exploring Artificial Intelligence of Internet of Medical Things. In Healthcare Industry Assessment: Analyzing Risks, Security, and Reliability (pp. 201-229): Springer.
Sharma, A., Singh, P. K., Nikashina, P., Gavrilenko, V., Tselykh, A., & Bozhenyuk, A. (2024). Real-Time Organ Status Tracking System for Digital Healthcare. In Data Science and Artificial Intelligence for Digital Healthcare: Communications Technologies for Epidemic Models (pp. 183-194): Springer.
Siddique, A. (2024). Leveraging AI in Medical Engineering for Targeted Cancer Therapy Delivery. Journal Environmental Sciences And Technology, 3(1), 261-281.
Sidhu, J. S., Jamwal, A., Mehta, D., & Gautam, A. (2024a). 10 Integration of IoT and AI in Bioengineering of Natural. Calcium-Based Materials: Processing, Characterization, and Applications, 168.
Sidhu, J. S., Jamwal, A., Mehta, D., & Gautam, A. (2024b). Integration of IoT and AI in Bioengineering of Natural Materials. In Calcium-Based Materials (pp. 168-188): CRC Press.
Srivastava, M., Siddiqui, A. T., & Srivastava, V. (2024). Application of Artificial Intelligence of Medical Things in Remote Healthcare Delivery. In Handbook of Security and Privacy of AI-Enabled Healthcare Systems and Internet of Medical Things (pp. 169-190): CRC Press.
Taha, B. A., Ahmed, N. M., Talreja, R. K., Haider, A. J., Al Mashhadany, Y., Al-Jubouri, Q., . . . Kaushik, A. (2024). Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis. ACS Synthetic Biology.
Vasdev, N., Gupta, T., Pawar, B., Bain, A., & Tekade, R. K. (2024). Navigating the future of health care with AI-driven digital therapeutics. Drug Discovery Today, 104110.
Verma, D., Singh, K. R., Yadav, A. K., Nayak, V., Singh, J., Solanki, P. R., & Singh, R. P. (2022). Internet of Things (IoT) in nano-integrated wearable biosensor devices for healthcare applications. Biosensors and Bioelectronics: X, 11, 100153.
Verma, P., Rao, C. M., Chapalamadugu, P. K., Tiwari, R., & Upadhyay, S. (2024). Future of Electronic Healthcare Management: Blockchain and Artificial Intelligence Integration. In Next-Generation Cybersecurity: AI, ML, and Blockchain (pp. 179-218): Springer.
Verma, V., & Thakur, P. (2023). Nanotechnology in the natural world and its application in the medical sector. Recent Innovative Trends in Interdisciplinary Research Areas, 2, 17.
Vo, T. S., Hoang, T., Vo, T. T. B. C., Jeon, B., Nguyen, V. H., & Kim, K. (2024). Recent Trends of Bioanalytical Sensors with Smart Health Monitoring Systems: From Materials to Applications. Advanced Healthcare Materials, 2303923.
Wang, C., He, T., Zhou, H., Zhang, Z., & Lee, C. (2023). Artificial intelligence enhanced sensors-enabling technologies to next-generation healthcare and biomedical platforms. Bioelectronic Medicine, 9(1), 17.
Wasilewski, T., Kamysz, W., & Gębicki, J. (2024). AI-Assisted Detection of Biomarkers by Sensors and Biosensors for Early Diagnosis and Monitoring. Biosensors, 14(7).
Yadav, A., Verma, D., Kumar, A., Kumar, P., & Solanki, P. (2021). The perspectives of biomarker-based electrochemical immunosensors, artificial intelligence, and the Internet of medical things towardáCOVID-19 diagnosis and management. Materials Today Chemistry, 20, 100443
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
