An Intelligent IOT-Enabled Smart Diaper System With AI-Driven Health Monitoring For Infant Care

Neonatal care is incomplete without infant hygiene and health monitoring, but conventional diapers are not equipped with real-time sensing, which may cause discomfort, rashes, and even infection due to the prolonged contact with moisture. This paper suggests an AI-based smart diaper system with the incorporation of moisture and temperature sensors along with IoT-based wireless communication for real-time monitoring. The system repeatedly monitors for levels of moisture, temperature changes, and urinal patterns, giving caregivers real-time notifications through a mobile app or cloud portal. Machine learning software is utilized in predicting diaper levels of saturation as well as for analyzing urination trends to prepare for future changes and enhanced care for the infants. By applying low-power embedded technology, the system manages its energy efficiently but with high levels of accuracy when detecting moisture. Analysis by AI enables early detection of possible health problems like dehydration or urinary tract infection (UTI), and edge computing preserves privacy with decreased latency through data processing at the edge. Experimental tests show high accuracy in detection with low false positives, and it is tested to show its practicality for real-world deployment. Future advancements involve the creation of biodegradable, ultra-slim sensors for enhanced comfort, wireless charging technology for longer device life, and enhanced AI capabilities for sophisticated health diagnostics. The smart diaper design can also be applied to the elderly care and medical fields, solving hospital and residential care incontinence issues. With the integration of IoT, AI, and smart sensing technologies, the research offers an intelligent, sustainable solution for the management of infant hygiene, enhancing the development of AI-based healthcare systems.