Intellectual Property India Publishes Patent Application for An Ai-Driven Sensor-Aware Multimodal System For Quality-Controlled Acquisition, Synchronised Feature Extraction, Benchmarking, And Developmental Performance Mapping Of Child Activities

MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202541035865 A) filed by Srinivas Tirukappa Venkataravana on April 13, 2025, for An Ai-Driven Sensor-Aware Multimodal System For Quality-Controlled Acquisition, Synchronised Feature Extraction, Benchmarking, And Developmental Performance Mapping Of Child Activities.

Inventor includes Srinivas Tirukappa Venkataravana.

The application for the patent was published on June 26, 2026, under issue no. 26/2026.

Abstract: AN AI-DRIVEN SENSOR-AWARE MULTIMODAL SYSTEM FOR QUALITY-CONTROLLED ACQUISITION, SYNCHRONISED FEATURE EXTRACTION, BENCHMARKING, AND DEVELOPMENTAL PERFORMANCE MAPPING OF CHILD ACTIVITIES The invention relates to a sensor-assisted multimodal biomechanical, acoustic, and cross-modal assessment system, device, and method. The invention acquires image, video, and audio data of a child performing a sports, dance, music, art, recitation, hobby, or skill-based activity through one or more camera and microphone devices, and optionally one or more auxiliary sensors. The acquired data is subjected to quality validation, sensor-aware preprocessing, and synchronisation. A multimodal feature extraction engine derives movement, expression, acoustic, temporal, and activity-specific features, which are compared with age-specific and activity-specific benchmark reference profiles. A scoring and projection engine computes one or more alignment, coherence, consistency, readiness, or developmental-projection outputs, and an output engine generates recapture, coaching, developmental, and reporting outputs. The invention may further support longitudinal closed-loop updating using later-acquired child-performance data. The invention provides a sensor-linked technical architecture for quality-validated capture, synchronised feature extraction, and developmental-performance mapping. The system may further generate benchmark-alignment outputs and improvement guidance relative to predefined standard or elite-performer reference profiles. Figure of abstract: FIG. 1.

Disclaimer: Curated by HT Syndication.