Architecture and implementation of a smart-pregnancy monitoring system using web-based application

Today, people use web-based technologies to meet their information needs, socialise, communicate, and deal with formal and informal processes. At the same time, mobile versions of these applications provide people with great convenience in daily life. These applications include blood-pressure monitors, blood-glucose monitors, body-analysis scales, pulse oximeters, and activity and sleep trackers. Many of these products sync directly with a free mobile app that makes monitoring, viewing, storing, and sharing of health vitals simple and comprehensive. The data collected from the user is stored in a cloud-based application, then trained by intelligent algorithms that use machine learning for health aims so that the user can instantly see his or her status and development. In this study, the aim was to construct a cloud-based application specific to women for monitoring pregnancy. In the web-based application working with membership logic, members can access machine learning assisted calculators of the baby percentile, period tracker, pregnancy calendar, and baby vaccination schedule. Moreover, they can access augmented/virtual-reality-assisted visual training.