HAND GESTURE DETECTION TECHNOLOGY USING RASPBERRY PI CONVERTING HAND SIGNALS INTO TAGALOG WORDS

Abstract

This study presents a Raspberry Pi-based system for translating hand gestures into Tagalog words for government facilities such as SSS, Pag-IBIG, PhilHealth, and city halls, aiming to provide guidance and support to the Filipino deaf community. The Filipino Sign Language (FSL) was declared the national sign language of the Filipino deaf by Rodrigo Duterte in 2018, mandating its use in educational institutions, broadcast media, and workplaces. An Experimental Prototyping Method were used by the researchers to conduct this study. Experimental prototyping is the process for developing a concept and prototype that can be accepted or rejected. For the survey methodology's demographic profile and descriptive method of interpreting the 5-point Likert Scale indications, the Purposive Sampling Technique has been used. A survey questionnaire will be conducted by the researchers to the product targeted users. The Descriptive Type Survey Questionnaire Method analyzes data gathered to determine whether the intended users consider the prototype is acceptable.   Two sets of variables were chosen as respondents for this project: (15) Filipino deaf individuals in Fairview, Quezon City, and (15) normal-hearing individuals/workplace employees in Novaliches, Quezon City. Using Tinkercad, the researchers designed the prototype in both 2D and 3D. The prototype cover is made of ceramic glossy PVC wallpaper and plywood, measuring 32 cm in width and 23 cm in height. The results of testing using experimental prototyping revealed that the Raspberry Pi, as the microcomputer of the prototype hand gesture system, can successfully translate hand gestures into Tagalog words, serving as an effective communication tool for Filipino deaf individuals and normal-hearing people/workplace employees. The Raspberry Pi-based Hand Gesture Detection Technology is a reliable innovation that enables Filipino deaf individuals to communicate more effectively. The Hand Gesture Detection Technology Converting Hand Signals Into Tagalog Words is based on Filipino Sign Language (FSL). To develop a prototype using Raspberry Pi bridging communication gaps and enhancing accessibility. The technology also aims to contribute to creating inclusive environments for individuals with disabilities promoting social inclusion and equality. The system uses Python, MediaPipe, and Tensorflow frameworks for detection and gesture processes. The project demonstrates how CNN can be used to tackle computer vision problems accurately, potentially expanding other Filipino Sign Languages (FSL).