MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641079440 A) filed by Rajitha. M; N. Shilpa; R Karan; Prof. Dr. Rahul Sharma; Santhana Megala Srinivasagam; Mary Joseph; Dr. Maturi Ranga Rao; Dr. Meghana Solanki; Anusha Kanchari Bavajigari; and Dr. Sabyasachi Pramanik on June 27, 2026, for A Neuromorphic Computing System For Brain - Inspired Ai Using Event - Driven Neural Processing.
Inventors include Rajitha. M; N. Shilpa; R Karan; Prof. Dr. Rahul Sharma; Santhana Megala Srinivasagam; Mary Joseph; Dr. Maturi Ranga Rao; Dr. Meghana Solanki; Anusha Kanchari Bavajigari; and Dr. Sabyasachi Pramanik.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The proposed invention entitled “A Neuromorphic Computing System for Brain-Inspired AI Using Event-Driven Neural Processing” relates to an advanced artificial intelligence framework inspired by biological neural systems for developing energy-efficient and adaptive computational architectures. The invention integrates event acquisition interfaces, spiking neural processing modules, adaptive synaptic networks, neuromorphic memory structures, predictive intelligence engines, and cognitive reasoning components within a unified framework. The proposed system employs event-driven processing methodologies where computation occurs only upon significant event generation, thereby reducing redundant operations and minimizing energy consumption. The invention further incorporates temporal learning mechanisms, adaptive plasticity models, and multi-modal sensory fusion techniques for enabling autonomous learning and intelligent decision-making. Neuromorphic memory integration minimizes computational bottlenecks and improves processing efficiency. The proposed framework supports edge intelligence, robotics, healthcare systems, industrial automation, autonomous transportation, and cognitive computing applications while providing scalable, sustainable, and low-power artificial intelligence capabilities through brain-inspired event-driven neural processing mechanisms.
Disclaimer: Curated by HT Syndication.
