Smart Assistant for Deaf and Mute Using Micro:bit
Abstract
Deaf and mute people are an integral part of society. They have difficulty speaking or are unable to speak. Therefore, to overcome this difficulty, sign language emerged as a method of non-verbal communication commonly used by deaf and mute people. The problem that arises with sign language is that healthy people who do not suffer from hearing or speaking problems do not learn this language. This problem is dangerous because it creates a barrier between them. It is possible to solve this problem by taking advantage of modern technologies as they are more applicable and cheaper. In this research, the micro:bit was used as a means aimed at facilitating communication between deaf and mute people and other people through human-computer interaction. A program has been created that transforms what a mute wants into luminous expressive forms that can be easily understood by healthy people, such as his desire to eat or drink or any other needs. Another important point is to alert the deaf person to the presence of an external sound (car alarm, someone calling to the deaf person, etc.) by lighting up the micro:bit. The micro:bit is easy to use and low-cost. It was also improved by being developed into a watch worn by a disabled person. This device is expected to support deaf and mute people (especially children) in communicating effectively with others and regaining a sense of normalcy in their daily lives. This research idea was applied to a sample of ten deaf and mute children of different ages ranging from (2-10 years) after training them on how to use the program represented by the manual watch. It was noted that children under the age of six (4 children) benefited more than others, because children over 6 years old are able to express their needs and meet them compared to younger children.
Keywords
Full Text:
PDFReferences
Mishra, S. K., Sinha, S., Sinha, S., & Bilgaiyan, S. (2019). Recognition of hand gestures and conversion of voice for betterment of deaf and mute people. In Advances in Computing and Data Sciences: Third International Conference, ICACDS 2019, Ghaziabad, India, April 12–13, 2019, Revised Selected Papers, Part II 3 (pp. 46-57). Springer Singapore.
Al Rakib, M. A., Rahman, M. M., Anik, M. S. A., Masud, F. A. J., Rahman, M. A., Islam, S., & Abbas, F. I. (2022). Arduino Uno based voice conversion system for dumb people. European Journal of Engineering and Technology Research, 7(2), 118-123.
Al-Qarni, S. A., & Omran, A. M. (2021). The Effect of Artificial Intelligence (Micro:bit) in Raising the Motivation Towards Learning Programming Among the Students of Educational Technology at King Abdulaziz University in Jeddah: أثر الذكاء الاصطناعي المايكروبت (Micro:bit) في رفع الدافعية نحو تعلُّم البرمجة لدى الطالبات في مقرر تقنيات التعليم بجامعة الملك عبد العزيز بجدة. مجلة العلوم التربوية و النفسية, 5(30), 58-76.
Saleem, M. I., Siddiqui, A., Noor, S., Luque-Nieto, M. A., & Otero, P. (2022). A Novel Machine Learning Based Two-Way Communication System for Deaf and Mute. Applied Sciences, 13(1), 453.
MILIĆ, M., KUKULJAN, D., & KURELOVIĆ, E. K. (2018). Micro: Bit Immplementation in ICT Education. The Eurasia Proceedings of Educational and Social Sciences, 11, 128-133.
Austin, J., Baker, H., Ball, T., Devine, J., Finney, J., De Halleux, P., ... & Stockdale, G. (2020). The BBC micro: bit: from the UK to the world. Communications of the ACM, 63(3), 62-69.
Cachetas, H., Martins, V. M., Costa, M. F., & Vieira, J. P. (2022). Codelastro. A STEM project for code learning with astronomical ideas.
Jeeva, M. P. A., Nagarajan, T., & Vijayalakshmi, P. (2020). Adaptive multi‐band filter structure‐based far‐end speech enhancement. IET Signal Processing, 14(5), 288-299.
Kumuda, S., & Mane, P. K. (2020, February). Smart Assistant for Deaf and Dumb Using Flexible Resistive Sensor: Implemented on LabVIEW Platform. In 2020 International Conference on Inventive Computation Technologies (ICICT) (pp. 994-1000). IEEE.
Battina, D. S., & Surya, L. (2021). Innovative study of an AI voice based smart Device to assist deaf people in understanding and responding to their body language. SSRN Electronic Journal, 9, 816-822.
Ahmad, M. S., Puspanathan, K., Revi, T., & Tan, H. H. (2021). Automated Appliances using Microbit. Multidisciplinary Applied Research and Innovation, 2(2), 94-100.
Naik, A., Nair, V., Mishra, N., & Dubey, A. (2022). Convo Hand–Smart Glove (No. 7802). EasyChair.
Abualkishik, A., Alzyadat, W., Al Share, M., Al-Khaifi, S., & Nazari, M. (2023). Intelligent Gesture Recognition System for Deaf People by using CNN and IoT. International Journal of Advances in Soft Computing & Its Applications, 15(1).
DOI: https://doi.org/10.33387/protk.v12i2.8091
Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Editorial Office :
Address: Jusuf Abdulrahman 53 Gambesi, Ternate City, Indonesia.
Email: protek@unkhair.ac.id, WhatsApp: +6282292852552