<![CDATA[Neonatal mortality in low- and middle-income countries remains high, partly because early physiological deterioration is detected late and continuous monitoring is limited outside specialized units. To address this gap, this study presents NeoCare: Telehealth System with Intelligent Notification for Neonatal Care, a multi-actor platform that integrates neonatal data management, vital-sign monitoring, and machine-learning–based alerts. The research followed a software engineering approach comprising stakeholder and context analysis, requirements engineering, clinical data acquisition, system and database design, intelligent notification model design, and prototype implementation. Retrospective neonatal records from two Indonesian referral hospitals were used to characterize heterogeneous and homogeneous clinical populations and to inform the design of classification features for vital-sign–based risk assessment. NeoCare is realized as a layered architecture with sensor, device, communication, processing-intelligence, and application layers. The prototype includes web and mobile interfaces tailored to four actor groups: hospital administrators, doctors, midwives, and parents. Administrators manage users, hospitals, vital-sign data, and machine-learning models while supervising alert output. Doctors and midwives access dashboards that display neonatal lists, detailed histories, trend graphs, and consultation management, supporting triage and longitudinal follow-up. Parents use a simplified mobile interface to view their baby’s status, monitor vital-sign trends, receive alerts, and schedule consultations. The system embeds an intelligent notification mechanism that flags abnormal patterns and presents them through color-coded indicators and concise messages. The results demonstrate the technical feasibility and coherence of a role-based, data-driven telehealth platform for neonatal care, providing a solid foundation for future work on clinical validation, device integration, and large-scale deployment.]]>
