HUMAN MOVEMENT RECOGNITION BERBASIS IOT

Authors

  • Ida Bagus Made Harisanjaya Adi Nugraha
  • I Gusti Putu Mastawan Eka Putra
  • Anak Agung Ngurah Gde Sapteka

Keywords:

gyro, HMR, fall, IoT, LoRa

Abstract

Every year science and technology develops very rapidly. Humans can create sophisticated sensors, one of which is the gyro sensor. By utilizing gyro, humans can create various new innovations in the field of technology such as Human Movement Recognition (HMR). HMR means human movement recognition. Human movement recognition technology has become a new research direction in the field of Artificial Intelligence (AI) . HMR can be used to monitor the elderly and provide notifications when the elderly fall. A sudden, unintentional and unexpected event that causes the elderly to be on a lower level or on the ground is the definition of a fall. The system will also implement the Internet of things (IoT). By implementing IoT , it is hoped that monitoring the movement of the elderly can be real-time and can be monitored remotely. In addition to IoT , the system will also be integrated with Long Range (LoRa) technology so that the system can operate in areas where cellular signals and internet networks are difficult. In this study, the movement recognition system can scan falling movements with a good percentage of success. The fall motion scan has a 90% success rate.

References

Al Amin, M., & Juniati, D. (2017). Klasifikasi Kelompok Umur Manusia Berdasarkan Analisis Dimensi. Jurnal Ilmiah Matematika, 2(6), 1–10.

Arifien, Z., Bachtiar, F. A., & Yudistira, N. (2021). Pengenalan Aktivitas Manusia Menggunakan Sensor Akselerometer Dan Giroskop Pada Smartphone Dengan Metode K-Nearest Neighbor. Sentrin, 9(1).

Didik Widianto, E., Faizal, A. A., Eridani, D., Dwi, R., Augustinus, O., & Pakpahan, M. S. (2019). Simple LoRa Protocol: Protokol Komunikasi LoRa Untuk Sistem Pemantauan Multisensor Simple LoRa Protocol: LoRa Communication Protocol for Multisensor Monitoring Systems. Telka, 5(2), 83–92.

Jefiza, A. (2017). Sistem Pendeteksi Jatuh Berbasis Sensor Gyroscope Dan Sensor Accelerometer. Sistem Pendeteksi Jatuh Berbasis Sensor Gyroscope Dan Sensor Accelerometer, 87, 111.

Putra, G. G. (2019). Human Activity Recognition using Smartphone. International Journal of Recent Technology and Engineering, 8(4), 10159–10163.

Ramandita, R. A., Kusuma, W. A., & Minarno, A. E. (2021). Klasifikasi Aktifitas Pada Human Activity Recognition Dataset Menggunakan Logistic Regression. 3(5), 425–432.

Ratna, S. (2020). Sistem Monitoring Kesehatan Berbasis Internet Of Things (IoT). Al Ulum Jurnal Sains Dan Teknologi, 5(2), 83. Vera, V. (2021). Analisis Laporan Kejadian Jatuh pada Pasien Lansia Saat Rawat Inap di Rumah Sakit Immanuel Bandung Periode 2014-2016. Journal of Medicine and Health, 3(2), 127–136.

Yanziah, A., Soim, S., & Rose, M. M. (2020). Analisis Jarak Jangkauan Lora Dengan Parameter Rssi Dan Packet Loss Pada Area Urban. Jurnal Teknologi Technoscientia, 13(1), 27–34.

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Published

2023-01-23

How to Cite

Ida Bagus Made Harisanjaya Adi Nugraha, I Gusti Putu Mastawan Eka Putra, & Anak Agung Ngurah Gde Sapteka. (2023). HUMAN MOVEMENT RECOGNITION BERBASIS IOT . Prosiding Seminar Nasional Terapan Riset Inovatif (SENTRINOV), 8(1), 263 - 270. Retrieved from https://proceeding.isas.or.id/index.php/sentrinov/article/view/1175