Intellectual Property India Publishes Patent Application for System And Method For Adaptive Meta Deep Learning Using Sensor Fusion, Transformer-Based Learning, And Entanglement For Real Time Multi Sensor Data Processing And Decision Making.

MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202541026362 A) filed by Kayandoor Ravindra Shetty; and K Ravindra Shetty on March 22, 2025, for System And Method For Adaptive Meta Deep Learning Using Sensor Fusion, Transformer-Based Learning, And Entanglement For Real Time Multi Sensor Data Processing And Decision Making..

Inventor includes K Ravindra Shetty.

The application for the patent was published on September 25, 2026, under issue no. 39/2026.

Abstract: Abstract: A system and method for adaptive meta deep learning using sensor fusion, transformer-based learning, and entanglement to process real-time data from multiple sensor types is disclosed. The system employs a multi-layer neural network and a self-adaptive learning framework to generate seven probable output classes with high accuracy. It integrates text-to-uniquenumber transformation for specific applications, word-to-vector or tensor transformation for others, and a hybrid approach for select cases. The system delivers output in visual, audio, and textual formats for real-time monitoring, control, and decision-making. To reduce computational complexity, object state and transition information are embedded within real-time state transitions. Adaptive entanglement-based learning enhances prediction reliability by optimizing data correlation, reducing noise, and enriching features. The system operates on both local devices and cloud platforms, ensuring scalability and seamless operation. This invention is applicable to AI-enabled standalone and enterprise systems, with potential use cases in healthcare, agriculture, education, finance, and other industries.

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