MUMBAI, India, Oct. 26 -- Intellectual Property India has published a patent application (202641122918 A) filed by Dr. Chethan Chandra S Basavaraddi; Dr. Sapna S Basavaraddi; Dr. Ravindra Pratap Singh; Dr. Diksha; Dr. Vivek Panvekar; Rajvardhan Sandip Vikhe Patil; Dr. Etlam Mahadev Reddy; Dr. Ratna Panvekar; Dr. Kamatam Kiran; Er. Akanksha Bali; Dr. Himanshi Babbar; Dr. Shivam Gaur; Dr. K Veena; Dr. Anuj Sangwan; and Shreya Bhardwaj on October 14, 2026, for Next-Generation Artificial Intelligence And Nanotechnology For Cybersecurity, Smart Higher Education, Fintech, Blockchain Applications, Management, And Multidisciplinary Research.
Inventors include Dr. Chethan Chandra S Basavaraddi; Dr. Sapna S Basavaraddi; Dr. Ravindra Pratap Singh; Dr. Diksha; Dr. Vivek Panvekar; Rajvardhan Sandip Vikhe Patil; Dr. Etlam Mahadev Reddy; Dr. Ratna Panvekar; Dr. Kamatam Kiran; Er. Akanksha Bali; Dr. Himanshi Babbar; Dr. Shivam Gaur; Dr. K Veena; Dr. Anuj Sangwan; and Shreya Bhardwaj.
The application for the patent was published on October 23, 2026, under issue no. 43/2026.
Abstract: An integrated AI–nanotechnology platform is disclosed for secure, adaptive, and auditable digital services across multiple sectors. The platform comprises a data- ingestion layer, a nanotechnology-enabled sensing interface, an AI analytics engine, a zero-trust cybersecurity controller, a permissioned blockchain ledger, and a policy-and-workflow manager. Data from learning systems, financial services, institutional operations, research instruments, and connected devices are normalized and evaluated according to purpose-specific policies. AI models detect anomalous activity, estimate risk, personalize learning and services, and support decision-making. Where deployed, nanosensors or nanomaterial-based devices provide physical measurements such as environmental, structural, or equipment-condition data, with calibration and confidence metadata. Sensitive records may be processed locally or in privacy-preserving form; only approved proofs, hashes, consent records, and audit events are written to the ledger. A feedback mechanism updates models and access policies following authorized review. The modular design is intended to improve threat detection, data provenance, operational efficiency, research reproducibility, and responsible cross-domain collaboration while maintaining human oversight and traceability. A modular AI–nanotechnology platform integrates data ingestion, optional nanosensor inputs, AI analytics, zero-trust cybersecurity, permissioned blockchain verification, and policy-based workflows. It supports anomaly detection, risk assessment, personalized learning, transaction monitoring, organizational decision support, and research provenance. Sensitive data may remain in authorized repositories while hashes and audit events are recorded on a permissioned ledger. Confidence-aware outputs, governance controls, and human review are used to improve security, traceability, and responsible use across higher education, FinTech, management, cybersecurity, and multidisciplinary research.
Disclaimer: Curated by HT Syndication.
