Smart Pregnancy Care System: Real-time Fetal Brain Abnormality Detection and Maternal Health using IoT

The Smart Pregnancy Care System presents an advanced healthcare monitoring solution that leverages Machine Learning (ML), Artificial Intelligence (AI), and Internet of Things (IoT) technologies to enhance maternal health and fetal well-being. This system integrates real-time monitoring of physiological parameters with intelligent image-based diagnostics to enable early detection of fetal brain abnormalities and timely intervention during pregnancy. Maternal vital signs— including heart rate, body temperature, and blood oxygen saturation (SpO₂)—are continuously tracked using wearable IoT sensors connected to an ESP-32 microcontroller. Simultaneously, fetal health is assessed through ultrasound imaging, where the YOLO (You Only Look Once) deep learning object detection algorithm identifies potential brain abnormalities. In case of any anomaly or when sensor readings exceed predefined thresholds, immediate alerts are dispatched to healthcare professionals through a notification system, facilitating rapid response. This dual-modality system combines cloud computing, machine learning, and IoT for proactive and preventive maternal-fetal care, aiming to reduce health risks and improve pregnancy outcomes through intelligent automation and continuous Monitoring.