A Comprehensive Review of AI-Based Personalized Systems for Child Development Monitoring Using Machine Learning and Health Analytics

Author(s)	Ms. Sanyukta Avinash Patil, Prof. Nilesh Joshi, Dr. Manisha Bharati
Country	India
Abstract	Child development includes physical growth, emotional well-being, learning ability, behavior, and mental health. Traditional methods used for monitoring children usually follow general developmental guidelines and often fail to consider the unique needs of each child. With the growth of Artificial Intelligence (AI) and Machine Learning (ML), researchers are now developing intelligent systems that can study child health data, predict possible risks, and provide personalized recommendations. This review paper discusses recent studies related to childhood obesity prediction, personalized nutrition, behavioral health analysis, sleep monitoring, and digital health interventions. The paper also explains the advantages and limitations of current AI systems and identifies important research gaps. Finally, it proposes the idea of a unified intelligent child development system that can support parents, caregivers, and healthcare professionals.
Keywords	Artificial Intelligence, Machine Learning, Child Development, Personalized Nutrition, Obesity Prediction, Health Monitoring, Behavioral Health, Predictive Analytics
Field	Engineering
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-05-27

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