Enhancing cognitive abilities in autistic children through AI-enabled iot intervention and cognicare framework

Autism Spectrum Disorder (ASD) presents unique challenges, including social skill deficits, repetitive behaviours, and communication difficulties, warranting innovative healthcare approaches. Traditional treatments have shown limited success, necessitating a shift towards assistive technologies. This paper addresses the gap in effective medical treatments for autistic children by proposing an AI-enabled IoT system. Current research lacks tangible solutions for ASD, emphasizing the need for a new paradigm. Leveraging AI and IoT technologies, our system utilizes heart rate and EEG sensors for data collection, employing fast geometric ensembling for feature extraction and a Radial Basis Function Network (RBFN) for classification. The system integrates a real-time heart rate sensor to monitor the child’s physiological state, offering a predictive model for emotional and behavioural states. A virtual environment using 3D models aids in eye contact improvement and alleviation of social barriers. The goal is to enhance adaptive processes, addressing social skill deficits and communication challenges. Results demonstrate the system’s potential in predicting and conveying the child’s state, fostering positive interaction, and breaking fear barriers through innovative virtual environments. This novel AI-enabled IoT intervention, CogniCare, fills a critical public health gap, providing a promising avenue for enhancing cognitive abilities and daily living skills in autistic children, ultimately maximizing their positive participation in the community.