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All Journal Techne : Jurnal Ilmiah Elektroteknika Jurnal Telematika
Endang Djuana, Endang
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Model Sistem Monitoring Perlintasan Kereta Api Menggunakan Arduino Mega Triyanto, Irfan Rusidy; Djuana, Endang; Gozali, Ferrianto; S, Kuat Rahardjo T; Sunarto, Sunarto
Jurnal Telematika Vol. 12 No. 2 (2017)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v12i2.192

Abstract

Monitoring system at railway crossing is a system that can be used to monitor train and the railway crossing that will be passed by train. In designing simulation for this monitoring system model, Arduino Mega is needed as a microcontroller. Besides that, radio-frequency identification (RFID) sensor is used to identify the train and ultrasonic sensor is used to detect the train. Data from train and railway crossing will be stored in database. This data that have been stored will be displayed in a server computer. In this display, there will be data from train and the railway crossing. A router is used to send the data to the Internet and an Ethernet module is used to bring the data from Arduino Mega. Experiments were conducted on a model railroad through a computer server. In the test results, the use of features such as train detection of ultrasonic sensors and sensor RFID as the train identification have been tested to work well. The process of sending data from Arduino Mega to be displayed on the display monitor in the server computer is depending on traffic data at the time of testing.Sistem monitoring pada perlintasan kereta api merupakan sistem yang dapat digunakan untuk melakukan deteksi pada kereta dan identifikasi perlintasan yang dilaluinya. Pada perancangan simulasi untuk model sistem monitoring ini, diperlukan Arduino Mega sebagai mikrokontroler dan sensor radio-frequency identification (RFID) dalam proses identifikasi kereta dan  sensor ultrasonik dalam proses deteksi kereta. Data kereta api dan perlintasan disimpan pada sistem basis data. Data yang telah disimpan ditampilkan pada komputer server. Pada tampilan server tersebut, terdapat data kereta dan juga perlintasan. Untuk pengiriman data, dipergunakan router untuk mengirim data ke Internet dan modul Ethernet untuk meneruskan data dari Arduino Mega. Uji coba dilakukan pada model kereta api untuk ditampilkan pada komputer server. Hasil pengujian menunjukkan bahwa dengan menggunakan fitur pendeteksi kereta berupa sensor ultrasonik dan pengidentifikasi kereta berupa sensor RFID, proses identifikasi kereta bekerja dengan baik. Adapun, proses pengiriman data dari Arduino Mega hingga dapat ditampilkan oleh layar monitor komputer server tergantung dari lalu lintas data pada waktu pengujian dilakukan.
Rancang Bangun Sistem Kamera Pengawas dengan Pengenalan Wajah untuk Keamanan Berbasis Blynk Legacy Zamorano, Chandra I.; Prawiroredjo, Kiki; Julian, E. Shintadewi; Djuana, Endang
Techné : Jurnal Ilmiah Elektroteknika Vol. 22 No. 2 (2023)
Publisher : Fakultas Teknik Elektronika dan Komputer Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31358/techne.v22i2.381

Abstract

Covid-19 pandemic that has occurred since the beginning of 2020 has brought down all aspects of the country, starting from community activities to the economy. This has an impact on increasing the number of crimes committed by the community such as theft, robbery or other crimes. In this study, a room security system is proposed that uses a surveillance camera with a face recognition ability that records the face image of an intruder and records events as evidence of an intrusion. This system sends information quickly and automatically to the Android application user if an intruder who the camera doesn't recognize enters his house. The smartphone application user can control camera movements inside the house to monitor the movement of intruders and record the incident. This system uses 5 ESP32-CAM cameras. One camera is used to recognize and record the intruder's face image placed in front of the house and four cameras as surveillance and face recognition cameras are placed inside of the house. Each camera is driven by a servo motor controlled by a ESP8266 microcontroller. From the test results it is known that the maximum distance that the cameras still recognize the face image of an intruder or the home owner's face image is 2 meters when the light is bright. When it is dim, the camera in front of the house recognizes the face images up to 0.5 meters while the cameras inside of the house recognize the face images up to 1 meter. The average delay time for sending data from the camera system to application user is 201 ms to 617 ms.
Co-Authors E. Shintadewi Julian, E. Shintadewi Ferrianto Gozali Irfan Rusydi Triyanto Kiki Prawiroredjo Kuat Rahardjo T.S. Sunarto Sunarto Zamorano, Chandra I.