<![CDATA[This research addresses the pressing issue of monitoring the growth and nutritional status of infants aged 0-12months, a critical period for health and development. Inadequate growth monitoring can lead to undetected nutritionaldeficiencies and long-term health consequences. To tackle this problem, the study developed an innovative Growth MonitoringSystem that utilizes length, weight, and head circumference as key indicators of nutritional status. The system integratesadvanced technology, including an ESP-32 microcontroller, load cell sensors for weight measurement, ultrasonic sensors forheight measurement, and infrared sensors for head circumference measurement. The methodology involved collecting datafrom 30 respondents, where the system automatically recorded measurements and generated growth curves displayed on aweb-based platform. The accuracy of the measurements was evaluated, revealing significant variability in error rates.Specifically, the highest error in head circumference measurement was recorded at 25.38%, while the weight measurementexhibited a lower error rate of -20.47%. These results highlight the challenges in achieving precise measurements but alsodemonstrate the system's capability to provide essential data for assessing infant growth. In conclusion, the developed GrowthMonitoring System represents a significant advancement in child health monitoring, offering a reliable and efficient methodfor tracking the growth of infants. Despite the observed measurement errors, the system's automated data collection andanalysis capabilities provide valuable insights into nutritional status. The research emphasizes the potential for broaderimplementation of such systems in pediatric clinics and national health programs, ultimately contributing to improved healthoutcomes for infants. By enhancing the accuracy and accessibility of growth monitoring, this research paves the way for moreeffective interventions in early childhood nutrition and health.]]>
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