Design of an IoT-Based Smart Nutrition Tracking Prototype for Monitoring Toddler Nutritional Status at Posyandu

Abstract

The recording of toddler anthropometric data, including weight and height, at Posyandu Orchid is currently still dominated by conventional methods and manual data input. This mechanism is prone to human error during the recording conversion process and requires a relatively long service time. To address these constraints, this study aimed to design and develop an Internet of Things (IoT)-based automatic system for measuring toddlers’ weight and height, which was directly integrated with the Posyandu Orchid web application. The system hardware used an ESP32 microcontroller, a load cell sensor with an HX711 module, and a VL53L1X Time of Flight (ToF) sensor. The transmission of measurement data from the device to the web application utilized the MQTT communication protocol in real time. The test results showed that the load cell sensor produced an average accuracy of 98.47%. Meanwhile, the VL53L1X ToF sensor produced an average accuracy of 98.71%. The quantitative functional testing of the device showed a component functional success rate of 100%. Data packet transmission through the MQTT protocol was successful, with an average transactional latency of 2.200 seconds. The system integration test results demonstrated that the implementation of this system was able to automate the anthropometric data recording process accurately, reduce the administrative service time at Posyandu, and eliminate human error in recording toddlers’ weight and height measurement results.