DEVELOPMENT OF INTELLIGENT FALL SENSING ALGORITHM IN AN AUTOMATED AIRBAG SYSTEM FOR ELDERLY - Dalam bentuk buku karya ilmiah
MUHAMMAD FASHA AQILLAH
Informasi Umum
Kode
25.05.673
Klasifikasi
000 - General Works
Jenis
Karya Ilmiah - Thesis (S2) - Reference
Subjek
Machine Learning
Dilihat
13 kali
Informasi Lainnya
Abstraksi
Falls can occur unexpectedly and pose significant risks, including fractures, reduced<br /> mobility, and increased dependence. This study proposes a real-time fall<br /> detection system using an IMU sensor to monitor body movements, including acceleration,<br /> angular velocity, and orientation. Four machine learning models, Support<br /> Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network<br /> (CNN), and Artificial Neural Network (ANN), were evaluated to determine the optimal<br /> model for fall detection. Data were collected through simulated fall and non-fall<br /> activities, including walking, standing, and different types of falls (forward, backward,<br /> and sideways), synchronized with IMU data at a sampling rate of 100Hz. The<br /> ANN model demonstrated the highest performance with 98% accuracy and a 0.1s<br /> latency, followed by CNN (97%, 0.3s), RF (97%, 0.3s), and SVM (90%, 0.5s). The<br /> system is designed to trigger an immediate protective response, such as airbag activation,<br /> upon detecting a fall. These results emphasize the potential of ANN-based<br /> algorithms for fast and reliable fall detection in wearable airbag systems.<br /> Keywords: IMU sensor, fall detection, machine learning, ANN, airbag vest.
Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
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Pengarang
| Nama | MUHAMMAD FASHA AQILLAH |
| Jenis | Perorangan |
| Penyunting | Willy Anugrah Cahyadi, Husneni Mukhtar |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S2 Teknik Elektro |
| Kota | Bandung |
| Tahun | 2025 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
