Body-part identification learning for preschool children using internet of things.

Abstract

Children can identify body parts either on dolls or on their bodies. The inability of toddlers (aged 2-3 years) to demonstrate body parts can indicate potential delays in language, cognitive, and body scheme development. The integration of teaching aids for body part identification with the Internet of Things (IoT) offers several advantages, including automation and customization of activities, digital storage of activity results for easy accessibility, real-time and accurate evaluation and feedback, as well as the freedom to repeat activities without limitations. This study focuses on implementing the integration of body part identification trainers with IoT, following the five phases of IoT development: initialization, analysis, design, implementation, and evaluation. The initialization phase involves problem identification, and the position of this research is based on a literature study. The analysis phase establishes parameters for measuring the functionality and performance of the system, as well as requirements for software and hardware components. The design phase produces the system architecture and system flowchart. The implementation phase results in a prototype integrating hardware and software components. Evaluation results based on the predefined functionality and performance parameters set during the analysis phase indicate that all system functionalities have been successfully achieved. The system demonstrates a response time below 1 second for sensor buttons and LED lights, and the feedback system shows 100% accuracy. This prototype highlights the potential and opportunities of implementing IoT to support learning at various levels, specifically at the pre-school level, as shown in this study.