Digital Infant Scale with Fuzzy Decision Support for Growth Monitoring

Monitoring a child's growth and development is crucial, especially during the first 1000 days of life, due to the rapid changes. Various factors, including nutritional problems and environmental conditions, significantly influence early childhood growth and development. Nutritional issues often arise from an imbalance between intake and bodily needs, manifesting as stunting and low birth weight. Collecting anthropometric data, particularly body weight and length, is essential for assessing children's nutritional status. This study advances the development of a digital scale that combines a load cell sensor connected to an ADS1232 module for weight measurement and a rotary encoder for length measurement. Further analysis on a personal computer (PC) calculates body mass index (BMI/A), weight-for-age (W/A), and length-for-age (L/ A) using the FDSS, focusing on children aged 0–12 months. The scale results accurately measure body weight and length, with a minimum error rate of 0.52% and 0.42%, respectively. Of the 49 participating subjects, normal results were obtained for 44 subjects based on W/A, 41 on L/A, and 41 on BMI/U. The classification results were consistent with established anthropometric standards, confirming the efficacy of the FDSS in assessing infant conditions. Further development of this study includes enhancing the design and materials used to meet commercial standards, incorporating Internet of Things (IoT) technology to facilitate system integration and classification, and focusing exclusively on measuring and monitoring infant growth and development.