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Sedayu, Agung, Elvan Yuniarti, and Edi Sanjaya. "Rancang Bangun Home Automation Berbasis Raspberry Pi 3 Model B dengan Interface Aprlikasi Media Sosial Telegram sebagai Kendali." Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics 1, no. 2 (April 2, 2019): 42–47. http://dx.doi.org/10.15408/fiziya.v1i2.9254.
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Telah berkambangnya tekonologi home automation pada zaman ini dan salah satunya dengan pemanfaatan smartphone sebagai salah satu pengendalinya. Pada penelitian ini memanfaatkan sebuah aplikasi media sosial telegram dan sebuah single board computer sebagai kontrol pada sebuah home automation. Penelitian ini bertujuan untuk membangun sebuah home automation dengan menggunakan Raspberry Pi dan aplikasi media sosial telegram sebagai kendalinya. Dengan studi pustaka dan metode eksperimen penelitian ini berhasil merancang bangun sebuah home automation menggunakan Raspberry Pi 3 Model B dengan interface aplikasi telegram sebagai kendalinya. Dibutuhkan sebuah Bot API telegram agar Raspberry Pi dan aplikasi telegram dapat terhubung. Perangkat yang digunakan dalam penelitian ini meliputi: single board computer Raspberry Pi 3 Model B, 2 buah relay untuk 2 perangkat elektronik (lampu dan kipas), 1 buah MCB dan smartphone yang telah terinstall aplikasi telegram yang digunakan sebagai pengontrol perangkat elektronik. Hasil dari penelitian ini sudah sesuai dengan tujuannya yaitu merancang bangun sebuah home automation dengan menggunakan Raspberry Pi dan aplikasi media social telegram sebagai kendalinya mensimulasikannya pada peralatan elektronika.
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Wardana, I. Nyoman Kusuma, Julian W. Gardner, and Suhaib A. Fahmy. "Optimising Deep Learning at the Edge for Accurate Hourly Air Quality Prediction." Sensors 21, no. 4 (February 4, 2021): 1064. http://dx.doi.org/10.3390/s21041064.
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Accurate air quality monitoring requires processing of multi-dimensional, multi-location sensor data, which has previously been considered in centralised machine learning models. These are often unsuitable for resource-constrained edge devices. In this article, we address this challenge by: (1) designing a novel hybrid deep learning model for hourly PM2.5 pollutant prediction; (2) optimising the obtained model for edge devices; and (3) examining model performance running on the edge devices in terms of both accuracy and latency. The hybrid deep learning model in this work comprises a 1D Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) to predict hourly PM2.5 concentration. The results show that our proposed model outperforms other deep learning models, evaluated by calculating RMSE and MAE errors. The proposed model was optimised for edge devices, the Raspberry Pi 3 Model B+ (RPi3B+) and Raspberry Pi 4 Model B (RPi4B). This optimised model reduced file size to a quarter of the original, with further size reduction achieved by implementing different post-training quantisation. In total, 8272 hourly samples were continuously fed to the edge device, with the RPi4B executing the model twice as fast as the RPi3B+ in all quantisation modes. Full-integer quantisation produced the lowest execution time, with latencies of 2.19 s and 4.73 s for RPi4B and RPi3B+, respectively.
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Wiguna, Esa Hayyu, and Arkhan Subari. "RANCANG BANGUN SISTEM MONITORING KETINGGIAN AIR DAN KELEMBABAN TANAH PADA PENYIRAM TANAMAN OTOMATIS DENGAN HMI (HUMAN MACHINE INTERFACE) BERBASIS RASPBERRY PI MENGGUNAKAN SOFTWARE NODE-RED." Gema Teknologi 19, no. 3 (October 31, 2017): 1. http://dx.doi.org/10.14710/gt.v19i3.21878.
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Esa Hayyu Wiguna, Arkhan Subari, in this paper explain that the monitoring system is a system used to monitor and control work processes in a plant design. This system is widely used and applied in the industrial world to find out the performance of a plant. To do the monitoring system, a lot of software can be used, which is then called the HMI (Human Machine Interface). The monitoring system with an interface in the form of HMI can be presented in various forms, such as buttons, or can also be displayed in the visualization of the plant while working. This monitoring system through an HMI interface uses supporting hardware in the form of a Raspberry Pi as a device to process the data that will be displayed on the display screen, while displaying its visualization uses an LCD touch screen. This LCD touch screen is connected to the Raspberry Pi via the LCD driver. The graphic form that will be displayed on the LCD touch screen is designed using Node-RED software. The visualization that will be displayed on the Touch Screen LCD will be adjusted to the working system of automatic plant sprinklers. This monitoring system using an HMI interface can display the plant's working system through indicators of water level and soil moisture. To test tube 2 water level measured through ultrasonic sensors through HMI has an error ratio of 1.01%, while for soil moisture measured through soil moisture sensors has an error ratio of 1.51%. Keywords: Monitoring System, Human Machine Interface (HMI), Raspberry Pi, Node-RED. ReferencesHaryanto, Heri dan Sarif Hidayat. 2012. Perancangan HMI (Human Machine Interface) Untuk Pengendalian Kecepatan Motor DC. Jurnal S1 Jurusan Elektro Fakultas Teknik Terpublikasi. Banten: Universitas Sultan Ageng Tirtayasa.Udayana, Gede Agus, I Gede Mahendra Darmawiguna, dan I Made Gede Sumarya. 2016. Pengembangan Prototipe Portal Otomatis Dengan Pendeteksian Plat Nomor Kendaraan Berbasis Raspberry Pi. Artikel Jurusan Pendidikan Teknik Informatika Terpublikasi. Bali: Universitas Pendidikan Ganesha.Man, Joseph. 2016. Raspberry Pi 3 Model B Technical Specifications. https://www.element14.com/community/docs/DOC-80899/l/raspberry-pi-3-model-b-technical-specifications. Diakses tanggal 14 Agustus 2017.Kurniawan, Halim. 2005. Aplikasi Penjawab Pesan Singkat Automatis dengan Bahasa Python. Makalah Seminar Tugas Akhir S1 Jurusan Teknik Elektro Terpublikasi. Semarang: Universitas Diponegoro.Node-RED. 2013. Node-RED; Flow-based programming for the Internet of Things. https://nodered.org/. Diakses tanggal 02 Mei 2017.Tim J, M. 2016. Developing with Node-RED. https://software.intel.com/en-us/articles/developing-with-node-red. Diakses tanggal 02 Mei 2017.
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Utami, Pipit, Abdul Aziz Sidiq Tri Putra, Djoko Santoso, Nuryake Fajaryati, Bonita Destiana, and Mohd Erfy Ismail. "VIDEO MOVING SURVEILLANCE YANG TERINTEGRASI YOUTUBE MENGGUNAKAN RASPBERRY PI 3." Elinvo (Electronics, Informatics, and Vocational Education) 3, no. 1 (August 14, 2018): 113–23. http://dx.doi.org/10.21831/elinvo.v3i1.20797.
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Static CCTV facilities in class need to be optimized in classroom learning, especially in recording learning activities as implementation of learning in the 21st century and strategic steps to face the Industrial Revolution 4.0. Educators need to play a role in utilizing CCTV in learning. This article presents the development of YouTube Integrated Video Moving Surveillance devices using Raspberry Pi 3. The development stages consist of analysis, design, development and evaluation. The analysis shows that: (1) the limitations of CCTV motion are followed up with the addition of motorcycles; (2) limited access to video recording data is followed up by sending in real time using YouTube; and (3) controlling the system performance of the device using Raspberry Pi 3 model B. The evaluation results show that all electronic measurement parameters are in accordance with the success target and the functional test shows that the device can function to record classroom learning activities that can be monitored in real time via YouTube with good quality (average delay is 22,89s). The results of the development of this device are expected to be an alternative use of technology in learning, especially in the supervision and assessment of student learning activities.
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Suchendra, Devie Ryana, Dewi Putri Suryani, and Muhammad Ikhsan Sani. "Home Lighting Control Based on Time Scheduling using Crontab." IJAIT (International Journal of Applied Information Technology) 2, no. 01 (May 25, 2018): 1. http://dx.doi.org/10.25124/ijait.v2i01.924.
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Access control system in smart home concept is a support system that affects especially on controlling the electronic devices. Along with advances in technology, the conventional access control system was developed into an electronic-based access control system. A conventional access control system such as manual electric switches is now beginning to be developed with an electric switch that can be controlled wirelessly from the web. Raspberry pi 2 model B is one of the minicomputers which can be used in an automatic access control system. By using GPIO (General Purpose Input Output) on Raspberry Pi, can be created by a wireless access control system, safe and effective. The purpose of this study is designing a prototype relay control system wirelessly model that can be accessed through the web, the result indicates the possibility of relay control to be remote. Crontab scheduling functions on the controller's relay are used, then the device can function based on a predetermined schedule, it is very helpful to turn on and off electrical devices home remotely. The form of a username and password authentication will be used to protect the system from being accessed by anyone. In the final phase of research, the system is evaluated at day and night using Crontab function. Meanwhile, the response time of the relay is within 1-2 seconds range.
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Delgado-Reyes, Gustavo, Pedro Guevara-Lopez, Igor Loboda, Leobardo Hernandez-Gonzalez, Jazmin Ramirez-Hernandez, Jorge-Salvador Valdez-Martinez, and Asdrubal Lopez-Chau. "State Vector Identification of Hybrid Model of a Gas Turbine by Real-Time Kalman Filter." Mathematics 8, no. 5 (April 27, 2020): 659. http://dx.doi.org/10.3390/math8050659.
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A model and real-time simulation of a gas turbine engine (GTE) by real-time tasks (RTT) is presented. A Kalman filter is applied to perform the state vector identification of the GTE model. The obtained algorithms are recursive and multivariable; for this reason, ANSI C libraries have been developed for (a) use of matrices and vectors, (b) dynamic memory management, (c) simulation of state-space systems, (d) approximation of systems using equations in matrix finite difference, (e) computing the mean square errors vector, and (f) state vector identification of dynamic systems through digital Kalman filter. Simulations were performed in a Single Board Computer (SBC) Raspberry Pi 2® with a real-time operating system. Execution times have been measured to justify the real-time simulation. To validate the results, multiple time plots are analyzed to verify the quality and convergence time of the mean square error obtained.
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Sowah, Robert A., Dale E. Boahene, Dalton C. Owoh, Rexford Addo, Godfrey A. Mills, Wiafe Owusu-Banahene, Gifty Buah, and Baffour Sarkodie-Mensah. "Design of a Secure Wireless Home Automation System with an Open Home Automation Bus (OpenHAB 2) Framework." Journal of Sensors 2020 (October 30, 2020): 1–22. http://dx.doi.org/10.1155/2020/8868602.
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There is rapid interest growing in the use of smart, connected devices. The developing world market for smart technology is evolving to adopt and adapt to the interconnected world of devices leading to the Internet of Things (IoT) everywhere. This research paper presents the design, development, and deployment of a prototype for the secure wireless home automation system with OpenHAB 2. We employed the use of two (2) high-performance microcontrollers, namely, the Arduino Mega 2560, interfaced with a 16-channel relay, and Raspberry Pi Model B, running the OpenHAB software. The Raspberry Pi functioned as the server to develop a prototype of an automated smart home that is remotely controllable from both a web application and an Android mobile app. In designing a wireless controlled switch for home appliances, two security procedures were implemented, namely, the token-based JSON Web Token (JWT) interface and Advanced Encryption Standard (AES) procedures for authentication and data encryption. Our system delivered a home automation system that leverages on the power of the latest version of OpenHAB to maximize productivity and overall home security while making it adaptable to the management of individual devices. When tested, both the developed hardware and software modules performed extremely well to meet the goal of a secured home automation system. Industry-standard penetration testing tools and frameworks, including Aircrack-ng, were utilized; wireless network audit began with a full sweep of the wireless frequencies with excellent results. It also ensures the efficient use of energy in the home as devices are intelligently controlled from both mobile and web applications. The results of the design and implementation of the additional layer for the security of the OpenHAB framework provide various theoretical and practical implications for home automation.
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Wu, Yu Tzu, Matheus K. Gomes, Willian HA da Silva, Pedro M. Lazari, and Eric Fujiwara. "Integrated Optical Fiber Force Myography Sensor as Pervasive Predictor of Hand Postures." Biomedical Engineering and Computational Biology 11 (January 2020): 117959722091282. http://dx.doi.org/10.1177/1179597220912825.
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Force myography (FMG) is an appealing alternative to traditional electromyography in biomedical applications, mainly due to its simpler signal pattern and immunity to electrical interference. Most FMG sensors, however, send data to a computer for further processing, which reduces the user mobility and, thus, the chances for practical application. In this sense, this work proposes to remodel a typical optical fiber FMG sensor with smaller portable components. Moreover, all data acquisition and processing routines were migrated to a Raspberry Pi 3 Model B microprocessor, ensuring the comfort of use and portability. The sensor was successfully demonstrated for 2 input channels and 9 postures classification with an average precision and accuracy of ~99.5% and ~99.8%, respectively, using a feedforward artificial neural network of 2 hidden layers and a competitive output layer.
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Santise, M., K. Thoeni, R. Roncella, S. W. Sloan, and A. Giacomini. "PRELIMINARY TESTS OF A NEW LOW-COST PHOTOGRAMMETRIC SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W8 (November 14, 2017): 229–36. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w8-229-2017.
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This paper presents preliminary tests of a new low-cost photogrammetric system for 4D modelling of large scale areas for civil engineering applications. The system consists of five stand-alone units. Each of the units is composed of a Raspberry Pi 2 Model B (RPi2B) single board computer connected to a PiCamera Module V2 (8 MP) and is powered by a 10 W solar panel. The acquisition of the images is performed automatically using Python scripts and the OpenCV library. Images are recorded at different times during the day and automatically uploaded onto a FTP server from where they can be accessed for processing. Preliminary tests and outcomes of the system are discussed in detail. The focus is on the performance assessment of the low-cost sensor and the quality evaluation of the digital surface models generated by the low-cost photogrammetric systems in the field under real test conditions. Two different test cases were set up in order to calibrate the low-cost photogrammetric system and to assess its performance. First comparisons with a TLS model show a good agreement.
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Villaseñor-Aguilar, Marcos J., J. Enrique Botello-Álvarez, F. Javier Pérez-Pinal, Miroslava Cano-Lara, M. Fabiola León-Galván, Micael-G. Bravo-Sánchez, and Alejandro I. Barranco-Gutierrez. "Fuzzy Classification of the Maturity of the Tomato Using a Vision System." Journal of Sensors 2019 (July 4, 2019): 1–12. http://dx.doi.org/10.1155/2019/3175848.
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Artificial vision systems (AVS) have become very important in precision agriculture applied to produce high-quality and low-cost foods with high functional characteristics generated through environmental care practices. This article reported the design and implementation of a new fuzzy classification architecture based on the RGB color model with descriptors. Three inputs were used that are associated with the average value of the color components of four views of the tomato; the number of triangular membership functions associated with the components R and B were three and four for the case of component G. The amount of tomato samples used in training were forty and twenty for testing; the training was done using the Matlab© ANFISEDIT. The tomato samples were divided into six categories according to the US Department of Agriculture (USDA). This study focused on optimizing the descriptors of the color space to achieve high precision in the prediction results of the final classification task with an error of 536,995×10-6. The Computer Vision System (CVS) is integrated by an image isolation system with lighting; the image capture system uses a Raspberry Pi 3 and Camera Module Raspberry Pi 2 at a fixed distance and a black background. In the implementation of the CVS, three different color description methods for tomato classification were analyzed and their respective diffuse systems were also designed, two of them using the descriptors described in the literature.
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Eridani, Dania, Eko Didik Widianto, and Nur Kholid. "Rancang Bangun Sistem Monitoring Dan Controlling Tambak Udang Windu Dengan Konsep Internet Of Things Menggunakan Protokol Message Queuing Telemetry Transport." CESS (Journal of Computer Engineering, System and Science) 5, no. 1 (January 31, 2020): 137. http://dx.doi.org/10.24114/cess.v5i1.14718.
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Udang windu merupakan salah satu jenis udang asli dari Indonesia. Pembudidayaan udang windu sangat dipengaruhi oleh kualitas air pada tambak udang windu. Berdasarkan faktor tersebut, maka dibuatlah sistem yang mampu memantau dan mengontrol kualitas air pada tambak udang windu secara kontinyu dan real-time menggunakan konsep Internet of Things dengan protokol Message Queuing Telemetry Transport. Sistem yang dibangun terdiri dari 2 bagian, yang pertama adalah NodeMCU sebagai primary node yang terhubung dengan sensor (HC-SR04, SEN0161, dan DS18B20) untuk pemantauan kualitas air dan aktuator (motor DC sebagai kincir air). Bagian kedua adalah Raspberry Pi 3 Model B sebagai MQTT broker dan berfungsi untuk mengirimkan hasil pembacaan sensor menuju database. Hasil dari penelitian ini adalah sistem dapat memantau kualitas air dan juga melakukan kontrol terhadap kincir air melalui aplikasi berbasis website. Primary node juga bisa berkomunikasi dengan broker melalui protokol MQTT.
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Suryatini, Fitria, Maimunah Maimunah, and Fachri Ilman Fauzandi. "Implementasi Sistem Kontrol Irigasi Tetes Menggunakan Konsep IoT Berbasis Logika Fuzzy Takagi-Sugeno." JTERA (Jurnal Teknologi Rekayasa) 4, no. 1 (June 19, 2019): 115. http://dx.doi.org/10.31544/jtera.v4.i1.2019.115-124.
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Irigasi merupakan faktor penting dalam proses budidaya tanaman. Oleh karena itu, dibutuhkan upaya pengelolaan air secara tepat khususnya dalam irigasi. Salah satu metode irigasi yang banyak digunakan adalah irigasi tetes. Penelitian ini bertujuan untuk merancang sistem kontrol irigasi tetes berdasarkan kondisi suhu dan kelembapan tanah menggunakan kendali logika fuzzy Takagi-Sugeno yang diimplementasikan menggunakan konsep Internet of Things (IoT). Perangkat keras yang digunakan adalah Raspberry Pi 3 model B sebagai pusat kendali, sensor suhu DS18B20, dan sensor kelembapan tanah SKU:SEN0193. Keluaran kendali fuzzy menentukan durasi penyalaan solenoid valve untuk mengairi tanaman. Sumber air irigasi berasal dari tangki yang dapat terisi secara otomatis menggunakan motor pompa dan sensor ultrasonik HCSR04 sebagai pendeteksi level air. Aplikasi Android digunaka untuk kendali jarak jauh dan monitoring parameter yang dikirim secara realtime melalui database online Firebase. Hasil penelitian menunjukkan bahwa sistem dapat menjaga kelembapan tanah pada kelembapan rata-rata sebesar 98,4% dengan durasi penyiraman rata-rata sebesar 453,6 detik. Rata-rata volume air yang terpakai pada proses penyiraman sebanyak 10,9 liter. Selain itu, sistem dapat melakukan proses monitoring dan pengontrolan jarak jauh dengan delay rata-rata 2 detik.
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Yen, Chih-Ta, Sheng-Nan Chang, and Cheng-Yang Cai. "Development of a Continuous Blood Pressure Measurement and Cardiovascular Multi-Indicator Platform for Asian Populations by Using a Back Propagation Neural Network and Dual Photoplethysmography Sensor Signal Acquisition Technology." Journal of Nanomaterials 2021 (May 29, 2021): 1–15. http://dx.doi.org/10.1155/2021/6613817.
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This study proposed a measurement platform for continuous blood pressure estimation based on dual photoplethysmography (PPG) sensors and a back propagation neural network (BPNN) that can be used for continuous and rapid measurement of blood pressure and analysis of cardiovascular-related indicators. The proposed platform measured the signal changes in PPG and converted them into physiological indicators, such as pulse transit time (PTT), pulse wave velocity (PWV), perfusion index (PI), heart rate (HR), and pulse wave analysis (PWA); these indicators were then fed into the BPNN to calculate blood pressure. The hardware of the experiment comprised 2 PPG components (i.e., Raspberry Pi 3 Model B and analog-to-digital converter [MCP3008]), which were connected using a serial peripheral interface. The BPNN algorithm converted the stable dual PPG signals acquired from the strictly standardized experimental process into various physiological indicators as input parameters and finally obtained the systolic blood pressure (SBP) and diastolic blood pressure (DBP). To increase the robustness of the BPNN model, this study input data of 100 Asian participants into the training database, including those with and without cardiovascular disease, each with a proportion of approximately 50%. The experimental results revealed that the mean and standard deviation of SBP were 2.23 ± 2.24 mmHg , with a mean squared error of 3.15 mmHg. The mean and standard deviation of DBP was 3.5 ± 3.53 mmHg , with a mean squared error of 4.96 mmHg. The proposed real-time blood pressure measurement system exhibited a mean accuracy of 98.22% and 95.58% for SBP and DBP, respectively.
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Syukur, Arba Abdul. "Implementasi Webcam sebagai Pendeteksi Wajah pada Sistem Keamanan Perumahan menggunakan Image Processing." ELECTRICES 2, no. 1 (May 22, 2020): 1–5. http://dx.doi.org/10.32722/ees.v2i1.2791.
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Pencurian yang sangat meresahkan masyarakat seringkali terjadi pada suatu ruangan atau lingkungan seperti gedung, kantor, lorong bahkan tempat ibadah juga menjadi sasaran para pencuri. Upaya yang dilakukan DKM (Dewan Kemakmuran Masjid) yaitu memberikan himbauan supaya tetap menjaga barang pentingnya masing-masing. Masjid seharusnya menjadi tempat yang aman dan nyaman untuk dikunjungi. Oleh karena itu kami memiliki ide yang bertujuan untuk mengantisipasi pencurian di masjid atau tempattempat yang rawan pencurian. Penelitian ini merancangbangun sistem pengenalan wajah sebagai solusi untuk mengurangi tingkat pencurian. Sistem ini dilengkapi dengan perangkat keras Raspberry Pi 3 model B dan webcam A4Tech. Perangkat lunak database yang dapat menyimpan data pengguna. Tujuan penelitian untuk membandingkan 2 metode yang terbaik dalam pengenalan wajah yaitu metode LBPH (Local Binary Pattern Histogram) dan metode Eigenface. Penelitian dilakukan pada siang hari untuk mengambil citra wajah yang berbeda. Penelitian dilakukan dengan 3 kondisi yaitu siang hari luar ruangan, siang hari dalam ruangan dan malam hari dalam ruangan. Parameter yang digunakan untuk melihat hasil dari pengenalan wajah yaitu Akurasi, FAR (False Accept Rate) dan FRR (False Reject Rate). Hasil pengujian 2 metode tersebut yang memiliki tingkat rata-rata Akurasi tertinggi dan tingkat rata-rata FAR dan FRR terendah adalah metode Eigenface. Kesimpulan dari hasil penelitian yaitu pencahayaan mempengaruhi pengenalan wajah dalam 2 metode tersebut.
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Jung, Sunghun. "Development and Verification of Hybrid Power Controller Using Indoor HIL Test for the Solar UAV." Energies 13, no. 8 (April 24, 2020): 2110. http://dx.doi.org/10.3390/en13082110.
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A hybrid power system (HPS) is developed for the photovoltaic (PV) powered and tethered multirotor unmanned aerial vehicle (UAV) based on the robot operating system (ROS) and verified using an indoor hardware-in-the-loop (HIL) test. All the processes, including a UAV flight mode change (i.e., takeoff, hovering, and landing) and power flow control (consisting of PV modules, a LiPo battery pack, and a UAV) are completely automated using a combination of Pixhawk 2.1 and the Raspberry Pi 3 Model B (RPi 3B). Once the indoor HIL test starts, (1) the UAV takes off and hovers with a preassigned 10 m altitude at a fixed point and keeps hovering until the voltage drops below 13.4 V ; (2) the UAV lands when the voltage drops below 13.4 V, and the hybrid power controller (HPC) starts to charge the LiPo battery pack using the energy from PV modules; and (3) the UAV takes off when the voltage of the battery pack becomes more than 16.8 V, and the procedure repeats from (1). A PV-powered and tethered multirotor UAV using the proposed HPS can fly more safely for a longer time, particularly in an urban area, and so it is competitive to the traditional multirotor type UAV in the sense of both the flight time and the surveillance mission performance.
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Endang Supriyadi, Maya Sofiana, and Surya Dwipangga. "Sistem Kendali Lampu Defect Dan Reject Berbasis Web Server Menggunakan Raspberrry Pi 3 Model B." Jurnal Teknik Informatika 7, no. 1 (February 2, 2021): 09–15. http://dx.doi.org/10.51998/jti.v7i1.346.
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Abstract— This research covers the design and construction of a Web-based Defect & Reject Light Control Intelligent System with Raspberry Pi with the aim of detecting the quality conditions of manufactured goods at the final inspection section of PT. Suryaraya Rubberindo Industries. This system requires several components such as a Raspberry Pi 3 Microcontroller, Relays, mini filament LED lamps and several other supporting components. The design and construction of a Web-Based Defect & Reject Light Control Intelligent System with the Raspberry Pi comes from experimental results, besides that it is also supported by several literary documents found in journals and reference books. This Intelligent Web-Based Defect & Reject Light Control System with the Raspberry Pi uses a website design as an input to turn off or turn on a lamp. Two mini filament lamps are used as output components that are made like Signal lamps. Based on the results of the experiments conducted, the Web-Based Defect & Reject Light Control Intelligent System with the Raspberry Pi can work quite well. When this system detects the condition of the production goods in a state that does not meet the specified company standards but has a low level of seriousness (defect), the system will give a signal for a yellow light with a value of 1, whereas if the level of seriousness is high (reject) then the control system will give a signal to turn on the red light the value of the number 1 stored in the database
Intisari— Penelitian ini meliputi racang dan bangun Sistem Cerdas Kendali Lampu Defect & Reject Berbasis Web denganRaspberry Pi dengan tujuan untuk mendeteksi kondisi kualitas barang produksi pada bagian final Inspection di PT. SuryarayaRubberindo Industries. Sistem ini memerlukan beberapa komponen seperti Mikrokontroller Raspberry Pi 3, Relay,Lampu berjenis LED filamen mini dan beberapa komponen pendukung lainnya. Rancang Rangun Sistem Cerdas KendaliLampu Defect & Reject Berbasis Web dengan Raspberry Pi tersebut berasal dari hasil percobaan, selain itu didukung pulaoleh beberapa literatur dokumen yang terdapat pada jurnal dan buku referensi. Sistem Cerdas Kendali Lampu Defect & RejectBerbasis Web dengan Raspberry Pi ini menggunakan rancangan website sebagai input untuk mematikan atau menyalakan sebuah lampu. Dua buah lampu filamen mini digunakan sebagai komponen output yang dibuat seperti lampu Signal.Berdasarkan hasil percobaan yang dilakukan, Sistem Cerdas ini dapat bekerja dengan cukup baik. Ketika sistem ini mendeteksikondisi barang produksi dalam keadaan tidak memenuhi standard perusahaan yang telah ditentukan akan tetapi memilikitingkat keseriusan rendah (defect) maka sistem akan memberikan sinyal untuk lampu kuning bernilai angka 1 sedangkan jika tingkat keseriusan tinggi (reject) maka sistem kendali akan memberikan sinyal untuk menyalakan lampu merah bernilai angka 1 yang tersimpan pada database.
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Nurcahyana, Mohamad Lukman. "Dual Channel TV and Fans Controllers Based on Android Smartphones." Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan 3, no. 2 (July 22, 2019): 52–61. http://dx.doi.org/10.34010/telekontran.v3i2.1883.
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Abstract - This research will focus on the design of dual channel television control systems and fan speed control. The design of a dual channel TV controller system and fan speed control uses wireless media as a link between an Android smart phone, Raspberry Pi B +, TV, and fan. To design a dual channel TV controller system and control wind kipsa, it includes an Android smartphone, wi-fi module type TL-WN832N TP-Link and Raspberry pi B +. Android smartphones function as TV controllers and fans with applications installed on Android smartphones. The TP-Link TL-WN832N wi-fi module functions as a wireless multimedia link between the Raspberry Pi B + and Android smartphones. Raspberry pi B + functions like processing data sent by an Android smartphone to control the TV or fan. Thus, the system design tool can replace 2 controllers and TV fans in one device that can control the TV and fan using an Android smartphone
Keyword : Android smartphone, TP-Link TL-WN832N Wi-Fi module, Raspberry Pi B +
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Dhakate, Prajwal. "NFC based Smart Attendance System using Raspberry Pi 3 Model B+." International Journal for Research in Applied Science and Engineering Technology 8, no. 5 (May 31, 2020): 1830–35. http://dx.doi.org/10.22214/ijraset.2020.5293.
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Sałuch, Mateusz, Daniel Tokarski, Tomasz Grudniewski, Marta Chodyka, JerzyAntoni Nitychoruk, Paweł Woliński, Beata Jaworska, and Grzegorz Adamczewski. "Raspberry PI 3B + microcomputer as a central control unit in intelligent building automation management systems." MATEC Web of Conferences 196 (2018): 04032. http://dx.doi.org/10.1051/matecconf/201819604032.
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This article aims to show the possible savings in electricity costs in smart building installations with the use of new version of Raspberry Pi 3 model B + as the control unit in intelligent building automation systems. It presents a comparison of the consumption of electricity in two units used in the central control systems, i.e. a small Windows-based computer and a Raspberry microcomputer. The power consumption of these units was measured during the rest period and during standard operations in the intelligent installation system. The conducted measurements proved that the use of the new updated version of Raspberry Pi 3 model B + as the central control unit in intelligent building management systems is more economical and energy-saving.
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Sudarsono, Joshua Fernaldy, Gede Sukadarmika, and Linawati Linawati. "Rancang Bangun Alat Ukur Kualitas Jaringan Berbasis Raspberry Pi 3 Model B." Majalah Ilmiah Teknologi Elektro 20, no. 1 (March 1, 2021): 53. http://dx.doi.org/10.24843/mite.2021.v20i01.p06.
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Internet telah menjadi kebutuhan bagi masyarakat modern dalam melakukan berbagai aktifitasnya saat ini. Pengguna Internet yang meningkat sangat pesat di setiap tahun menunjukkan bahwa kebutuhan masyarakat terhadap Internet yang semakin tinggi. Di Indonesia pertumbuhan pengguna Internet diprediksi meningkat 10,2 persen setiap tahunnya dari tahun 2018 hingga 2023. Namun demikian, pertumbuhan jumlah pelanggan sering kali tidak diikuti dengan kemampuan provider Internet untuk meningkatkan fasilitas maintanance dan untuk menjaga kualitas layanan kepada pelanggannya. Salah satu penyebabnya adalah keterbatasan perangkat yang sering kali menjadi kendala bagi teknisi untuk mealakukan maintenance sesegera mungkin. Penelitian ini bertujuan untuk dapat merancang dan membangun perangkat yang dapat digunakan sebagai alat ukur kualitas jaringan yang lebih sederhana dan ekonomis sehingga mendukung mobilitas teknisi untuk membagun maupun maintenance jaringannya. Perangkat yang dibangun pada penelitian ini berbasis Raspberry Pi 3 Model B. Perbandingan hasil pengukuran performa perangkat antara lain daya tahan baterai, ping, upload dan download rate antara perangkat yang dibangun dengan penggunaan laptop memberikan hasil yang hampir sama. Peangkat yang dibangun ini memiliki keunggulan pada sisi dimensi yang lebih kecil dan ringan serta biaya yang jauh lebih ekonomis.
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Kumar, G. Pavan. "Face Mask Detection with Raspberry Pi." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 3451–58. http://dx.doi.org/10.22214/ijraset.2021.35778.
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In the wake of the COVID-19 epidemic, institutions such as the academy are suffering the most from global closure if the current situation haven’t rectified. COVID-19 also known as Serious Acute Respiratory Syndrome Corona virus-2 is an infectious disease that is transmitted to an infected person who talks, sneezes or coughs through respiratory droplets. This spreads quickly through close contact with anyone with the disease, or by touching objects or the infected area. By wearing a face mask under the jaws covering at crowded places or by frequently hygiene at your palms and by using at the minimum of 70% sanitizers which are based on alcohol is the best method for the against of the COVID-19. In this project we have used it ML, OpenCV and TensorFlow face recognition. This the model can be used for security purposes because of course an app that works well for use. In this way MobilenetV2 using a BN-based layout too lightweight and embedded this model with Raspberry pi to make real-time mask discovery, when, SSD (Single Shot Detector) format is used and the spinal network is light. As technology advances, Deep Learning has demonstrated its effectiveness in recognition and classification through image processing. The study uses in-depth reading techniques to distinguish facial recognition and to determine whether a person is wearing a facemask or not. The collected data contains 25,000 images using 224x224 pixel resolution and obtained 96% accuracy with the performance of a trained model. The system enhances the Raspberry Pi-based real-time recognition made by alarms and takes a facial image when the person found is not wearing a facemask. This study is beneficial in combating the spread of the virus and in avoiding contact with it.
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Duda, Liubomyr. "Developing of the method for optimizing the performance of architecture-independent hardware platforms." Technology audit and production reserves 3, no. 1(59) (June 30, 2021): 45–49. http://dx.doi.org/10.15587/2706-5448.2021.233947.
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The object of research is the Raspberry Pi single-board computer. The work examines the optimization of architecture-independent hardware platforms using its example. The research is based on an integrated scientific approach based on a system-analytical, structural-functional, empirical and typological approach. It is emphasized that the entire Raspberry Pi line uses APM-architecture processors. The genesis of Raspberry Pi is given, the parameters of the last build are determined. It is noted that the latest version is dated November 2020. It is equipped with wireless WiFi and Bluetooth modules (2×USB 3.0 and 1×USB 2.0 ports type A, 5.0, BLE), which expand the boundaries of mini-PC application in the field of Ethernet technologies and has a frequency of 1.8 GHz. The appearance of one of the popular Raspberry Pi B+boards has been formed, with the separation of the main blocks. The basic principles of improving the performance of the Raspberry Pi single board computer are determined, each of which is based on a specific mechanism. The first is the addition of ZRAM as a compressed random access memory block device. The principle of ZRAM operation is described, the mechanism for activating ZRAM on the Raspberry Pi is given. To improve the performance of the Raspberry Pi single board computer, the use of an NVMe disk is justified. It is emphasized that the NVMe disk is reliable and has a high data transfer rate. Connecting it to the Raspberry Pi single board computer is the optimal solution to improve performance. The tuning sequence is presented, the numerical result of the NVMe disk operation based on the Raspberry Pi single-board computer is proposed. It is proposed, as a principle to improve performance, the installation of an ICE Tower CPU based on Raspberry Pi. It is noted that the ICE Tower CPU is a cooling system that is designed to cool the Raspberry Pi. The principles of tuning ICE Tower CPU and the result of fluctuations in temperature components using the rpi-monitor are described. As part of the study, performance improvements were obtained from 26 % to 34 %, which is mainly in line with the expected theoretical improvement of 34 %.
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Yenni, Helda, and M. Ari Ardianto. "ALAT DIGITAL PENCETAK KUE BAWANG MENGGUNAKAN RASPBERRY PI 3 MODEL B BERBASIS ANDROID." JTT (Jurnal Teknologi Terapan) 6, no. 1 (April 30, 2020): 93. http://dx.doi.org/10.31884/jtt.v6i1.246.
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Kue bawang merupakan salah satu makanan ringan tradisional di Indonesia. Makanan berbahan dasar tepung terigu dan tapioka ini bercita rasa gurih dan garing. Saat ini, kue bawang sudah merambah bisnis kuliner. Peralatan utama dalam pembuatan kue ini disebut ampia. Ampia yang digunakan masih berupa perangkat manual dalam operasionalnya termasuk mengatur ketebalan adonan setelah digiling. Kendala yang dihadapi berupa keterbatasan tenaga manusia untuk menggerakkan alat dan keterbatasan ketelitian untuk mendapatkan ukuran ketebalan yang presisi sesuai dengan yang diinginkan. Pada industri skala besar, hal tersebut dapat berpengaruh pada produktifitas. Solusi dari permasalahan tersebut berupa penerapan teknologi pada industri kuliner dengan membuat alat digital pencetak kue bawang secara otomatis. Kontrol utama adalah Raspberry pi 3, aplikasi smartphone android untuk menjalankan dan mematikan mesin pencetak kue bawang secara otomatis. Sensor ultrasonik digunakan untuk mendeteksi adonan, alat ini dilengkapi dengan motor penggerak yaitu yang digunakan untuk menggiling, mencetak serta memotong adonan kue dan motor servo untuk mengatur ketebalan adonan. Sensor Rotary Encoder ky-040 yang berfungsi sebagai pengatur panjang pemotongan adonan kue bawang. Pada penelitian ini sistem yang dirancang mampu menghasilkan sistem kontrol menggunakan aplikasi smartphone Android, sehingga dapat menghemat tenaga dan waktu dalam proses pembuatan kue bawang serta ukuran dapat diatur sesuai dengan yang diinginkan. Kata Kunci: kue bawang, Raspberry Pi 3, otomatis, Android
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Ludony, Stephanie Graciela, Melisa Mulyadi, and Kumala Indriati. "Rancang Bangun Purwarupa Lengan Robot Berbantuan Raspberry Pi." Jurnal Elektro 13, no. 2 (February 17, 2021): 115–24. http://dx.doi.org/10.25170/jurnalelektro.v13i2.1979.
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Persaingan di bidang industri telah mendorong untuk dilakukannya proses otomasi dalam mengoperasikan peralatan mesin-mesin industri dan kontrol proses untuk menggantikan operator tenaga manusia. Teknologi robot merupakan bagian dari otomasi yang banyak diterapkan di industri, salah satunya adalah lengan robot. Pada proses produksi, lengan robot digunakan untuk memindahkan objek. Dibutuhkan perancangan yang benar agar lengan robot dapat bergerak sesuai dengan kriteria yang diinginkan. Oleh karena itu pada penelitian ini dilakukan perancangan dan pembuatan purwarupa lengan robot yang memiliki lima derajat kebebasan atau Degree of Freedom (DoF) dan dilengkapi dengan pencapit objek. Sebagai pengendali lengan robot digunakan mikrokomputer Raspberry Pi 3 Model B+ yang diprogram dengan perangkat lunak python. Pada lengan robot terdapat kamera untuk mendeteksi warna objek agar lengan robot dapat memindahkan dan menempatkan objek sesuai kelompok warnanya. Pengujian terhadap rancangan lengan robot menunjukkan bahwa kamera dapat mengenali warna objek dan lengan dapat memindahkan objek sesuai pada tempatnya.
Competition in the industrial sector has pushed for automation processes in operating industrial machine tools and process control to replace human labor operators. Robot technology is a part of automation that is widely applied in industry, one of which is the robot arm. In the production process, robotic arms are used to move goods. Correct design is needed so that the robot arm can move according to the desired criteria. Therefore, in this study, the design and manufacture of a robot arm prototype that has five degrees of freedom (DoF) is carried out and is equipped with a clamp. As a controller for the robot arm, a Raspberry Pi 3 Model B + microcomputer is used, which is programmed with python software. On the robot arm, there is a camera to detect the color of the object so that the robot arm can move and place object according to the color group. Testing of the robot arm design shows that the camera can recognize the color of goods and the robot arm can move object according to their place.
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Agustian, Indra, Faisal Hadi, and M. Khairul Amri Rosa. "Pre-Diagnosis Gangguan Ginjal Melalui Citra Iris Mata Menggunakan Raspberry PI Dengan Metode Convolutional Neural Network (CNN)." JURNAL AMPLIFIER : JURNAL ILMIAH BIDANG TEKNIK ELEKTRO DAN KOMPUTER 9, no. 1 (May 30, 2019): 16–25. http://dx.doi.org/10.33369/jamplifier.v9i1.15396.
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ABSTRAKPenelitian ini melakukan perancangan aplikasi pengenalan gangguan ginjal dini melalui citra digital iris mata menggunakan metode convolutional neural network (CNN) dengan antarmuka Raspberry Pi 3 model B+. Hasil akurasi terbaik yang diperoleh dengan memvariasikan banyak epoch, nilai learning rate, ukuran kernel, komposisi database, dan fungsi pooling layer adalah 94% pada saat epoch 12, 92% pada nilai 0,0001, 95% pada ukuran 3x3, 95% pada komposisi 100 train dan 50 validation, 90% menggunakan fungsi max pooling. Kata kunci: gangguan ginjal, iridology, convolutional neural network, raspberry pi.
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Juanda, Enjang Akhmad, Nurul Wahidah, M. Khairudin, and Z. Mohamed. "Implementation of a Raspberry Pi Trainer for the Subject of Microprocessors and Microcontrollers in Vocational High Schools." Jurnal Pendidikan Teknologi dan Kejuruan 24, no. 1 (April 17, 2018): 147–54. http://dx.doi.org/10.21831/jptk.v24i1.18428.
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A Raspberry Pi Trainer is a tool which is able to support and facilitate the learning process of the subject of microprocessors and microcontrollers. The objective of this study was to find out the process and the results of the implementation of a Raspberry Pi Trainer for the subject of microprocessors and microcontrollers in the expertise program of industrial electronics in vocational high schools. This study used a qualitative method. The descriptive data were resulted from the observed students’ behavior in the form of the research informants’ activities covering the domains of cognitive, psychomotor, and affective. There were 20 informants divided into two classes, 10 in class XII A and 10 in class XII B. Each class consisted of 2 males and 8 females. The results showed the Raspberry Pi Trainer was well applied in practical learning activities. The average abilities of class XII B and class XII A for the domains of cognitive, psychomotor and affective were categorized as very good, good and moderate respectively.
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Syabibi, Muhammad Khoiru, and Arkhan Subari. "RANCANG BANGUN SISTEM MONITORING KEAMANAN RUMAH BERBASIS WEB MENGGUNAKAN RASPBERRY PI B+ SEBAGAI SERVER DAN MEDIA KONTROL." Gema Teknologi 19, no. 1 (October 31, 2016): 22. http://dx.doi.org/10.14710/gt.v19i1.21959.
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Muhammad Khoiru Syabibi, Arkhan Subari in this paper explain that Along with the progress of era, the development of advanced technology also impacts on the development of security systems. Sophisticated security systems that digitally integrated has been growing, one of them is a web-based security system. This web-based home security monitoring system uses a raspberry pi b + that serves as a server and media controller, then for the web programming, it uses HTML, CSS and Javascript. This web-based home security monitoring system home uses a webcam (web camera) that functions like CCTV which can be monitored via a web browser, magnetic switch as security detector, keypad as access control to turn off security monitoring system for 10 seconds, and the buzzer and LED as security indicators. When someone enter the house, he/she must press the keypad. If keypad input is correct according to the passcode then the LED will turn off, indicate that home security monitoring system off for 10 seconds. If he/she enter the house without pressing the keypad according to the passcode then when the door opens, a switch magnetic will active, then buzzer will sound and the indicator on the web will change, indicate that he/she is a person who will do the crime.Keyword : raspberry pi b+, webcam, magnetic switch, keypad, buzzer and LED. ReferencesAndre. 2014. Sejarah PHP dan Perkembangan Versi PHP. http://www.duniailkom.com/sejarah-php-dan-perkembangan-versi-php.Apache Software Foundation. About the Apache HTTP Server Project. http://httpd.apache.org/ABOUT_APACHE.html.Arfa. 2014. Akses Kontrol Kendaraan Bermotor Roda Empat Menggunakan Password dan Sensor. Skripsi. Jakarta: STMIK Raharja.Aziz, Abdul. 2012. Pengertian, Fungsi, Serta Cara Kerja Web Server. http://www.dedeerik.com/pengertian-fungsi-serta-cara-kerja-web-server.Baharudin, M. 2011. Pengertian Website. http://www.naevaweb.com/pengertian-website/arsip.html.Cox, Tim. 2014. Raspberry Pi Cookbook. Birmingham: Packt Publishing.Embedded Linux Wiki. Raspberry Pi, Low-level Peripherals. http://elinux.org/RPi_Low- level_peripherals.Embededdlinux. Raspberry Mode B-Block diagram. Diunduh http://embeddelinux01.com.Faizal. 2011. Prinsip Kerja Piezoelectric. http://www.insinyoer.com/prinsip-kerja-piezoelectric.Friedl, Stave. 2015. Secure Linux/Unix Access With Putty and Open SSH. http://unixwiz.net/techtips/putty-openssh.html/2015.Gudang Linux. 2011. Python. http://gudanglinux.com/glossary/python.Gurevich, Vladimir. 2011. Electric Relays: Principles and Applications. London: CRC Press.Harian Android. 2014. Pengertian dan Fungsi SD Card. http://www.harianandroid.com/2014/04/pengertian-dan-fungsi-sd-card.html.Heranudin. 2011. Rancang Bangun Sistem Keamanan Ruangan Menggunakan Radio Frequency. Skripsi. Depok: FT UI.Iswan, Agusta. 2012. Sistem Proteksi Brankas Berpassword Menggunakan Magnetic Doorlock sebagai Penggerak Doorstrike Berbasis Mikrokontroller. Tugas Akhir D3 Teknik Elektro. Semarang: FT UNNES.Kho, Dickson. 2012. Dioda dan Fungsi Dioda. http://teknikelektronika.com/-dioda-fungsi-dioda.Kho, Dickson. 2012. Pengertian LED (Light Emitting Diode) dan Cara Kerjanya. http://teknikelektronika.com/pengertian-led-light-emitting-diode-cara-kerja.Kho, Dickson. Pengertian Resistor dan Jenis Resistor. http://teknikelektronika.com/pengertian-resistor-jenis-jenis-resistor.Komponen Elektronika. 2011. Rangkaian Buzzer. http://komponenelektronika.com/rangkaian- buzzer.html.MS-1 Magnetic Door Switch datasheet. http://www.braude.ac.il/files/departments/electrical_electronic_engineering/labs/data_pages/p3.pdfNasih, Muhammad Usman. 2013. Alat Pengaman Kendaraan Bermotor Menggunakan Password dan SMS. Tugas Akhir. Yogyakarta: STMIK El Rahma.Özcan, Yakut. 2014. Piezoelektrik.Paul Malvino, Albert. 2010. Prinsip-Prinsip Elektronika. Jakarta: Erlangga.Pemrograman Komputer. 2012. Petunjuk Praktikum Pemrograman Komputer. Semarang: D3 Teknik Elektro UNDIP.Prayitno, Indra. 2010. Kupas Tuntas Malwar. Jakarta: Elex Media Komputindo.Raspberry Pi Fondation. GPIO Raspberry Pi Model A dan B. https://www.raspberrypi.org/documentation/usage/gpio/2009Raspberry Pi Fondation. Setting Up And Apache Web Server On A Raspberry Pi. https://www.raspberrypi.org/documentation/remote-access/web-server/apache.md.Raspberrry Pi Fondation. SSH Using Windows. http://raspberrypi.org/documentation/remote-access/ssh/windows.md/2014Richardson, Matt dan Shawn Wallace. 2015. Make: Getting Started with Raspberry Pi. Sebastopol: Maker Media.Robinson, Andrew dan Mike Cook. 2014. Raspberry Pi Projects. Chichester: John Wiley & Sons Ltd.Rohiman, Ao. 2011. Pengertian dan cara kerja router.http://www.catatanteknisi.com/2011/05/pengertian-cara-kerja-router.html.Sidik, Betha. 2011. Javascript. Jakarta: Informatika.Wahyu. Pengertian Webcam dan Fungsinya. http://wahyu.blog.fisip.uns.ac.id/2011/12/06/pengertian-web-cam-dan-fungsinya.Wikipedia. Secure Digital. https://en.wikipedia.org/wiki/Secure_Digital#Micro.
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Muttaqin, Imam Wildan, and Arif Rahman. "Sistem Presensi Berbasis RFID Menggunakan Raspberry Pi 3." Buletin Ilmiah Sarjana Teknik Elektro 1, no. 1 (August 19, 2019): 27. http://dx.doi.org/10.12928/biste.v1i1.850.
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Sistem presensi mahasiswa banyak dilakukan secara konvensional. Sistem presensi otomatis yang ada pun memiliki kinerja yang lambat dan tidak mampu diperbarui secara otomatis. Sistem presensi mahasiswa berbasis RFID menggunakan Raspberry Pi 3 diharapkan mampu menangani masalah-masalah tersebut. Sistem pada penelitian ini dibangun menggunakan modul RFID jenis MIFARE RC522, Raspberry Pi 3 model B, dan RTC DS1307. Prinsip kerja sistem ini yaitu menerima masukan berupa hasil identifikasi ID pada kartu RFID, kemudian hasilnya diolah Raspberry Pi 3 sekaligus menentukan respon, dan merekap data presensi pada server. Hasil presensi berupa nama mahasiswa dan mata kuliah ditampilkan pada LCD 16x2. Sebagai hasil akhir, server mengirim data presensi yang dapat ditampilkan pada komputer klien melalui situs web. Pengujian sistem menunjukkan jarak maksimal identifikasi ID sejauh 4,5 cm dengan rata-rata waktu pembacaan selama 150,53 ms. Penambahan RTC DS1307 menjadikan sistem tidak harus terhubung dengan internet untuk update secara otomatis. Selain itu, penelitian ini juga membuktikan bahwa penghalang kayu, karet, keramik, kaca, plastik, dan akrilik, tidak mempengaruhi jarak dan waktu dalam proses identifikasi kartu RFID. Namun penghalang jenis logam dapat menghalangi proses identifikasi kartu RFID.
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Novikov, D. V., A. S. Stankevich, E. G. Silkis, A. M. Torubarov, and G. A. Perepelkin. "THE MORS-4 SPECTRA RECORDING SYSTEM WITH THE RASPBERRY PI 3 MODEL B MICROCOMPUTER." NAUCHNOE PRIBOROSTROENIE 28, no. 3 (August 29, 2018): 24–28. http://dx.doi.org/10.18358/np-28-3-i2428.
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Muck, P. Y., and M. J. Homam. "Iot Based Weather Station Using Raspberry Pi 3." International Journal of Engineering & Technology 7, no. 4.30 (November 30, 2018): 145. http://dx.doi.org/10.14419/ijet.v7i4.30.22085.
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Weather is the day-to-day state of atmosphere that is hard to predict which affects the activities of mankind and has great significance in many different domains. However, the current weather station in the market is expensive and bulky which cause inconvenience. The aim of this project is to design a weather station with real time notifications for climatology monitoring, interface it to a cloud platform and analyse weather parameters. In this project, a weather station is assembled using SparkFun Weather Shield and Weather Meter and Arduino Uno R3 to collect weather parameters. Data collected from the sensors are then stored into Google Cloud SQL using Raspberry Pi 3 Model B which acts as a gateway between them and analysis of weather data are done. A website and mobile application are developed using Google Data Studio and Android Studio respectively to display the real-time weather conditions in graphical presentation which are accessible by administrator and users. Users will receive notification regarding the weather conditions at that particular place on social media platform regularly and irregularly. Weather prediction is done in short term which allows users to get themselves prepared for their future plan in the next thirty minutes.
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Muzzaki, Arisla Choirudin, Aghus Sofwan, and Muhammad Arfan. "EMBEDDED CODING VIDEO STREAM DALAM RASPBERRY PI MODEL 2 PADA DEVICE TO DEVICE COMMUNICATION." TRANSIENT 6, no. 3 (November 9, 2017): 461. http://dx.doi.org/10.14710/transient.6.3.461-466.
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Pemanfaatan Internet of Things (IoT) saat ini sudah semakin meluas. Cakupan pemafaatannya pun semakin beragam, dari hanya pada sektor pendidikan sebagai sarana berkomunikasi hingga pada hal-hal yang berkenaan dengan kebutuhan sehari-hari. Salah satu pemanfaatan IoT yang sering digunakan saat ini adalah layanan video streaming. Saat ini, telah terdapat beberapa cara dan metode konfigurasi untuk membuat sebuah layanan video streaming, salah satunya adalah dengan proses embedded coding. Coding yang ditanamkan ini nantinya yang menjadi pengirim dari proses streaming video. Dengan digunakannya proses embedded coding untuk mendapatkan layanan video streaming, tentunya akan membuat layanan ini dapat diakses dari beberapa software Video Stream Player yang berbeda-beda. Server ini nantinya merupakan program yang dijalankan dalam sebuah mini computer yaitu Raspberry Pi. Dengan adanya Raspberry Pi beserta komponen-komponen pelengkapnya seperti Raspi Camera, akan memperkecil dimensi alat tanpa mengurangi peforma dari sistem yang dijalankan. Penggunaan teknologi video stream dengan menggunakan proses embedded coding diharapkan dapat menjadi sarana baru untuk meningkatkan peforma layanan streaming video dan bisa mengikuti perkembangan di zaman sekarang.
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GANESH, E. N. "Health Monitoring System using Raspberry Pi and IOT." Oriental journal of computer science and technology 12, no. 1 (March 7, 2019): 08–13. http://dx.doi.org/10.13005/ojcst12.01.03.
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Health Monitoring system using IOT describes the collection and interoperation of Patient data collected from the sensors from the hospitals through IOT Technology. The collected sensor data will support the doctor in the emergency situation for the betterment and improvement of Patient health. The hardware platform to implement the project consists of a sensor and Raspberry Pi 3 Model B equipped in a way to communicate with a doctor through the Internet and Smart Phone. This proposed idea will help doctors to know about the state of patient health and monitor anywhere in the world. In this proposed idea the sensors gather the medical information of the patient that includes patient’s heart rate, blood pressure, and pulse rate Then using the camera the patient is livelily monitored through the Raspberry kit and this information is sent to the Internet and stored in a medical server. The doctor and patient can monitor the patient data from any place of the world through the provided IP server address anytime. The emergency alert is sent to the patient if the sensor value is exceeded by the threshold data. Thus the patient's health parameters are watched lively and regular monitoring through the medical server to a doctor will help to make an effective diagnosis and almost accurate care can be given. The data collected through the IOT will help the patient to recover easily and also enhanced medical care can be given to the patients at a low cost.
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Sulistyo, Meiyanto Eko, Stephanus Hanurjaya, and Muhammad Danang Prastowo. "Monitoring Print Engine Output Using Arduino and Raspberry Pi." Journal of Electrical, Electronic, Information, and Communication Technology 3, no. 1 (April 30, 2021): 6. http://dx.doi.org/10.20961/jeeict.3.1.49771.
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In the printing industry process, monitoring is necessary for quality control of the product. The making of the tool on this project serves to monitor the output of the production machine. This monitoring is done by detecting the product output from the production machine using Sensor E18 D80NK. When the sensor detects the output, the sensor sends a signal to the Arduino UNO R3 which will calculate the amount of output from the product. Arduino will send information of the number of outputs via a USB connection to a central computer that is a Raspberry Pi 3 model B. The Python program on Raspberry Pi will read input from each Arduino address and display the data in realtime. At the same time, the data will be stored as a text file. This text file contains the number of product output and the time of the output. The prototype of this tool has been successfully created and there is still much development to do.
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Aryani, Diah, Muhamad Wahyudin, and Muhammad Fazri. "PROTOTYPE ROBOT CERDAS PEMOTONG RUMPUT BERBASIS RASPBERRY Pi B+ MENGGUNAKAN WEB BROWSER." Journal CERITA 1, no. 1 (February 1, 2015): 1–10. http://dx.doi.org/10.33050/cerita.v1i1.121.
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Current science and technology are developing by leaps and bounds thus providinggreat benefits in all aspects of human life including the robot-a robot designed toassist human tasks through supervision and human control, or use the program. The development of grass that propagate ground quickly often make nursing groundshave to mow the lawn with regular intensive. Related to this, then the tool in the form of a single intelligent robot cutting grass-based Pi B+ raspberry is the application ofrobotic systems that aim to control 2 motor Driver l298n useful for running gear boxwheel robots and grass cutters on Dynamo cutting tools lawns without a crew. The programming language used is the language which has been running pyton Apache Web Server. So by designing Intelligent robot prototype lawnmowing rasbery Pibased B+ using a web browser at the time grass has begun to grow tall, grass-cuttingIntelligent robot can directly perform cutting grass with a controlled web browser.
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Juliansyah, Akbar, Ramlah Ramlah, and Dewi Nadiani. "Sistem Pendeteksi Gerak Menggunakan Sensor PIR dan Raspberry Pi." JTIM : Jurnal Teknologi Informasi dan Multimedia 2, no. 4 (February 6, 2021): 199–205. http://dx.doi.org/10.35746/jtim.v2i4.113.
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Digital security and monitoring systems are entering a new era. Every industry is busy developing security systems according to their individual needs. What can be done is by providing a security perimeter around the assets to prevent unwanted things. There are currently many CCTV (Closed Circuit Television) based security systems; CCTV security systems also have less effective because they require more devices and large enough storage memory. Also, there are other solutions, namely systems that are built using PIR sensors and Raspberry Pi. The PIR sensor is used to detect infrared emissions from humans, so the target object is a human. The PIR sensor also receives heat radiation from humans, so when humans move, this sensor will receive changes in radiation emitted by humans. The purpose of this study is to simulate a solution to the problem of infrastructure design for the development of a physical asset security system using a Wireless Sensor Network and to find out how the security system works using a PIR sensor and Raspberry Pi Model B. The research method used is the Network Development Life Cycle (NDLC) approach. This study illustrates that the Raspberry Pi with hardware capabilities and Rasbian OS and the Python programming language support building a security system. The HC-SR501 PIR sensor can also detect moving objects from the right, left, and front. Email and SMS can be well integrated to produce reports according to the sensor's movement.
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NATALIANA, DECY, IQBAL SYAMSU, and GALIH GIANTARA. "Sistem Monitoring Parkir Mobil menggunakan Sensor Infrared berbasis RASPBERRY PI." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 2, no. 1 (January 1, 2014): 68. http://dx.doi.org/10.26760/elkomika.v2i1.68.
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ABSTRAKMasalah yang selalu timbul dalam sistem perparkiran adalah kurangnya informasi mengenai status ketersediaan lahan parkir, untuk itu diperlukan sebuah sistem monitoring parkir. Tujuan penelitian ini adalah merancang dan merealisasikan model sistem monitoring perparkiran dengan fasilitas pemilihan area parkir dengan berbasiskan Raspberry Pi serta pemanfaatan infrared sebagai sensor. Sistem ini mampu menampilkan status ketersediaan dari area parkir yang ditampilkan pada display serta dilengkapi dengan perhitungan tarif parkir. Pada sistem yang dirancang dilengkapi dengan tombol untuk memilih area parkir, 2 buah sensor pada masing-masing area parkir untuk mendeteksi kendaraan, kamera untuk kemanan dan lampu LED sebagai indikator ketersediaan area parkir. Perangkat lunak yang digunakan pada sistem ini dirancang dengan menggunakan bahasa Python 2 dan untuk sistem database digunakan SQLite3. Pengujian dilakukan secara simulasi pada miniatur perparkiran. Hasil pengujian model sistem perparkiran dapat menampilkan kondisi dari masing-masing area parkir yang ditampilkan pada display. Kedua buah LED berhasil menjadi indikator ada tidaknya lahan parkir yang masih kosong. Untuk sistem perhitungan tarif parkir telah sesuai dengan perhitungan lamanya parkir.Kata kunci: Parkir, Raspberry Pi , Infrared, Python 2, Monitoring.ABSTRACTThe problem which always happens in parking system is the lack of information about the parking area. That’s why we need parking monitoring system. The purposes of this project are to devise and create parking monitoring system which has fitur for ordering parking area. The system based on Raspberry Pi. The system use infra red as sensor. Beside show the availability status of parking area in a display, this system also calculates the price of using the parking area. The System equipped with button for ordering parking area, 2 infrared sensors for each area, web camera for security and 2 LED lamps for availability indicator. Software for this system is made by Pyhton 2 language. For database the system use SQLite 3 as database system. The trial for this system done with simulation in a miniatur parking area. The result of the trial is the system can display about status of parking area. The system is also can make red LED and green LED light depend on the status of parking area. For billing system, the calculation of parking rates fits with the calculation of parking duration.Keywords: Parking, Raspberry Pi, Infra Red, Python 2, Monitoring.
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Florentinus Budi Setiawan, Franciska Amalia Kurnianingsih, Slamet Riyadi, and Leonardus Heru Pratomo. "Pattern Recognition untuk Deteksi Posisi pada AGV Berbasis Raspberry Pi." Jurnal Nasional Teknik Elektro dan Teknologi Informasi 10, no. 1 (February 25, 2021): 49–56. http://dx.doi.org/10.22146/jnteti.v10i1.738.
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Perkembangan teknologi di bidang otomatisasi dan robotika berkembang sangat pesat, karena memiliki tingkat efesiensi tinggi dari segi tenaga dan waktu. Pada sistem pergudangan, salah satu robot yang digunakan adalah Automated Guided Vehicle (AGV). AGV adalah alat transportasi berupa robot yang dikendalikan secara otomatis, yang berfungsi sebagai pengangkut barang, dengan menggunakan sistem navigasi agar bergerak ke arah yang telah ditentukan. Salah satu sistem navigasi AGV yang telah ada ialah dengan mengikuti pola garis pada lantai. Sistem tersebut kurang efisien karena lambat laun pola garis tersebut akan pudar dan tidak dapat terdeteksi kembali akibat gaya gesek dari roda AGV itu sendiri. Oleh karena itu, sangat diperlukan pengembangan sistem navigasi AGV untuk meminimalkan hambatan tersebut. Sistem pattern recognition ini menggunakan pola yang diletakkan pada langit-langit bangunan dan kamera sebagai sensor yang menghadap ke atas sehingga AGV mampu dengan leluasa mendeteksi pola. Kemudian, pola yang sudah terdeteksi diolah melalui perangkat komputer berupa Raspberry Pi 4 Model B yang telah diprogram. Hasil pengujian menunjukkan bahwa sistem ini mampu mendeteksi posisi dan berhasil menampilkan titik koordinat (x,y) dari AGV serta akan tetap berjalan sampai kapan pun hingga program diubah sesuai yang diperintahkan.
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Nguyen, An Toan, Ngoc Thien Nguyen, and Thanh Truc Nguyen. "Research of object recognition using neural network Inception-v3 model operating on Raspberry Pi B3+." Journal of Science, Quy Nhon University 15, no. 1 (February 25, 2021): 13–22. http://dx.doi.org/10.52111/qnjs.2021.15102.
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Image Classification is the most important problem in the field of computer vision. It is very simple and has many practical applications, the image classifier is responsible for assigning a label to the input image from a fixed category group. This article has applied image classification to identify objects by giving the image of the object to be identified, then labeling the image and announcing the label name (object name) through the audio channel. The classification is based on the neural network Inception-v3 model that has been trained on Tensorflow and used Raspberian operating system running on the Raspberry Pi 3 B+ to create a device capable of recognizing objects which compact size and convenient to apply in many fields.
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Marufuzzaman, Mohammad, Teresa Tumbraegel, Labonnah Farzana Rahman, and Lariyah Mohd Sidek. "A machine learning approach to predict the activity of smart home inhabitant." Journal of Ambient Intelligence and Smart Environments 13, no. 4 (July 21, 2021): 271–83. http://dx.doi.org/10.3233/ais-210604.
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A smart home inhabitant performs a unique pattern or sequence of tasks repeatedly. Thus, a machine learning approach will be required to build an intelligent network of home appliances, and the algorithm should respond quickly to execute the decision. This study proposes a decision tree-based machine learning approach for predicting the activities using different appliances such as state, locations and time. A noise filter is employed to remove unwanted data and generate task sequences, and dual state properties of a home appliance are utilized to extract episodes from the sequence. An incremental decision tree approach was taken to reduce execution time. The algorithm was tested using a well-known smart home dataset from MavLab. The experimental results showed that the algorithm successfully extracted 689 predictions and their location at 90% accuracy, and the total execution time was 94 s, which is less than that of existing methods. A hardware prototype was designed using Raspberry Pi 2 B to validate the proposed prediction system. The general-purpose input-output (GPIO) interfaces of Raspberry Pi 2 B were used to communicate with the prototype testbed and showed that the algorithm successfully predicted the next activities.
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Muzawi, Rometdo. "Rancang Bangun Prototype Pengontrolan Lampu Gedung STMIK Amik Riau Berbasis IoT Menggunakan Rasberry Pi 3 Model B." JATISI (Jurnal Teknik Informatika dan Sistem Informasi) 5, no. 1 (September 24, 2018): 100–108. http://dx.doi.org/10.35957/jatisi.v5i1.127.
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Internet of Things (IoT) is a hardware (Raspberry Pi) that can connect to the internet with the aim to expand the internet network that is connected thoroughly to the hardware. The development of the Internet of things (IoT) has been widely used, especially in this day and age, one of the utilization of this IoT technology is the control of electronic room light equipment through global network controlled via smartphone that can be operated remotely. This research aims to build a remote-control device by utilizing internet technology to perform the process of controlling the lights based on the Internet of Things (IoT). This research is done by building a prototype with mobile based application using python and php programming language. In this research there is a feature of controlling the room lights with the first condition of control of one lamp used to turn one room light and the second condition is used to turn the lights simultaneously.
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Dasmen, Rahmat Novrianda, and Nasrul Halim. "IMPLEMENTASI PAPAN INFORMASI DIGITAL MENGGUNAKAN RASPBERRY PI 3 PADA STIPER SRIWIGAMA PALEMBANG." Computatio : Journal of Computer Science and Information Systems 2, no. 2 (October 31, 2018): 196. http://dx.doi.org/10.24912/computatio.v2i2.2570.
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STIPER Sriwigama Palembang is one of the high school agricultural sciences located in the city of Palembang. As with other universities, in the STIPER Sriwigama Palembang environment there are lecturers, staff and students. STIPER Sriwigama Palembang in informing about the presence of lecturers is currently still using a simple manual information board to display the names of lecturers present or not with a static, unattractive and inaccurate display. The purpose of this research is to build a dynamic digital information board where information in it can be arranged according to needs, which can be managed by the information section. This research uses Raspberry Pi which will connect the LED TV with the computer part information. This research will produce an information board that contains interesting features such as the use of running images and text and provide information about the presence of lecturers who are teaching or not teaching which can be arranged through the computer information section. Because it is still in the research process, the current output will be explained limited to the display design and also explained about the configuration of the Raspberry Pi 3 model B so that it can modify the LED TV into a digital information board.
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Hermawan, Diki, and Eko Budi Setiawan. "Prototype of Gas Warning Monitoring Application Using Mobile Android Smartphone : A Case Study." International Journal of New Media Technology 4, no. 1 (June 12, 2017): 17–24. http://dx.doi.org/10.31937/ijnmt.v4i1.533.
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This study aims to monitor gas leakage with case studies in a national company engaged in the production of polycarbonate for drinking water packaging. In the future this research will be referred to as the Company. The Company implements Sistem Manajemen Keselamatan dan Kesehatan Kerja or socalled. System Management K3 (SMK3) to create a safety and health system by involving elements of management, labor, conditions and an integrated work environment in order to prevent and reduce accidents and occupational diseases. One of the causes of work accidents of the many causes that should be a concern is the danger that can be caused by the leaking gas LPG installation. Such hazards may cause explosions to fire that may threaten the safety of workers in companies using LPG gas for their production processes. The system in this study was designed to monitor and provide gas leak warnings to leaked LPG gas installations and promptly take prompt and automatic precautions. With the development of warning gas monitoring via android raspberry-based pi is expected to improve the security system and reduce therisk of work accident caused by LPG gas.
Index Terms— Gas Monitoring, Raspberry pi, MQ2, LPG, Android
REFERENCES[1] F. Pangkey dan G. Y. Malingkas, “Jurnal Ilmiah MEDIA ENGGINEERING,” Penerapan Sistem ManajemenKeselamatan Dan Kesehatan Kerja (SMK3) Pada Proyek Konstruksi Di Indonesia , vol. 2 , pp. 100-113, 2012.[2] B. Hadiwijaya, D. dan A. A. Zahra, “TRANSIENT,” Perancangan Aplikasi CCTV Sebagai Pemantau RuanganMenggunakan IP Camera, vol. 3, p. 232, 2014.[3] R. F. Giant, “Perancangan Aplikasi Pemantau Dan Pengendali Piranti Elektronik Pada Ruangan BerbasisWeb,” TRANSMISI , vol. 2, pp. 71-74, 2015.[4] S. Paul, A. Antony. , “International Journal Of Computing and Technology,” Android Based Home AutomationUsing Raspberry Pi , vol. 1, pp. 143-147, 2014.[5] M. P. Sulistyanto, D. A. Nugraha, N. Sari, N. Karima dan W. Asrori, “Implementasi IOT (Internet Of Things) dalam Pembelajaran di Universitas Kanjuruan Malang,” SMARTICS Journal , vol. 1, pp. 20-23, 2015.[6] H. N. Lengkong, “Perancangan Penunjuk Rute Pada Kendaraan Pribadi Menggunkan Aplikasi GIS BerbasisAndroid Yang Terintregasi Pada Google Maps,” EJournal Teknik Elektro dan Komputer, vol. 1, pp. 20-21,2015.[7] B. Prakasa, M. S. Qiron dan D. Hermanto, “Automatisasi Smart Home Dengan Rasperry Pi Dan SmartphoneAndroid,” pp. 1-13.[8] D. Nurmali dan S. Suhartini, “Komunikasi Data Digital menggunakan Gelombang Radio HF,” Penelitian PusatPemamfaatan Sains Antartika Lapan , vol. 1, pp. 27-30,2005.
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Prasath, K. S. "Analysis of Potholes on Road Using Image Processing." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (August 31, 2021): 1731–34. http://dx.doi.org/10.22214/ijraset.2021.37655.
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Abstract: Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Nowadays, image processing is one among rapidly growing technologies. It forms core research area within engineering and computer science disciplines too. Image detection on road is primarily carried out with the help of camera with Raspberry pi 3 model b+ and stimulation software. The device is built in such a way that we can identify any potholes in the respective roads and able to rectify as soon as possible with the help of the device. The data signals shared by the device will be converted to text signals from which we can get it right. These devices are fixed at top of the lamppost which is located at the corners of the road from where the device is monitoring the road at 120 degree for weekly once respectively. Keywords: Image processing, Image detection on road, Raspberry pi 3, 120 degree
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Arifudin, Ahmad. "Rancang Bangun Sistem Keamanan Pintu Rumah Menggunakan Metode Segitiga Wajah (triangle face) Berbasis Raspberry Pi." Jurnal Teknologi Elektro 12, no. 1 (January 31, 2021): 29. http://dx.doi.org/10.22441/jte.2021.v12i1.006.
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Seiring perkembangan teknologi, semakin banyak peralatan-peralatan maupun sistem keamanan canggih berbasis teknologi yang mutakhir. Semakin tingginya angka kriminalitas terutama pencurian dan perampokan mendorong diperlukannya sistem keamanan yang lebih efektif dan efisien. Keamanan pintu rumah yang baik tentu memiliki sistem penguncian yang baik pula, yang kecil kemungkinannya terjadi pembobolan. Pada perancangan sistem keamanan pintu rumah menggunakan metode segitiga wajah (triangle face) berbasis raspberry pi 3 model B+ yang memiliki kelebihan salah satunya mudah,praktis dalam penggunaan untuk dapat meningkatkan kenyamanan dan keamanan dalam membuka pintu rumah tanpa harus memegang bermacam-macam kunci yang mungkin sangat menggangu. Penggunaan fitur Haar Casecade Classifier dengan OpenCV digunakan sebagai pemograman yang berfungsi untuk melakukan deteksi terhadap suatu objek yang pada penelitian ini adalah wajah. Berdasarkan hasil pengujian pada sistem yang telah dirancang, pengenalan dengan metode segitiga wajah memiliki keakurasian 92% di pencahayaan 104 lux dan keakurasian 84% di pencahayaan yang lebih rendah yaitu 53 lux
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Iglehart, Brian. "MVO Automation Platform: Addressing Unmet Needs in Clinical Laboratories with Microcontrollers, 3D Printing, and Open-Source Hardware/Software." SLAS TECHNOLOGY: Translating Life Sciences Innovation 23, no. 5 (May 10, 2018): 423–31. http://dx.doi.org/10.1177/2472630318773693.
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Laboratory automation improves test reproducibility, which is vital to patient care in clinical laboratories. Many small and specialty laboratories are excluded from the benefits of automation due to low sample number, cost, space, and/or lack of automation expertise. The Minimum Viable Option (MVO) automation platform was developed to address these hurdles and fulfill an unmet need. Consumer 3D printing enabled rapid iterative prototyping to allow for a variety of instrumentation and assay setups and procedures. Three MVO versions have been produced. MVOv1.1 successfully performed part of a clinical assay, and results were comparable to those of commercial automation. Raspberry Pi 3 Model B (RPI3) single-board computers with Sense Hardware Attached on Top (HAT) and Raspberry Pi Camera Module V2 hardware were remotely accessed and evaluated for their suitability to qualify the latest MVOv1.2 platform. Sense HAT temperature, barometric pressure, and relative humidity sensors were stable in climate-controlled environments and are useful in identifying appropriate laboratory spaces for automation placement. The RPI3 with camera plus digital dial indicator logged axis travel experiments. RPI3 with camera and Sense HAT as a light source showed promise when used for photometric dispensing tests. Individual well standard curves were necessary for well-to-well light and path length compensations.
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Samsinar, Riza, and Sulistiawan Sulistiawan. "Prototype Switching Proyektor Wireless Berbasis Web dengan Virtual Network Computing (Vnc) Server Menggunakan Raspberry Pi 3." RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) 3, no. 2 (December 7, 2020): 71. http://dx.doi.org/10.24853/resistor.3.2.71-74.
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Pada perangkat wireless ini berfungsi untuk memudahkan pengguna menghubungkan komputer atau laptop ke projector. Biasanya pengguna masih menggunakan kabel penghubung diantara komputer atau laptop ke projector. Penggunaan perangkat wireless ini memiliki jangkuan luas untuk pengguna. Penggunaan perangkat wireless ini dapat digunakan pada ruangan terbuka. Jangkauan yang dapat diakses oleh pengguna hingga 6 Meter. Dalam menggunakan perangkat wireless ini pengguna perlu menginstal driver software agar dapat digunakan. Software tersebut berfungsi sebagai perintah agar terkoneksi pada perangkat wireless sesuai yang diharapkan. Jika pengguna ingin menghubungkan ke perangkat wireless harus mempunyai Wi-Fi pada komputer atau laptop. Mini PC Raspberry pi 3 model B+ ini berfungsi sebagai pemproses perintah yang dilakukan oleh pengguna. Penggunaan keseluruhan pengguna mengakses melalui internet pada modem dengan security key didalamnya, kemudian membuka browser untuk mengkoneksikannya. Dalam penggunaan perangkat wireless ini pengguna yang telah terhubung dan diijinkan oleh admin akan tampil pada layar projector. This wireless device serves to make it easier for users to connect a computer or laptop to the projector. Usually users still use a connecting cable between a computer or laptop to the projector. The use of this wireless device has a broad reach for users. The use of this wireless device can be used in open spaces. User-accessible range up to 6 Meters. In using this wireless device the user needs to install the driver software so that it can be used. The software functions as a command to connect to wireless devices as expected. If users want to connect to wireless devices, they must have Wi-Fi on a computer or laptop. This mini PC Raspberry pi 3 model B+ functions as a processing command made by the user. The overall use of the user accesses via the internet on a modem with a security key in it, then opens a browser to connect it. In using this wireless device, users who have been connected and authorized by the admin will appear on the projector screen.
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Wen, Jing, and Yuanyao Lu. "Automatic Lip Reading System Based on a Fusion Lightweight Neural Network with Raspberry Pi." Applied Sciences 9, no. 24 (December 11, 2019): 5432. http://dx.doi.org/10.3390/app9245432.
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Virtual Reality (VR) is a kind of interactive experience technology. Human vision, hearing, expression, voice and even touch can be added to the interaction between humans and machine. Lip reading recognition is a new technology in the field of human-computer interaction, which has a broad development prospect. It is particularly important in a noisy environment and within the hearing- impaired population and is obtained by means of visual information from a video to make up for the deficiency of voice information. This information is a visual language that benefits from Augmented Reality (AR). The purpose is to establish an efficient and convenient way of communication. However, the traditional lip reading recognition system has high requirements of running speed and performance of the equipment because of its long recognition process and large number of parameters, so it is difficult to meet the requirements of practical application. In this paper, the mobile end lip-reading recognition system based on Raspberry Pi is implemented for the first time, and the recognition application has reached the latest level of our research. Our mobile lip-reading recognition system can be divided into three stages: First, we extract key frames from our own independent database, and then use a multi-task cascade convolution network (MTCNN) to correct the face, so as to improve the accuracy of lip extraction. In the second stage, we use MobileNets to extract lip image features and long short-term memory (LSTM) to extract sequence information between key frames. Finally, we compare three lip reading models: (1) The fusion model of Bi-LSTM and AlexNet. (2) A fusion model with attention mechanism. (3) The LSTM and MobileNets hybrid network model proposed by us. The results show that our model has fewer parameters and lower complexity. The accuracy of the model in the test dataset is 86.5%. Therefore, our mobile lip reading system is simpler and smaller than other PC platforms and saves computing resources and memory space.
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Amdallah Zulyus, Hadi. "Realtime Informasi Cuaca WEB BMKG." Jurnal Elektro dan Mesin Terapan 3, no. 1 (May 2017): 37–45. http://dx.doi.org/10.35143/elementer.v3i1.127.
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Informasi cuaca yang menjadi satu kebutuhan penting untuk semua orang saat ini. Melihat perkembangan ini , maka timbul sebuah inovasi untuk menciptakan alat yang dapat menampilkan informasi cuaca yang disajikan oleh salah satu penyaji informasi cuaca dari situs resmi. Pada proyek akhir ini, penulis membuat suatu alat yang dapat membaca informasi cuaca dengan menggunakan Raspberry Pi B+. Kemudian untuk pengendalian penampil informasi teks pada LED matrix p10 dilakukan oleh Arduino Uno yang didalamnya terdapat ATMEGA 328. Komunikasi yang digunakan antara Arduino dan Raspberry adalah komunikasi serial menggunakan USB. Informasi cuaca yang didapat dari situs resmi akan selalu di perbarui oleh alat penampil informasi cuaca dan menampilkannya pada LED matrix p10 dalam waktu sekitar 2 sampai 2,5 menit. Setelah melakukan pengujian, diketahui bahwa alat sudah mampu menampilkan informasi secara realtime. Ketika jaringan terputus, alat akan menampilkan informasi ”Jaringan Putus”. Tampilan informasi cuaca ini bermanfaat untuk mempermudah manusia untuk dapat mengetahui informasi cuaca di kota tujuan mereka pada tempat-tempat umum.
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Bayat, M., H. Latifi, and A. Hosseininaveh. "THE ARCHITECTURE OF A STEREO IMAGE BASED SYSTEM TO MEASURE TREE GEOMETRIC PARAMETERS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 183–89. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-183-2019.
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Abstract. Stereo photogrammetry enables collecting precise and detailed three-dimensional data of terrestrial objects. The estimation of qualitative and quantitative tree attributes, in particular those related to geometric measures, is crucial for forest management. In this study, a stereo imaging system is designed in order to measure a set of geometric attributes of urban trees such as crown dimensions, height and diameter at multiple height levels. The system consists of two hardware and software components. The hardware comprises two cameras with a specified baseline, two raspberry pi 3 model B+ boards, a GPS, an IMU and a power bank, all embedded in a box. The software includes a connection between the camera and the raspberry pi 3 in each side as well as data transfer to a laptop. The calibration is conducted in laboratory prior to applying the system and leads to achieve a disparity image from a pair of stereo imagery, which is then processed to extract dense point clouds. The system enables measuring basic, yet crucial tree attributes such as height and diameter in near real-time basis. The entire process is conducted by means of drastic libraries in Robot Operating System (ROS). Apart from being convenient and real-time, the system is associated with the potential for timely and precise measurements, which enable comparative analysis against other existing remote measurement systems as well as reference field data.
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Kanani, Pratik, and Mamta Padole. "Implementing and Evaluating Health as a Service in Fog and Cloud Computing using Raspberry Pi." International Journal of Intelligent Engineering and Systems 13, no. 6 (December 31, 2020): 142–55. http://dx.doi.org/10.22266/ijies2020.1231.13.
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Internet of Things (IoT) generates a myriad amount of data, which is sent over the Cloud computing infrastructure for analytics and Business Intelligence. This application scenario suffers network delays, transmission delays and delays in decision making. Due to these drawbacks, the Cloud-based IoT infrastructure is not suitable for time-critical health care applications. To overcome this problem, a smart way is introduced called “Fog Computing” - a LAN based processing approach which has multiple advantages. When IoT, Fog and Cloud Computing are combined, the resultant system’s performance is far better. Hence, the combination results in a very efficient Health Care system. Fog and Cloud Computing have their dimensions that not only support each other but also explore many new application domains. In this paper, the real-time ElectroCardioGram (ECG) based Health Care system is implemented in Cloud and Fog Computing. Different Quality of Service (QoS) parameters like memory consumption, transmission delays, computation delays, network delays, Carbon dioxide emission, data transferred and response time are measured, analyzed and improved to make the system more efficient. Based on the Fog computing characteristics and capabilities, the Raspberry Pi 3 B+ model is configured as a Health Care serving gateway by using different installation and configuration steps. Initially, the proposed system is tested for one patients ECG data analysis over cloud and Fog. In every set up all QoS parameters are measured and later the system is subjected to multiple ECG streams for varying numbers of patients to find the limitations of the Raspberry Pi node as a Fog Computing node. The obtained results show that for more number of ECG streams the Fog node is not able maintain QoS in decision making time. Every QoS parameter is explored in detail for decision-making time. In the end, the Fog computing based proposed system is concluded for its pros and cons and future aspects of the Fog node are discussed to make better systems.