INTERNET OF THINGS-BASED CHILD STUNTING DETECTION SYSTEM FOR SUPPORTING SUSTAINABLE DEVELOPMENT GOALS

This research focused on the real-time detection of child stunting using measurement tools powered by Internet of Things (IoT) technology. Child stunting refers to a condition characterized by impaired height growth that does not align with a child's age. One of the government's primary strategies to combat stunting is through Posyandu (Indonesian community-level health service centers) that play a vital role in public health initiatives. Currently, most Posyandu in Indonesia rely on manual methods for monitoring child nutrition, with limited adoption of IoT technology for this purpose. This research introduced a system comprising both hardware and software components to address this gap. The hardware includes a load cell sensor for measuring weight and an ultrasonic sensor for measuring height. These sensors are integrated with an ESP32 microcontroller for data processing. The software component is a web- based application that receives data transmitted from the hardware via IoT technology. During testing, the hardware demonstrated accurate measurements of children's weight and height, with an average error of only 0.14 kg for weight and 0 mm for height. Furthermore, the web application performed reliably, providing stunting detection information with a 100% success rate. This study supports Sustainable Development Goals (SDGs).