S. A. Jadhav,
Tanveer Ahmad Wani,
Abhijeet Deshpande,
Eswar S. Meenakshi,
B. Pravallika,
Kada Tulasi,
- Associate Professor, Department of Computer Science and Engineering, Krishna Institute of Science and Technology, Krishna Vishwa Vidyapeeth “Deemed to be University”, Karad, Satara, Maharashtra, India
- Associate Professor, Department of Physics, Noida International University, Greater Noida, Uttar Pradesh, India
- Associate Professor, Department of Mechanical Engineering, Vishwakarma Institute of Technology, Pune, Maharashtra, India
- Associate Professor, Department of Allied Health, College of Allied Health Sciences, Meenakshi Medical College Hospital & Research Institute, Meenakshi Academy of Higher Education and Research, Kanchipuram, Tamil Nadu, India
- Associate Professor, Department of Computer Science and Engineering (AI&ML), Vardhaman College of Engineering, Shamshabad, Hyderabad, Telangana, India
- Associate Professor, Department of Mechanical Engineering, Pragati Engineering College, Kakinada, Andhra Pradesh, India
Abstract
Cognitive polymer composite systems: A novel form of intelligent biomaterials with the capability to sense, process and respond to real time physiological stimuli on their own. The present paper offers a comprehensive platform to integrate stimulus responsive polymers with intrinsic sensing networks and learning based decision models to offer adaptable bio-medical solutions. Mathematical formulations are available that are used to model stimulus response behavior, sensor signal processing and cognition decision processes. The proposed methodology will be a hybridization of the advanced fabrication and artificial intelligence models, including artificial neural networks and reinforcement learning, to provide dynamic adaptation in case of being exposed to alternative biological conditions. Experimental evaluation use has also shown more responsiveness, stability and accuracy compared to traditional systems and have also hinted possible uses in smart implants, drug delivery and even personalized healthcare systems. It has been demonstrated in this paper that the utilization of smart polymers containing embedded sensors and models based on learning can be helpful in offering autonomous biomedical functionality. The proposed system was more precise, sensitive, and faithful as compared to conventional biomaterials. Its capacity to cope with real-time physiological information and dynamically adjust explains good prospects in its application in smart implants, drug-delivery and personalized healthcare. The range of clinical use can be expanded, through future work, by increasing the range of scalability and a long-term biocompatibility, and improved integration with more complex artificial intelligence techniques.
Keywords: Cognitive polymer composites, smart biomaterials, autonomous response systems, artificial intelligence in healthcare, biomedical sensing.
[This article belongs to Special Issue under section in Journal of Polymer & Composites (jopc)]
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Journal of Polymer & Composites
| Volume | 14 | |
| Special Issue | 04 | |
| Received | 01/05/2026 | |
| Accepted | 24/06/2026 | |
| Published | 21/08/2026 | |
| Publication Time | 112 Days |