Firdaus, Ahmad Naufal (2019) Wearable Headset Untuk Mendeteksi Kantuk Dan Keadaan Fisiologis Pengendara Mobil Yang Terintegrasi Dengan Smartphone. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Berdasarkan data dari Badan Pusat Statistika Indonesia, pada tahun 2015, terjadi kecelakaan lalu lintas sebanyak 98,9 ribu kasus. Angka ini meningkat sebanyak 3,19 persen dibandingkan tahun sebelumnya, yaitu sebanyak 95,5 ribu kasus. Dari keterangan yang diberikan oleh Direktorat Lalu Lintas Polda Metro Jaya menyebutkan bahwa angka kecelakaan di wilayah ibukota lebih banyak disebabkan oleh kesalahan pengemudi, yaitu sebesar 90%. Berdasarkan kedua data di atas, diperlukan sebuah sistem monitor terhadap kantuk dan keadaan fisiologis pengemudi. Hal ini dimaksudkan untuk mengurangi tingkat kecelakaan akibat ketidaklayakan pengemudi dengan cara memberikan informasi terkait layak tidaknya keadaan pengemudi saat itu untuk berkendara. Sistem ini dirancang wearable dalam bentuk headgear untuk pengemudi mobil.
Proses deteksi keadaan fisiologis pengendara dapat diperoleh dengan cara mendapatkan angka kecepatan denyut nadi jantung. Pada tugas akhir ini, digunakan sebuah sensor partikel MAX30105 untuk memperoleh data kecepatan denyut nadi tersebut. Perangkat wearable ini juga dilengkapi dengan motion sensor MPU-6050 GY521 yang digunakan untuk memonitor gerakan kepala pengemudi. Apabila kecepatan denyut nadi rata-rata pengemudi di bawah 70 bpm dan gerakan kepala pengemudi terdeteksi sedang menunduk, maka perangkat akan mengirim sinyal ke perangkat smartphone penggunanya melalui koneksi bluetooth. Kemudian smartphone akan membunyikan suara alarm yang dapat memberikan peringatan dini kepada pengemudi. Dari 40 kali motion sensor test, perangkat berhasil mendeteksi gerakan kepala menunduk akibat mengantuk sebanyak 33 kali. Sehingga persentasi keberhasilannya adalah sebesar 82,25%.
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Based on the data from Statistics Indonesia, there are 98,9 thousand traffic accident cases in 2015. This number had increased 3.19% from the year before, which are 95,5 thousand cases. Based on statement given by Directorate of Traffic of Polda Metro Jaya, most of traffic accident cases, about 90% of it, were caused by driver fault itself. Based on both data, a monitoring system of drowsiness and physiological state of car driver is required. This is intended to reduce the rate of accidents due to the impropriety of the driver by providing information related to whether or not the driver’s condition is appropriate for driving. This system is designed wearable in the form of a headgear for the driver of the car.
The process of detecting the physiological state of the driver can be obtained by getting the average heart rate. In this final project, a MAX30105 particle sensor is used to obtain the pulse velocity data. This wearable device is also equipped with a motion sensor MPU-6050 GY521 which is used to monitor the movement of the driver’s head. If the average driver’s pulse rate is below 70 bpm and the driver’s head motion is detected while nodded, the device will send a signal to the user’s smartphone device via a bluetooth connection. Then the smartphone will sound an alarm sound that can provide an early warning to the driver. From 40 times the motion sensor test, the device successfully detects head down motion due to drowsiness 33 times. So the percentage of success is 82.25%.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSE 621.384 152 Fir w-1 2019 |
| Uncontrolled Keywords: | Wearable Headgear, Deteksi Kondisi Kantuk, Photoplethysmography, Accelerometer. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5103.2 Wireless communication systems. Two way wireless communication T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105 Data Transmission Systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK6564 Radio transmitter-receivers T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7871.674 Detectors. Sensors |
| Divisions: | Faculty of Electrical Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Ahmad Naufal Firdaus |
| Date Deposited: | 23 Jun 2021 14:04 |
| Last Modified: | 23 Jun 2021 14:04 |
| URI: | http://repository.its.ac.id/id/eprint/60618 |
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