Design and Implementation of a Real-Time IoT-Enabled Embedded Monitoring Architecture for an Off-Grid Infant Incubator - Joni Candra; Mhd Adi Setiawan Aritonang; Muhammad Nazwan (Information Technology and Science (ITScience), 2026)
Reliable real-time monitoring of infant incubators is essential in off-grid and resource-limited environments, where unstable power supply and limited infrastructure often compromise continuous operation and data reliability. This study aims to design and implement a real-time IoT-enabled embedded monitoring architecture that addresses the lack of dependable data acquisition and remote monitoring for infant incubators operating under off-grid conditions. The proposed system is developed using a microcontroller-based embedded platform integrated with temperature and environmental sensors, wireless communication modules, and a cloud-based data service. An off-grid photovoltaic power system supports continuous operation, while the embedded architecture is designed with power-aware and real-time constraints. The system adopts an edge-to-cloud approach, enabling local data acquisition and processing at the embedded level and real-time data transmission to a remote monitoring interface. The research methodology includes system architecture design, embedded firmware development, IoT communication implementation, and experimental performance evaluation under continuous off-grid operation. System performance is quantitatively evaluated in terms of data acquisition reliability, communication latency, real-time responsiveness, and operational stability. Experimental results show that the system achieves stable real-time monitoring with an average end-to-end communication latency below 200 ms, a sampling rate of 1 Hz, and continuous operation reliability exceeding 99% uptime during extended off-grid testing. The results demonstrate that integrating real-time embedded systems with IoT-based architecture significantly enhances monitoring reliability for infant incubators in off-grid environments. This study contributes a scalable embedded–IoT monitoring framework that can be extended to other cyber-physical systems operating under constrained energy and infrastructure conditions