Car Parking Distance Controller Using Ultrasonic Sensors Based On Arduino Uno

Susilo, Jenli; Febriani, Anita; Rahmalisa, Uci; Irawan, Yuda

doi:10.18196/jrc.25106

Cited by 21 publications

(13 citation statements)

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“…Dan sensor HC-SR04 akan mendeteksi orang yang lewat dan df-player berbunyi -Mohon Perhatian Untuk Tidak Lupa Mencuci Tangan‖ dan selanjutnya orang akan mendekat ke wastafel dan mencuci tangan dengan cara menaruh atau mendekatkan tangan ke kran maka kran akan otomatis pumpa mengeluarkan sabun dan air dengan cara berurutan menggunakan sensor infrared proximity dan saat yang bersamaan modul df-player juga akan berfungsi dengan berbunyi cara cuci tangan yang baik dan benar [10]. Yang terahir sensor HC-SR04 yang telah di pasang diatas tendon air akan mendeteksi volume air, jika air yang di dalam tendon telah habis atau tinggal sedikit maka telegram akan menerima notifikasi dari Arduino supaya tendon tetap terisi [11].…”

Section: Gambar : Blok Diagram Penelitian Sebelumnyaunclassified

Monitoring Pengunaan Daya 3 Phase Dengan Notifikasi Berbasis Telegram

Hariski¹,

Wicaksono²

2022

jeetech

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Voltage Monitoring, current, and power on the panel are a must because this monitoring can see the magnitude of the voltage, current, cos phi, and power on the load. One of these monitoring is to determine the quality of electricity, such as drop voltage, low cos phi. In this era of technology, monitoring can be viewed using mobile, so users don't need to come to the panel and see the measurement results, users look at the smartphone device. In this research, a researcher will make a tool that can monitor electrical measurements in 3 phase panel using mobile on a microcontroller. Data will process from the current transformer at 3 phase panel by the ESP8266 microcontroller to convert into three-phase voltage, current, and power figures. The ESP8266 microcontroller which is equipped with wifi can be used for remote monitoring. An android smartphone with a telegram software application will function as communicate via wifi with the ESP8266 microcontroller so that all measurement data can also be monitored on the smartphone. The reading of the electric power monitoring tool has an accuracy of 97.39%. This shows that the tool can function very well.

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Section: Gambar : Blok Diagram Penelitian Sebelumnyaunclassified

Monitoring Pengunaan Daya 3 Phase Dengan Notifikasi Berbasis Telegram

Hariski¹,

Wicaksono²

2022

jeetech

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“…Arduino [12], [13], [14], [15] merupakan suatu rangkaian elektronik yang mempunyai komponen utama sebuah chip mikrokontroler berjenis Alf and Vegard's Risc Processor (AVR). Dimana kegunaan Arduino ini dapat mengintegrasikan sistem untuk pengontrolan pada sebuah sistem cerdas berbasis Artificial Intelligence (AI).…”

Section: Arduinounclassified

Rancang bangun sistem radar pintar pengontrol pengisian air berbasis mikrokontroler

2022

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Setiap rumah penduduk yang bertempat tinggal khususnya di kawasan perumahan memiliki tandon air sebagai tempat penyimpanan air, sebagaimana kondisi yang ada juga pada perumahan yang berada di lokasi perumahan xyz di wilayah cileungsi. Permasalahan yang ada pada tandon air di perumahan kurangnya pengontrolan diantaranya kondisi mesin pompa, kelistrikan, pipa saluran rusak atau lepas jika dibiarkan akan menyebabkan air akan terbuang secara percuma, selain itu juga tidak bisa monitoring kerusakan pada komponen peralatan mesin. Untuk mempermudah pengontrolan pada mesin dan peralatan mesin, pipa penyaluran air dan kondisi tandon air perlu sistem yang otomatis radar pintar berbasis Arduino Uno R3 menggunakan model ESP8266 merupakan sebuah microcontroller yang bisa untuk mengintegrasikan pengontrolan ketinggian air di tandon, sensor kerusakan mesin, kelistrikan, perpipaan, pendeteksian kerusakan, kelebihan sistem ini dapat di kontrol berbasis Internet of Things atau IoT. Setelah dilakukan pengujian secara keseluruhan sistem dapat berfungsi dengan baik dan mudah untuk dipergunakan dengan biaya pembelian komponen relatif murah. Sehingga sistem radar pintar ini dapat bermanfaat untuk pengontrolan tandon air untuk warga di perumahan

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“…Cross-modal image registration is used to align the pixels of two or more images of the same scene generated by different sensors and describe them in a consistent coordinate system [1,2]. In object tracking, infrared and visible light are the most widely used in environmental perception, and are of great importance for many applications, such as medical imaging [3][4][5], remote sensing [6,7], panoramic vision [8][9][10], autonomous vehicles [11][12][13][14], and more. Visible light cameras are similar to the human visual system in that they have a wide range of perception, are affected by changes in light intensity, and lack night vision capabilities.…”

Section: Introductionmentioning

confidence: 99%

Cross-Modal Image Registration via Rasterized Parameter Prediction for Object Tracking

Zhang

Xiang

2023

Applied Sciences

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Object tracking requires heterogeneous images that are well registered in advance, with cross-modal image registration used to transform images of the same scene generated by different sensors into the same coordinate system. Infrared and visible light sensors are the most widely used in environmental perception; however, misaligned pixel coordinates in cross-modal images remain a challenge in practical applications of the object tracking task. Traditional feature-based approaches can only be applied in single-mode scenarios, and cannot be well extended to cross-modal scenarios. Recent deep learning technology employs neural networks with large parameter scales for prediction of feature points for image registration. However, supervised learning methods require numerous manually aligned images for model training, leading to the scalability and adaptivity problems. The Unsupervised Deep Homography Network (UDHN) applies Mean Absolute Error (MAE) metrics for cost function computation without labelled images; however, it is currently inapplicable for cross-modal image registration. In this paper, we propose aligning infrared and visible images using a rasterized parameter prediction algorithm with similarity measurement evaluation. Specifically, we use Cost Volume (CV) to predict registration parameters from coarse-grained to fine-grained layers with a raster constraint for multimodal feature fusion. In addition, motivated by the utilization of mutual information in contrastive learning, we apply a cross-modal similarity measurement algorithm for semi-supervised image registration. Our proposed method achieves state-of-the-art performance on the MS-COCO and FLIR datasets.

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Car Parking Distance Controller Using Ultrasonic Sensors Based On Arduino Uno

Cited by 21 publications

References 0 publications

Monitoring Pengunaan Daya 3 Phase Dengan Notifikasi Berbasis Telegram

Monitoring Pengunaan Daya 3 Phase Dengan Notifikasi Berbasis Telegram

Rancang bangun sistem radar pintar pengontrol pengisian air berbasis mikrokontroler

Cross-Modal Image Registration via Rasterized Parameter Prediction for Object Tracking

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