MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202511113508 A) filed by Dr. Gaurav Choudhary; Lakshita Rai; Dr. Ashish Kumar; Neeraj Garg; Upendra Chaudhary; Gaurav Sharma; Yashwant Singh; Sourabh Kumar Goutam; and Dr. Shashikant Sharma, Jaipur, Rajasthan, on Nov. 18, 2025, for 'intelligent sight assist for visually impaired individuals using lightweight deep learning.'
Inventor(s) include Dr. Gaurav Choudhary; Lakshita Rai; Dr. Ashish Kumar; Neeraj Garg; Upendra Chaudhary; Gaurav Sharma; Yashwant Singh; Sourabh Kumar Goutam; and Dr. Shashikant Sharma.
The application for the patent was published on Jan. 9, under issue no. 02/2026.
According to the abstract released by the Intellectual Property India: "The intelligent sight assist system introduces an innovative multi-sensory navigation framework for comprehensive environmental awareness that integrates lightweight deep learning protocols with adaptive obstacle detection mechanisms, facilitating real-time object recognition, dynamic text identification, and robust navigation assistance while maintaining seamless assistive integration and operational accuracy for consistent mobility applications. [510] The comprehensive assistive framework employs adaptive computer vision algorithms and intuitive sensor protocols, utilizing embedded processing arrays and energy-efficient recognition systems to ensure timely obstacle identification, enhanced environmental understanding, and optimal navigation reliability while maintaining continuous mobility monitoring capabilities. [515] The integrated methodology combines multi-modal sensing techniques with artificial intelligence-driven object recognition systems, leveraging variable-precision ultrasonic signals and multi-factor environmental indicators to optimize navigation procedures and recognition workflows for maximum mobility accuracy and minimal detection uncertainty during critical assistance applications. [520] The novel responsive assistive architecture features engineered high-precision sensor components with specialized environmental fingerprinting protocols, enabling complex multi-stage obstacle verification while ensuring detection consistency and performance optimization across various mobility instruments without compromising system reliability. [525] The innovative design incorporates strategic validation mechanisms for enhanced object identification and environmental security, utilizing optimized multi-function systems and adaptive sensing technology to ensure legitimate navigation assignment while maintaining functionality across diverse mobility environments and assistance scenarios. [530] Implementation methodology emphasizes scalable assistive integration and efficient navigation sequences, implementing interactive sensing measures and pattern recognition algorithms to achieve superior obstacle determination, enhanced object identification, and unauthorized movement prevention while ensuring technological simplicity during mobility monitoring. [535] The system demonstrates exceptional adaptability through comprehensive integration of environmental identification protocols and intelligent sensing technologies, validating its effectiveness across various multifunctional assistance configurations and mobility scenarios while maintaining consistent detection performance and operational efficiency under diverse conditions. [540] The developed framework enables sustainable and reliable navigation assistance through streamlined, AI-powered recognition systems, providing significant advantages over traditional mobility approaches through variable validation mechanisms, adaptive identification protocols, and improved environmental assignment while maintaining superior detection accuracy during critical assistance procedures."
Disclaimer: Curated by HT Syndication.
