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Development of Communication System between TPMS and Server using Combination of OFDM and Convolutional Code Technique Based on SDR Briantoro, Hendy; Montolalu, Billy; Farouq, Ardiansyah Al
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2024

The Tire Pressure Monitoring System (TPMS) has evolved into an essential element of contemporary vehicles, playing a pivotal role in enhancing road safety and the overall driving experience. Traditionally, TPMS systems rely on dedicated hardware components for the collection and transmission of tire pressure data to the vehicle's onboard computer and the data is visible only to the driver. In this research, we have developed a wireless communication system between TPMS and a server, enabling tire pressure data to be accessible not only to the driver but also remotely traceable by others. To build a reliable communication system, we utilized a combination of Orthogonal Frequency Division Multiplexing (OFDM) and Convolutional Code technologies. This system is implemented using Software-Defined Radio (SDR) technology. This communication method employs OFDM to enhance data throughput and integrates Convolutional Code to mitigate errors in received data. Consequently, this approach achieves a maximum throughput of 119.19MBps when utilizing the OFDM system alongside 16QAM modulation. The bit error rate for received data without coding stands at 5.77%, but the application of Convolutional Code with a 1/2 code rate effectively reduces this error rate to 3.85%. This system improves the reliability of TPMS communication with the server while also ensuring a consistently high throughput. It enhances road safety and remote monitoring capabilities.

Field oriented control driver development based on BTS7960 for physiotherapy robot implementation Halisyah, Andi Nur; Adiputra, Dimas; Al Farouq, Ardiansyah
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1486-1495

In conjunction with sustainable development goal 3 (SDG 3), it is important to develop a national electrical component for physiotherapy robot development. This study aimed to develop an open-loop field-oriented control (FOC) driver utilizing BTS7960. The driver utilized three BTS7960s that produce sinewave with variable angular frequency (ω). The research then compared the open-loop FOC driver with electronics speed controller (ESC) performance to drive a brushless DC (BLDC) motor with an initial rotation per minute (RPM) of 400, 500, and 600. The main observation was RPM reduction when the BLDC motor was subjected to loads of 20, 35, 50, 65, and 80 gr. The result showed that the open-loop FOC driver performed better, especially on an 80 gr load. For an initial RPM of 600, the RPM reduced to 100 when controlled with an open-loop FOC driver, but lesser when controlled using ESC. The open-loop FOC driver produces higher torque on the BLDC motor so it could rotate with less reduction compared to ESC, which is evident. The open-loop FOC driver can be easily developed using BTS7960 with a settling time of 4 seconds. However future studies should still consider close-loop FOC drivers to achieve higher torque performance and faster transient response for physiotherapy robot applications.

Analisa Kesalahan Trajektori dan Algoritma Solusi Invers pada Robot Lengan Berdasarkan Jaringan QACA-RBF Ardiansyah Al Farouq; Presto Fani; Muhammad Yanuar Muhaimin
Journal of Computer Electronic and Telecommunication Vol. 1 No. 1 (2020): July
Publisher : Institut Teknologi Telkom Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v1i1.49

Dalam rangka meningkatkan akurasi posisi dan trajektori dari robot lengan UR5, algoritma solusi invers pada robot lengan berdasarkan jaringan QACA-RBF diajukan. Desain algoritma ini menggunakan model prediksi melalui jaringan saraf dan menggunakan algoritma koloni semut kuantum untuk mengoptimalkan bobot keluarannya. Dalam memecahkan masalah ini, algoritma koloni semut kuantum memiliki presisi konvergen yang rendah dan mudah jatuh ke dalam solusi local optimal dalam algoritma solusi invers dari derajat kebebasan pada robot lengan, maka peningkatan pengukuran seperti local optimasi dan batas maksimum minimum feromon dan variasi dibutuhkan. Dengan membandingkan hasil simulasi dari hasil simulasi robot lengan UR5 dan hasil simulasi berdasarkan jaringan saraf ACA, QACA, dan RBF untuk mendapatkan posisi dan gerak trajektori pada titik ruang dengan kepresisian disetiap algoritma. Dengan skema tersebut agar dapat membuktikan kelayakan algotirma jaringan QACA-RBF.

Perancangan Sistem Sortir Limbah Plastik Warna Berdasarkan Warna Menggunakan PLC Fayola Liyani; Annisa, Aulia Rahma; Al Farouq, Ardiansyah; Yudha Adhitya, Ryan
Journal of Computer Electronic and Telecommunication Vol. 4 No. 1 (2023): July
Publisher : Institut Teknologi Telkom Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v4i1.365

Produksi dan penggunaan terhadap plastik sekali pakai yang semakin meningkat, sehingga diperlukan proses daur ulang pada limbah sampah plastik yang efisien untuk mengurangi dampak negatifnya. Dalam proses daur ulang, diperlukan tahapan proses penyortiran limbah sampah plastik berdasarkan warna. Saat ini, proses penyortiran limbah sampah plastik masih dilakukan secara manual dan membutuhkan tenaga kerja manusia. Pada penelitian sebelumnya sudah terdapat inovasi untuk mengatasi permasalahan tersebut yaitu sistem sortir barang berdasarkan warna menggunakan arduino. Pada penelitian ini penulis mengusulkan untuk mengatasi permasalahan tersebut yaitu dengan sistem sortir limbah plastik berdasarkan warna menggunakan PLC, dengan deteksi webcam sebagai input dan pneumatik sebagai output. Metode pengambilan deteksi warna menggunakan OpenCV python untuk memproses video dalam analisis citra dan untuk komunikasi PLC dengan PC menggunakan python serial. Proses awal yaitu saat warna dideteksi oleh webcam setelah itu pneumatik akan aktif mendorong limbah plastik tersebut sesuai warnanya. Hasil percobaan menunjukkan bahwa sistem ini 100% akurat dalam keberhasilan penyortiran warna merah, biru dan hijau. Dalam proses deteksi warna, dibutuhkan waktu rerata yang berbeda antar warna, yakni 6,78 detik, 7,78 detik, dan 8,87 detik untuk warna merah, hijau, dan biru secara berurutan.

Development of Communication System between TPMS and Server using Combination of OFDM and Convolutional Code Technique Based on SDR Briantoro, Hendy; Montolalu, Billy; Farouq, Ardiansyah Al
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 13 No. 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2024

The Tire Pressure Monitoring System (TPMS) has evolved into an essential element of contemporary vehicles, playing a pivotal role in enhancing road safety and the overall driving experience. Traditionally, TPMS systems rely on dedicated hardware components for the collection and transmission of tire pressure data to the vehicle's onboard computer and the data is visible only to the driver. In this research, we have developed a wireless communication system between TPMS and a server, enabling tire pressure data to be accessible not only to the driver but also remotely traceable by others. To build a reliable communication system, we utilized a combination of Orthogonal Frequency Division Multiplexing (OFDM) and Convolutional Code technologies. This system is implemented using Software-Defined Radio (SDR) technology. This communication method employs OFDM to enhance data throughput and integrates Convolutional Code to mitigate errors in received data. Consequently, this approach achieves a maximum throughput of 119.19MBps when utilizing the OFDM system alongside 16QAM modulation. The bit error rate for received data without coding stands at 5.77%, but the application of Convolutional Code with a 1/2 code rate effectively reduces this error rate to 3.85%. This system improves the reliability of TPMS communication with the server while also ensuring a consistently high throughput. It enhances road safety and remote monitoring capabilities.

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