Nanotechnology has arisen as a transformative field with vast potential in healthcare applications, promising to revolutionize diagnostics, therapeutics, and overall patient management. Nanotechnology manipulates molecules and atoms, creating materials and devices with extraordinary properties. This study aims to sightsee the various solicitations of nanotechnology in healthcare, highlighting its benefits, challenges, and prospects. Targeted Medication Delivery: Nanotechnology enables the design of sophisticated drug delivery systems, precisely tailoring dosage and release for optimal efficacy. Nanotechnology is making considerable progress in areas such as tissue engineering, which is another interesting area of use. The application of nanotechnology in the medical field is not without its difficulties, despite the fact that it has a tremendous amount of potential. Looking forward, the future of nanotechnology in healthcare appears promising. Advances in personalized medicine, driven by nanotechnology-based platforms, can lead to tailored therapies that consider individual patient profiles. The continuous evolution of materials science, alongside rigorous research and clinical trials, will facilitate the integration of nanotechnology into everyday clinical practices. The paper is essential reading for anybody interested in learning how nanotechnology will change healthcare in the future. It offers a peek at a day when medical interventions will be more intelligent, effective, and customized to each patient's needs.

Keywords: Nanotechnology, healthcare, drug delivery, medical imaging, tissue engineering, regenerative medicine

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Halli U M, “Nanotechnology in IoT Security”, Journal of Nanoscience, Nanoengineering & Applications, 2022, Vol 12, issue 3, pp. 11 – 16
2. Wale Anjali D., Rokade Dipali, et al, “Smart Agriculture System using IoT”, International Journal of Innovative Research In Technology, 2019, Vol 5, Issue 10, pp.493 - 497.
3. Halli U.M., “Nanotechnology in E-Vehicle Batteries”, International Journal of Nanomaterials and Nanostructures. 2022; Vol 8, Issue 2, pp. 22–27
4. K. Sayyad Liyakat, “Nanotechnology Application in Neural Growth Support System”, Nano Trends: A Journal of Nanotechnology and Its Applications, 2022, Vol 24, issue 2, pp. 47 - 55
5. Mishra Sunil B., et al. (2024). Nanotechnology's Importance in Mechanical Engineering, Journal of Fluid Mechanics and Mechanical Design, 6(1), 1-9
6. Kazi Sultanabanu Sayyad Liyakat,(2023). Accepting Internet of Nano-Things: Synopsis, Developments, and Challenges. Journal of Nanoscience, Nanoengineering & Applications. 2023; 13(2): 17–26p. DOI: https://doi.org/10.37591/jonsnea.v13i2.1464
7. Kazi Sultanabanu Sayyad Liyakat, Kazi Kutubuddin Sayyad Liyakat. Nanomedicine as a Potential Therapeutic Approach to COVID-19. International Journal of Applied Nanotechnology. 2023; 9(2): 27–35p.
8. Kazi Kutubuddin Sayyad Liyakat (2023). Nanotechnology in Precision Farming: The Role of Research, International Journal of Nanomaterials and Nanostructures, Vol 9, No 2 (2023), https://doi.org/10.37628/ijnn.v9i2.1051
9. Kazi Kutubuddin Sayyad Liyakat (2024). Smart Agriculture based on AI-Driven-IoT(AIIoT): A KSK Approach, Advance Research in Communication Engineering and its Innovations, 1(2), 23-32.
10. K Kazi(2024). Complications with Malware Identification in IoT and an Overview of Artificial Immune Approaches. Research & Reviews: A Journal of Immunology. 2024; 14(01):54-62.
11. Liyakat, K.K.S. (2024). Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Udgata, S.K., Sethi, S., Gao, XZ. (eds) Intelligent Systems. ICMIB 2023. Lecture Notes in Networks and Systems, vol 728. Springer, Singapore. https://doi.org/10.1007/978-981-99-3932-9_12 available at: https://link.springer.com/chapter/10.1007/978-981-99-3932-9_12
12. M Pradeepa, et al. (2022). Student Health Detection using a Machine Learning Approach and IoT, 2022 IEEE 2^nd Mysore sub section International Conference (MysuruCon),
13. K. S. Liyakat. (2023).Detecting Malicious Nodes in IoT Networks Using Machine Learning and Artificial Neural Networks, 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India, 2023, pp. 1-5, doi: 10.1109/ESCI56872.2023.10099544.
14. Kasat, N. Shaikh, V. K. Rayabharapu, M. Nayak. (2023). Implementation and Recognition of Waste Management System with Mobility Solution in Smart Cities using Internet of Things, 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2023, pp. 1661-1665, doi: 10.1109/ICAISS58487.2023.10250690
15. Liyakat, K.K.S. (2023). Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Shukla, P.K., Mittal, H., Engelbrecht, A. (eds) Computer Vision and Robotics. CVR 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-4577-1_3
16. Kazi, K. (2024a). AI-Driven IoT (AIIoT) in Healthcare Monitoring. In T. Nguyen & N. Vo (Eds.), Using Traditional Design Methods to Enhance AI-Driven Decision Making(pp. 77-101). IGI Global. https://doi.org/10.4018/979-8-3693-0639-0.ch003  available at: https://www.igi-global.com/chapter/ai-driven-iot-aiiot-in-healthcare-monitoring/336693
17. Kazi, K. (2024b). Modelling and Simulation of Electric Vehicle for Performance Analysis: BEV and HEV Electrical Vehicle Implementation Using Simulink for E-Mobility Ecosystems. In L. D., N. Nagpal, N. Kassarwani, V. Varthanan G., & P. Siano (Eds.), E-Mobility in Electrical Energy Systems for Sustainability (pp. 295-320). IGI Global. https://doi.org/10.4018/979-8-3693-2611-4.ch014 Available at: https://www.igi-global.com/gateway/chapter/full-text-pdf/341172
18. Kazi, K. S. (2024a). Computer-Aided Diagnosis in Ophthalmology: A Technical Review of Deep Learning Applications. In M. Garcia & R. de Almeida (Eds.), Transformative Approaches to Patient Literacy and Healthcare Innovation(pp. 112-135). IGI Global. https://doi.org/10.4018/979-8-3693-3661-8.ch006  Available at: https://www.igi-global.com/chapter/computer-aided-diagnosis-in-ophthalmology/342823
19. Prashant K Magadum (2024). Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems, Grenze International Journal of Engineering and Technology, Jan Issue, Vol 10, Issue 1, pp. 2074-2080. Grenze ID: 01.GIJET.10.1.4_1 Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=2514&id=8
20. Priya Mangesh Nerkar, Bhagyarekha Ujjwalganesh Dhaware. (2023). Predictive Data Analytics Framework Based on Heart Healthcare System (HHS) Using Machine Learning, Journal of Advanced Zoology, 2023, Volume 44, Special Issue -2, Page 3673:3686.
21. Neeraja, R. G. Kumar, M. S. Kumar, K. K. S. Liyakat and M. S. Vani. (2024), DL-Based Somnolence Detection for Improved Driver Safety and Alertness Monitoring. 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), Greater Noida, India, 2024, pp. 589-594, doi: 10.1109/IC2PCT60090.2024.10486714. Available at: https://ieeexplore.ieee.org/document/10486714
22. Kazi Kutubuddin Sayyad Liyakat, (2024). Explainable AI in Healthcare. In: Explainable Artificial Intelligence in healthcare System, editors: Anitha Kamaraj, Debi Prasanna Acharjya. ISBN: 979-8-89113-598-7. doi: https://doi.org/10.52305/GOMR8163
23. Liyakat Kazi, K. S. (2024). ChatGPT: An Automated Teacher's Guide to Learning. In R. Bansal, A. Chakir, A. Hafaz Ngah, F. Rabby, & A. Jain (Eds.), AI Algorithms and ChatGPT for Student Engagement in Online Learning(pp. 1-20). IGI Global. https://doi.org/10.4018/979-8-3693-4268-8.ch001
24. Veena, M. Sridevi, K. K. S. Liyakat, B. Saha, S. R. Reddy and N. Shirisha,(2023). HEECCNB: An Efficient IoT-Cloud Architecture for Secure Patient Data Transmission and Accurate Disease Prediction in Healthcare Systems, 2023 Seventh International Conference on Image Information Processing (ICIIP), Solan, India, 2023, pp. 407-410, doi: 10.1109/ICIIP61524.2023.10537627. Available at: https://ieeexplore.ieee.org/document/10537627
25. Rajendra Prasad, Santoshachandra Rao Karanam (2024). AI in public-private partnership for IT infrastructure development, Journal of High Technology Management Research, Volume 35, Issue 1, May 2024, 100496. https://doi.org/10.1016/j.hitech.2024.100496
26. Megha Nagrale, Rahul S. Pol, Ganesh B. Birajadar, Altaf O. Mulani, (2024). Internet of Robotic Things in Cardiac Surgery: An Innovative Approach, African Journal of Biological Sciences, Vol 6, Issue 6, pp. 709-725 doi: 33472/AFJBS.6.6.2024.709-725
27. Kazi, K. S. (2024b). IoT Driven by Machine Learning (MLIoT) for the Retail Apparel Sector. In T. Tarnanidis, E. Papachristou, M. Karypidis, & V. Ismyrlis (Eds.),Driving Green Marketing in Fashion and Retail (pp. 63-81). IGI Global. https://doi.org/10.4018/979-8-3693-3049-4.ch004
28. Kutubuddin Kazi, (2024a). Machine Learning (ML)-Based Braille Lippi Characters and Numbers Detection and Announcement System for Blind Children in Learning, In Gamze Sart (Eds.), Social Reflections of Human-Computer Interaction in Education, Management, and Economics, IGI Global. https://doi.org/10.4018/979-8-3693-3033-3.ch002
29. Kazi, K. S. (2024). Artificial Intelligence (AI)-Driven IoT (AIIoT)-Based Agriculture Automation. In S. Satapathy & K. Muduli (Eds.), Advanced Computational Methods for Agri-Business Sustainability(pp. 72-94). IGI Global. https://doi.org/10.4018/979-8-3693-3583-3.ch005
30. Kazi Kutubuddin, (2024c). Vehicle Health Monitoring System (VHMS) by Employing IoT and Sensors, Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp- 5367-5374.
31. 31.Kazi Kutubuddin, (2024e). A Novel Approach on ML based Palmistry, Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp- 5186-5193.
32. 32.Kazi Kutubuddin, (2024e). IoT based Boiler Health Monitoring for Sugar Industries,Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp. 5178 -5185.
33. 33.  Liyakat, K.K.S., (2024). Explainable AI in healthcare, Explainable Artificial Intelligence in Healthcare Systems, 2024, pp. 271–284
34. Yogita Shirdale, et al, “Analysis and design of Capacitive coupled wideband Microstrip antenna in C and X band: A Survey”, Journal GSD-International society for green, Sustainable Engineering and Management, 2014, Vol 1, issue 15, pp. 1 - 7.
35. Yogita Shirdale, et al., “Coplanar capacitive coupled probe fed micro strip antenna for C and X band”, International Journal of Advanced Research in Computer and Communication Engineering, 2016, Vol 5, Issue 4, pp. 661 - 663.
36. Kazi, K. S. (2024). Machine Learning-Based Pomegranate Disease Detection and Treatment. In M. Zia Ul Haq & I. Ali (Eds.), Revolutionizing Pest Management for Sustainable Agriculture(pp. 469-498). IGI Global. https://doi.org/10.4018/979-8-3693-3061-6.ch019
37. J. Patil, S. B. Khadake, D. A. Tamboli, H. M. Mallad, S. M. Takpere and V. A. Sawant, "Review of AI in Power Electronics and Drive Systems," 2024 3rd International conference on Power Electronics and IoT Applications in Renewable Energy and its Control (PARC),Mathura, India, 2024, pp. 94-99, doi: 10.1109/PARC59193.2024.10486488.
38. J. Patil, S. B. Khadake, D. A. Tamboli, H. M. Mallad, S. M. Takpere and V. A. Sawant, "A Comprehensive Analysis of Artificial Intelligence Integration in Electrical Engineering," 2024 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), Lalitpur, Nepal, 2024, pp. 484-491, doi: 10.1109/ICMCSI61536.2024.00076.
39. Suhas B khadake , Pranita J Kashid , Asmita M Kawade , Santoshi V Khedekar , H. M. Mallad., “Electric Vehicle Technology Battery Management – Review", International Journal of Advanced Research in Science Communication and Technology, vol. 3, no. 2, pp. 319-325, September 2023. https://doi.org/10.48175/ijarsct-13048
40. Khadake, S., Kawade, S., Moholkar, S., Pawar, M. (2024). A Review of 6G Technologies and Its Advantages Over 5G Technology. In: Pawar, P.M., et al.Techno-societal 2022. ICATSA 2022. Springer, Cham. https://doi.org/10.1007/978-3-031-34644-6_107
41. Kutubuddin Kazi (2024a). IoT Technologies for the Intelligent Dairy Industry: A New Challenge. InSalu George Thandekkattu,Narasimha Rao Vajjhala (Eds.), Designing Sustainable Internet of Things Solutions for Smart Industries, IGI Global.
42. Kutubuddin Kazi (2024b). Machine Learning-Driven-Internet of Things(MLIoT) Based Healthcare Monitoring System. InNilmini Wickramasinghe (Eds.), Impact of Digital Solutions for Improved Healthcare Delivery, IGI Global.
43. Kutubuddin Kazi (2024c). Moonlighting in Carrier, InMuhammad Nawaz Tunio (Eds.), Applications of Career Transitions and Entrepreneurship, IGI Global.
44. Kutubuddin Kazi (2024d). Heart Health Monitoring Using IoT and Machine Learning Methods, InAminabee Shaik (Eds.), AI-Powered Advances in Pharmacology, IGI Global.
45. Kutubuddin Kazi (2024a). IoT Technologies for the Intelligent Dairy Industry: A New Challenge. InSalu George Thandekkattu,Narasimha Rao Vajjhala (Eds.), Designing Sustainable Internet of Things Solutions for Smart Industries, IGI Global.
46. Kutubuddin Kazi (2024c). Moonlighting in Carrier, InMuhammad Nawaz Tunio (Eds.), Applications of Career Transitions and Entrepreneurship, IGI Global.
47. Liyakat, K. K. (2025). Heart Health Monitoring Using IoT and Machine Learning Methods. In A. Shaik (Ed.), AI-Powered Advances in Pharmacology(pp. 257-282). IGI Global. https://doi.org/10.4018/979-8-3693-3212-2.ch010
48. Kutubuddin Kazi (2024c). AI-Powered-IoT (AIIoT) based Decision Making System for BP Patient’s Healthcare Monitoring: KSK Approach for BP Patient Healthcare Monitoring. InSourour Aouadni, Ismahene Aouadni (Eds.), Recent Theories and Applications for Multi-Criteria Decision-Making, IGI Global,
49. Kutubuddin Kazi (2024c). AI-Driven-IoT (AIIoT) based Decision-Making in Drones for Climate Change: KSK Approach. InSourour Aouadni, Ismahene Aouadni (Eds.), Recent Theories and Applications for Multi-Criteria Decision-Making, IGI Global,
50. Kazi Kutubuddin Sayyad Liyakat (2024). Nanotechnology in Medical Applications: A Study. Nano Trends: A Journal of Nanotechnology and Its Applications. 2024; 26(2): 1–11p.
51. Kazi Kutubuddin Sayyad Liyakat.(2024). Nanotechnology in BattleField: A Study. Journal of Nanoscience, Nanoengineering & Applications. 2024; 14(2): 18–30p.
52. Kazi Sultananbanu Sayyad Liyakat Kazi, Kazi Kutubuddin Sayyad Liyakat.(2024/. Polymer Applications in Energy Generation and Storage: A Forward Path. Journal of Nanoscience, Nanoengineering & Applications. 2024; 14(2): 31–39p.

Nanotechnology has arisen as a transformative field with vast potential in healthcare applications, promising to revolutionize diagnostics, therapeutics, and overall patient management. Nanotechnology manipulates molecules and atoms, creating materials and devices with extraordinary properties. This study aims to sightsee the various solicitations of nanotechnology in healthcare, highlighting its benefits, challenges, and prospects. Targeted Medication Delivery: Nanotechnology enables the design of sophisticated drug delivery systems, precisely tailoring dosage and release for optimal efficacy. Nanotechnology is making considerable progress in areas such as tissue engineering, which is another interesting area of use. The application of nanotechnology in the medical field is not without its difficulties, despite the fact that it has a tremendous amount of potential. Looking forward, the future of nanotechnology in healthcare appears promising. Advances in personalized medicine, driven by nanotechnology-based platforms, can lead to tailored therapies that consider individual patient profiles. The continuous evolution of materials science, alongside rigorous research and clinical trials, will facilitate the integration of nanotechnology into everyday clinical practices. The paper is essential reading for anybody interested in learning how nanotechnology will change healthcare in the future. It offers a peek at a day when medical interventions will be more intelligent, effective, and customized to each patient's needs.

Keywords: Nanotechnology, healthcare, drug delivery, medical imaging, tissue engineering, regenerative medicine

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Halli U M, “Nanotechnology in IoT Security”, Journal of Nanoscience, Nanoengineering & Applications, 2022, Vol 12, issue 3, pp. 11 – 16
2. Wale Anjali D., Rokade Dipali, et al, “Smart Agriculture System using IoT”, International Journal of Innovative Research In Technology, 2019, Vol 5, Issue 10, pp.493 - 497.
3. Halli U.M., “Nanotechnology in E-Vehicle Batteries”, International Journal of Nanomaterials and Nanostructures. 2022; Vol 8, Issue 2, pp. 22–27
4. K. Sayyad Liyakat, “Nanotechnology Application in Neural Growth Support System”, Nano Trends: A Journal of Nanotechnology and Its Applications, 2022, Vol 24, issue 2, pp. 47 - 55
5. Mishra Sunil B., et al. (2024). Nanotechnology's Importance in Mechanical Engineering, Journal of Fluid Mechanics and Mechanical Design, 6(1), 1-9
6. Kazi Sultanabanu Sayyad Liyakat,(2023). Accepting Internet of Nano-Things: Synopsis, Developments, and Challenges. Journal of Nanoscience, Nanoengineering & Applications. 2023; 13(2): 17–26p. DOI: https://doi.org/10.37591/jonsnea.v13i2.1464
7. Kazi Sultanabanu Sayyad Liyakat, Kazi Kutubuddin Sayyad Liyakat. Nanomedicine as a Potential Therapeutic Approach to COVID-19. International Journal of Applied Nanotechnology. 2023; 9(2): 27–35p.
8. Kazi Kutubuddin Sayyad Liyakat (2023). Nanotechnology in Precision Farming: The Role of Research, International Journal of Nanomaterials and Nanostructures, Vol 9, No 2 (2023), https://doi.org/10.37628/ijnn.v9i2.1051
9. Kazi Kutubuddin Sayyad Liyakat (2024). Smart Agriculture based on AI-Driven-IoT(AIIoT): A KSK Approach, Advance Research in Communication Engineering and its Innovations, 1(2), 23-32.
10. K Kazi(2024). Complications with Malware Identification in IoT and an Overview of Artificial Immune Approaches. Research & Reviews: A Journal of Immunology. 2024; 14(01):54-62.
11. Liyakat, K.K.S. (2024). Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Udgata, S.K., Sethi, S., Gao, XZ. (eds) Intelligent Systems. ICMIB 2023. Lecture Notes in Networks and Systems, vol 728. Springer, Singapore. https://doi.org/10.1007/978-981-99-3932-9_12 available at: https://link.springer.com/chapter/10.1007/978-981-99-3932-9_12
12. M Pradeepa, et al. (2022). Student Health Detection using a Machine Learning Approach and IoT, 2022 IEEE 2^nd Mysore sub section International Conference (MysuruCon),
13. K. S. Liyakat. (2023).Detecting Malicious Nodes in IoT Networks Using Machine Learning and Artificial Neural Networks, 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India, 2023, pp. 1-5, doi: 10.1109/ESCI56872.2023.10099544.
14. Kasat, N. Shaikh, V. K. Rayabharapu, M. Nayak. (2023). Implementation and Recognition of Waste Management System with Mobility Solution in Smart Cities using Internet of Things, 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2023, pp. 1661-1665, doi: 10.1109/ICAISS58487.2023.10250690
15. Liyakat, K.K.S. (2023). Machine Learning Approach Using Artificial Neural Networks to Detect Malicious Nodes in IoT Networks. In: Shukla, P.K., Mittal, H., Engelbrecht, A. (eds) Computer Vision and Robotics. CVR 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-4577-1_3
16. Kazi, K. (2024a). AI-Driven IoT (AIIoT) in Healthcare Monitoring. In T. Nguyen & N. Vo (Eds.), Using Traditional Design Methods to Enhance AI-Driven Decision Making(pp. 77-101). IGI Global. https://doi.org/10.4018/979-8-3693-0639-0.ch003  available at: https://www.igi-global.com/chapter/ai-driven-iot-aiiot-in-healthcare-monitoring/336693
17. Kazi, K. (2024b). Modelling and Simulation of Electric Vehicle for Performance Analysis: BEV and HEV Electrical Vehicle Implementation Using Simulink for E-Mobility Ecosystems. In L. D., N. Nagpal, N. Kassarwani, V. Varthanan G., & P. Siano (Eds.), E-Mobility in Electrical Energy Systems for Sustainability (pp. 295-320). IGI Global. https://doi.org/10.4018/979-8-3693-2611-4.ch014 Available at: https://www.igi-global.com/gateway/chapter/full-text-pdf/341172
18. Kazi, K. S. (2024a). Computer-Aided Diagnosis in Ophthalmology: A Technical Review of Deep Learning Applications. In M. Garcia & R. de Almeida (Eds.), Transformative Approaches to Patient Literacy and Healthcare Innovation(pp. 112-135). IGI Global. https://doi.org/10.4018/979-8-3693-3661-8.ch006  Available at: https://www.igi-global.com/chapter/computer-aided-diagnosis-in-ophthalmology/342823
19. Prashant K Magadum (2024). Machine Learning for Predicting Wind Turbine Output Power in Wind Energy Conversion Systems, Grenze International Journal of Engineering and Technology, Jan Issue, Vol 10, Issue 1, pp. 2074-2080. Grenze ID: 01.GIJET.10.1.4_1 Available at: https://thegrenze.com/index.php?display=page&view=journalabstract&absid=2514&id=8
20. Priya Mangesh Nerkar, Bhagyarekha Ujjwalganesh Dhaware. (2023). Predictive Data Analytics Framework Based on Heart Healthcare System (HHS) Using Machine Learning, Journal of Advanced Zoology, 2023, Volume 44, Special Issue -2, Page 3673:3686.
21. Neeraja, R. G. Kumar, M. S. Kumar, K. K. S. Liyakat and M. S. Vani. (2024), DL-Based Somnolence Detection for Improved Driver Safety and Alertness Monitoring. 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), Greater Noida, India, 2024, pp. 589-594, doi: 10.1109/IC2PCT60090.2024.10486714. Available at: https://ieeexplore.ieee.org/document/10486714
22. Kazi Kutubuddin Sayyad Liyakat, (2024). Explainable AI in Healthcare. In: Explainable Artificial Intelligence in healthcare System, editors: Anitha Kamaraj, Debi Prasanna Acharjya. ISBN: 979-8-89113-598-7. doi: https://doi.org/10.52305/GOMR8163
23. Liyakat Kazi, K. S. (2024). ChatGPT: An Automated Teacher's Guide to Learning. In R. Bansal, A. Chakir, A. Hafaz Ngah, F. Rabby, & A. Jain (Eds.), AI Algorithms and ChatGPT for Student Engagement in Online Learning(pp. 1-20). IGI Global. https://doi.org/10.4018/979-8-3693-4268-8.ch001
24. Veena, M. Sridevi, K. K. S. Liyakat, B. Saha, S. R. Reddy and N. Shirisha,(2023). HEECCNB: An Efficient IoT-Cloud Architecture for Secure Patient Data Transmission and Accurate Disease Prediction in Healthcare Systems, 2023 Seventh International Conference on Image Information Processing (ICIIP), Solan, India, 2023, pp. 407-410, doi: 10.1109/ICIIP61524.2023.10537627. Available at: https://ieeexplore.ieee.org/document/10537627
25. Rajendra Prasad, Santoshachandra Rao Karanam (2024). AI in public-private partnership for IT infrastructure development, Journal of High Technology Management Research, Volume 35, Issue 1, May 2024, 100496. https://doi.org/10.1016/j.hitech.2024.100496
26. Megha Nagrale, Rahul S. Pol, Ganesh B. Birajadar, Altaf O. Mulani, (2024). Internet of Robotic Things in Cardiac Surgery: An Innovative Approach, African Journal of Biological Sciences, Vol 6, Issue 6, pp. 709-725 doi: 33472/AFJBS.6.6.2024.709-725
27. Kazi, K. S. (2024b). IoT Driven by Machine Learning (MLIoT) for the Retail Apparel Sector. In T. Tarnanidis, E. Papachristou, M. Karypidis, & V. Ismyrlis (Eds.),Driving Green Marketing in Fashion and Retail (pp. 63-81). IGI Global. https://doi.org/10.4018/979-8-3693-3049-4.ch004
28. Kutubuddin Kazi, (2024a). Machine Learning (ML)-Based Braille Lippi Characters and Numbers Detection and Announcement System for Blind Children in Learning, In Gamze Sart (Eds.), Social Reflections of Human-Computer Interaction in Education, Management, and Economics, IGI Global. https://doi.org/10.4018/979-8-3693-3033-3.ch002
29. Kazi, K. S. (2024). Artificial Intelligence (AI)-Driven IoT (AIIoT)-Based Agriculture Automation. In S. Satapathy & K. Muduli (Eds.), Advanced Computational Methods for Agri-Business Sustainability(pp. 72-94). IGI Global. https://doi.org/10.4018/979-8-3693-3583-3.ch005
30. Kazi Kutubuddin, (2024c). Vehicle Health Monitoring System (VHMS) by Employing IoT and Sensors, Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp- 5367-5374.
31. 31.Kazi Kutubuddin, (2024e). A Novel Approach on ML based Palmistry, Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp- 5186-5193.
32. 32.Kazi Kutubuddin, (2024e). IoT based Boiler Health Monitoring for Sugar Industries,Grenze International Journal of Engineering and Technology, Vol 10, Issue 2, pp. 5178 -5185.
33. 33.  Liyakat, K.K.S., (2024). Explainable AI in healthcare, Explainable Artificial Intelligence in Healthcare Systems, 2024, pp. 271–284
34. Yogita Shirdale, et al, “Analysis and design of Capacitive coupled wideband Microstrip antenna in C and X band: A Survey”, Journal GSD-International society for green, Sustainable Engineering and Management, 2014, Vol 1, issue 15, pp. 1 - 7.
35. Yogita Shirdale, et al., “Coplanar capacitive coupled probe fed micro strip antenna for C and X band”, International Journal of Advanced Research in Computer and Communication Engineering, 2016, Vol 5, Issue 4, pp. 661 - 663.
36. Kazi, K. S. (2024). Machine Learning-Based Pomegranate Disease Detection and Treatment. In M. Zia Ul Haq & I. Ali (Eds.), Revolutionizing Pest Management for Sustainable Agriculture(pp. 469-498). IGI Global. https://doi.org/10.4018/979-8-3693-3061-6.ch019
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