ESP32-Based Smart Gloves for Message Transmission via Hand Gestures Using Telegram Application
Keywords:
Smart Gloves, MPU9250, Microcontroller, Telegram, Hand GesturesAbstract
This research aims to develop an ESP32-based Smart Gloves system that facilitates message transmission via hand gestures, integrating Telegram as a communication platform. The system utilizes an MPU9250 motion sensor embedded in the glove to detect hand gesture patterns, which are then processed by the ESP32 microcontroller to convert these gestures into text messages. The translated messages are sent in real-time through the Telegram application to the intended recipient. This process offers a solution for users with verbal communication limitations, such as stroke patients, enabling them to communicate easily and effectively. Testing results demonstrate that the system can accurately convert hand gestures into text messages and transmit them via Telegram promptly.
References
Pratama, A. P. (2023, November 14). Teknologi IoT dalam Sistem Pengenalan Bahasa Isyarat. Retrieved from www.techinsight.id
Wijaya, B. I. (2024, March 8). Solusi Inovatif: Menggunakan Arduino untuk Pengenalan Gerakan Tangan. Retrieved from kumparan.com
Sari, D. P., & Sulistyo, H. R. (2022). Pengembangan Sistem Pengenalan Bahasa Isyarat Berbasis IoT dengan Arduino. Jurnal Teknologi Informasi, 6(2), 102-112.
Chaudhary, R., & Sharma, A. (2019). Gesture Recognition Using Arduino: A Step Towards Sign Language Communication. International Journal of Research in Computer Science, 10(4), 23-30.
Kumar, R., & Singh, A. (2021). IoT-based Systems for Real-Time Gesture Recognition: A Review. International Journal of Engineering Research and Technology, 9(5), 177-184.
Luthfi, D., & Kurniawan, S. (2023). Design and Implementation of IoT-based Sign Language Glove Using Arduino. Journal of Electronics and Communication Engineering, 18(3), 215-225.
Zulfikar, R., & Hidayat, A. (2022). Sistem Monitoring Gerakan Tangan Menggunakan Arduino dan Sensor Flex. Jurnal Teknologi dan Rekayasa, 12(2), 88-95.
Hidayat, F. F., & Arifin, M. (2020). Pengembangan Sistem Pengenalan Tanda Tangan Menggunakan Arduino Nano. Jurnal Rekayasa Elektronika, 5(1), 45-52.
Harsono, A., & Putra, M. A. (2023). Implementasi Sistem Pengenalan Gerakan Tangan untuk Komunikasi Bahasa Isyarat dengan Arduino. Jurnal Sistem Komputer, 9(3), 34-40.
