Developing a Digital Anthropometry Device Using IoT-Based Sensors for Monitoring Small Babies

Background Accurate anthropometric measurements are essential for monitoring the growth and health of small babies, particularly those born with low birth weight (LBW) or prematurely. Objectives This study aims to develop a digital anthropometry device integrated with Internet of Things (IoT) technology to support early detection, real-time monitoring, and data reporting in primary healthcare settings. Method In this study, a Research and Development (R&D) design based on the Borg and Gall model, involving stages of needs assessment, device design, prototyping, expert validation, and limited field testing, was used. The device incorporates a load cell, ultrasonic sensors (JSN-SR04T), and an ESP32 microcontroller connected to cloud platforms (Firebase/ThingsBoard). Usability and feasibility were evaluated through mixed methods involving healthcare workers and parents. Results The outcome of this protocol is a functional, validated, and user-friendly IoT-based digital baby scale capable of accurately measuring weight and length. The device is expected to enhance data accuracy, support growth monitoring at the community level, and integrate with existing public health reporting systems. Discussion This innovation will address long-standing challenges in neonatal growth monitoring by offering a scalable, real-time, accurate measurement and supporting data-driven interventions at the community level. The device’s design aligns with current digital transformation efforts in public health, although further testing is needed to assess its long-term implementation and cost-effectiveness. Conclusion The study presents a novel IoT-based anthropometry device that improves measurement accuracy, usability, and data integration in the care of small babies. It holds promise for strengthening primary health services and malnutrition prevention strategies.