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Research Article | Open Access
Volume 15 2023 | None
Bridging Gaps in Autism Care: The Smart Monitoring Solution
Viha Jaiswal, Koppala Vianney Xavier , Sucharitha M
Pages: 209-218
A pioneering effort that addresses the dire need to assist children with Autism Spectrum Disorder (ASD) and their caretakers is the Smart Monitoring Sys- tem for ASD. Around 1 in 18 million people in India are identified with autism, and about 1 to 1.5 percent of children aged two to nine receive a diagnosis of ASD. which is the third most common developmental disability worldwide. The communication, social, and repetitive behaviors that children with ASD struggle with can be detrimental to their ability to learn and adjust in social and academic contexts. India’s middle-class households frequently do not have access to expensive ASD therapy interventions. Our concept envisions an automated monitoring system that uses sensors, IoT, and AI to bridge this gap. Using body-worn and ambient sensors, this cutting-edge technology uses artificial intelligence (AI) algorithms to monitor children’s behavior. It then provides caretakers, educators, and healthcare professionals with real-time feedback and individualized learning opportunities. Personalized yoga instruction, predictive caring, real-time behavior tracking, user-friendliness, and alerts for impulsive conduct are just a few of the system’s distinctive characteristics. It incorporates multiple technologies, including AI-driven tailored interventions, augmented reality help, and virtual reality simulations. In the quest for optimal Yoga Neural Detection various algorithms prove valuable. However, Convolutional Neural Network (CNN) emerges as a robust contender, excelling in extracting and adapting hierarchical features. The model’s precision, recall, F2-score, and accuracy are reported as 0.94, 0.95, 0.95, and 97.61 percentage, respectively, underscoring its effectiveness in enhancing the system’s capabilities. Our System will empower caregivers, improve understanding of children’s behavior, and lessen the burden of managing ASD in children. There could have a significant positive influence on society, including less stress for parents, improved care and support for kids with ASD, and inclusive education and awareness. Additionally, the study may increase accessibility and knowledge of improved ASD monitoring. Moreover, we envisage a future for this system on a global scale, with ML being essential to individualized assistance and care for kids with ASD.
ASD Monitoring System, Internet of Things (IoT), Sensors, Machine Learning (ML), Real-time Feedback, Children with ASD