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Design of an Automatic Price Tag System for Web-Based Retail Business 9

Design of an Automatic Price Tag System for Web-Based Retail...

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Liawatimena, Suryadiputra Gunawan, Devina Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Deparment BINUS Graduate Program Master of Computer Science Jakarta11480 Indonesia Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

Modern retail businesses face a significant challenge with the inefficiency of manually changing price labels on shelves. This manual process not only consumes valuable time and resources but also increases the likelihood of errors, leading to potential inaccuracies in pricing and a less streamlined shopping experience for customers. The proposed solution is the implementation of an Electronic Shelf Label (ESL) system that automatically displays the prices of goods on retail business shelves. This system connects a website (front end and back end) to e-paper via a Wi-Fi network and microcontroller, allowing retail business owners to update prices more easily. Additionally, buyers can search for desired items through the website. The results are the time to send data from the website to the e-paper, namely, to know the performance of the e-paper used. The average time required from 10 attempts to send data from the website to the e-paper is 20.935 seconds. Since the data is connected to the server and will be updated automatically, using this system will be more efficient than manually changing the price label, although it takes time to transfer data from the website to the e-paper. © 2024 IEEE.

关键词： Sales

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Traffic Signs Detection System Using YOLO (You Only Look Once) That Provides Notification 1

Traffic Signs Detection System Using YOLO (You Only Look Onc...

引用

1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Setiawan, Yosua Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350368918

Road accidents have become a problem for many road users in many countries. It may affect human daily activity and tasks, potentially influencing productivity and safety. Therefore, reducing road accidents as swiftly and effectively as possible is critical. For this reason, a Traffic signs detection system has been developed in this work to improve road safety. The detection system can detect traffic signs on the road such as traffic lights, speed limits, and no U-turn signs, and then it will provide users with the corresponding text on an LCD and vibration feedback using a motor. Throughout this work, the You Only Look Once (YOLO) algorithm is proposed for detecting traffic signs on the road. Moreover, a camera is used to extract live videos which serve as an input for the Raspberry Pi 4 model B containing custom YOLOv5 and YOLOv8 models. The system then sends the output to an LCD, a vibration motor, and a radio frequency (RF) module as notifications for users. In the end, the performance of the proposed method has been collected and it is found to produce good accuracy within an inconsiderable amount of 1.677 images and 2.263 annotations. Therefore, the accuracy of 0.69 for YOLOv5 and 0.7 for YOLOv8 were obtained from the training and validation process. Furthermore, the system accurately detects the traffic signs on the road. © 2024 IEEE.

关键词： Traffic signs

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Design and Development of an Internet of Things (IoT)-Based Application and System to Detect Stunting in Infants and Toddlers 10

Design and Development of an Internet of Things (IoT)-Based ...

引用

10th International HCI and UX Conference in Indonesia, CHIuXiD 2024

作者： Tiffany, Theresa Jeremia, James Lie, Zener Sukra Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Engineering Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350380439

Currently, the process of monitoring children's growth in Indonesia relies on manual methods for collecting anthropometric data. These methods pose a risk of data recording errors. Additionally, the ratio of healthcare workers to children in Indonesia is 1:90, a significant disparity that hinders efforts to reduce the prevalence of stunting in the country. To support the third Sustainable Development Goal (SDG), which emphasizes 'Good Health and Well-being,' it is crucial to address issues in the stunting management process, from data collection to monitoring. The design and development of this iOS-based mobile application aim to assist in monitoring child growth and provide guidance and steps for prevention and treatment. Besides application development, it also involves the design and development of an Internet of Things (IoT) system to aid in the collection of children's anthropometric data. The research methodology includes studying stunting cases in Indonesia, anthropometric data calculation methods, stunting prevention and management steps, application design and development, automatic anthropometric data collection, and online data storage and transmission using IoT technology. The developed application and system have been tested and successfully integrated. The IoT device has an accuracy rate of 99.83% for weight measurement calibration and 98.68% for height or length measurement calibration. From the testing results of the child condition calculation method in the application, an accuracy rate of 100% was achieved. © 2024 IEEE.

关键词： Anthropometry

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Development of Detection Lung Disease Stand Alone System Based on Convolutional Neural Network (CNN) 7

Development of Detection Lung Disease Stand Alone System Bas...

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7th International Conference of computer and Informatics engineering, IC2IE 2024

作者： Liewarnata, Edgar Caesar Mariana, Yosica Tan, Sofyan Liawatimena, Suryadiputra Astuti, Winda Bina Nusantara University Binus Aso School of Engineering Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Aso School of Engineering Product Design Program Industrial Engineering Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Automotive and Robotics Program Computer Engineering Department Binus Aso School of Engineering Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798331505530

Lung disease, especially Tuberculosis (TBC), placed the highest death rate in Indonesia. Tuberculosis (TB) in Indonesia is ranked second after India. Therefore, it is important to reduce or early detection of the lung disease, to prevent this disease and speed up handling. The system can recognize the disease lung identification, and the system applied as standalone system. In this work, the Convolutional Neural Network (CNN) approach for identifying diseases lung identification is proposed. The Mel Frequency Cepstral Coefficient (MFCC) applied to process the stethoscope sounds which will used as input to the CNN. The performance of the proposed system has been investigated and resulted. The accuracy of 99% and 98%, for training and testing accuracy respectively. Furthermore, the system accurately detects lung diseases identification. © 2024 IEEE.

关键词： Lung cancer

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Histogram of Oriented Gradients (HOG) and Haar Cascade with Convolutional Neural Network (CNN) Performance Comparison in the Application of Edge Home Security System 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Asy’ari, Muhammad Zacky Filbert, Sebastian Sukra, Zener Lie Automotive and Robotics Program Computer Engineering Department BINUS ASO of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

In recent years, security has played a significant role in our daily lives. House security has become more popular with the enhancement of the Internet of Things (IoT) in intelligent home automation. This paper aims to build a system that can detect faces and the presence of unknown people using computer vision methods combined with the Internet of things. Two algorithms, Histogram of Oriented Gradients (HOG) and Haar Cascade classifiers with the enhancement of Convolutional Neural Network (CNN), were used to compare their performance. The system utilizes Nvidia Jetson Nano as an edge device, HD camera, Light Emitting Diode (LED), and sound buzzer as peripheral hardware. Telegram messenger application was used to notify the homeowner when uninvited guests passed through the pre-defined security area. In the result, the HOG method has 100% accuracy compared to 75% Haar Cascade with 720p video quality in the proposed developed system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Internet of things

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Simulation of Data Acquisition System Using SimulIDE, Virtual Serial Port and Python 9

Simulation of Data Acquisition System Using SimulIDE, Virtua...

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9th International Conference on Education and Technology, ICET 2023

作者： Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Engineering Program Computer Engineering Department Jakarta Indonesia

ISBN: (纸本)9798350358292

Data acquisition systems are commonplace in the current era of digitalization and Industry 4.0. These systems are typically used to obtain data from sensors, whether analog or digital, which is then stored for processing in subsequent stages. However, the implementation of hardware for creating data acquisition systems can be challenging due to constraints such as laboratory facilities, budget limitations, and other factors. Therefore, in this research, SimulIDE simulation software was employed to simulate electronic components and the Arduino Uno. To make this virtual Arduino appear as a physical one to the host computer, PyVirtualSerialPorts was used as a virtual serial port. The data acquisition system was created using Python programming with several key features: it can store data in CSV format, present data plots and graphs, and display the frequency spectrum of signals. The system achieved a sampling speed of 1000 data points per second, with input signals limited to a maximum of 10 Hz. This study also shows that signal distortion can occur due to excessively frequent data plotting and Fast Fourier Transform (FFT) processing. Therefore, the use of SimulIDE simulator, virtual serial port, and Python can be utilized in the learning process of a simple data acquisition system. © 2023 IEEE.

关键词： Python

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Car Engine and Chassis Assembly Training Simulation Using VR Technology

Car Engine and Chassis Assembly Training Simulation Using VR...

引用

2023 International Conference on Electrical engineering and Informatics, ICEEI 2023

作者： Noya, Miguel Yehezkiel Asy'ari, Muhammad Zacky Kuswandi, Christian Bernard Sukra, Zener Lie Automotive and Robotics Program Binus Aso School of Engineering Bina Nusantara University Computer Engineering Department Jakarta Indonesia

ISBN: (纸本)9798350381290

The process of educating and learning about the automotive industry is still ongoing, and one of the most effective techniques is the provision of direct practice. Such a system is regarded as effective, albeit with certain downsides. One of them is the restricted area and time required to conduct the exercise, as well as the significant risk of accidents during vehicle engine assembly. Based on these justifications, Vehicle Engine Assembly Simulation with Virtual Reality (VR) Technology is now available as an alternate means of educating students about the automotive industry, particularly car engine assembly. This concept employs a virtual environment that allows users to perceive the automobile world in real time through an immersive experience. VR allows users to directly disassemble automobile engines. This virtual reality application was created utilizing the Oculus Quest 2 platform and the Unity Game Engine. © 2023 IEEE.

关键词： Virtual reality

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computer Vision-Based Hydroponic Lettuce Contour and Area Recognition System

Computer Vision-Based Hydroponic Lettuce Contour and Area Re...

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2023 International Conference on Electrical engineering and Informatics, ICEEI 2023

作者： Pranowo, Samuel Raymond Sukra, Zener Lie Asy'ari, Muhammad Zacky Paryasto, Marisa Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Telkom University Computer Engineering Program Electrical Engineering Department Bandung Indonesia

ISBN: (纸本)9798350381290

Agriculture is a vital industry for the people of Indonesia, but there are several obstacles, including limited space in urban areas and inefficient conventional sorting and harvesting methods. Using computer vision to choose hydroponic lettuce that is ready to be harvested and a robotic arm to bring the selected lettuce yields, the produced system aims to solve this problem. The system's computer vision algorithms include color space conversion, intensity transformation, and an algorithm for following borders. This project's research methodology combines a quantitative approach with an experimental approach, which consists of conducting several trials on the built system. Several trials demonstrated that the computer vision software was able to accomplish the specified objectives. The average success rate of the developed computer vision system is 93%, while the average success rate of the robot arm is 85%. © 2023 IEEE.

关键词： Lettuce

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Analyze and Predict Car Accidents Using Different Machine Learning Algorithms 8

Analyze and Predict Car Accidents Using Different Machine Le...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Harimanto, Farrell Putra Andrew, Chris William, Henry Asy'ari, Muhammad Zacky Artanto, Samuel Albert Puji, Muhammad Nurul Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

Traffic accidents can occur from various factors, ranging from the driver themselves to problems with the vehicle. Road and traffic accidents are the most significant factor of fatalities in the world. Most of the causes of accidents are the drivers themselves. Poor physical and mental conditions can significantly impact how to drive. The driving experience is also important;the longer the driver has been driving, the more professional he will be, and vice versa. Smart City solutions can predict the severity of accidents and give information to the authorities in order to reduce the number of fatalities. This paper investigates the factors that may lead to an accident on the road. By looking at data collected from traffic-related accidents and then visualizing it to make it easy to analyze;then, from this data, we will predict the causes of traffic accidents so they can be avoided. The best algorithm based on accuracy, MAE and RMSE is Random Forest Classifier with 0.8461, 0.1663 and 0.4376, respectively. © 2023 IEEE.

关键词： Machine learning

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Automation Lamp Healing Application based on Face Expression Identification System using Convolution Neural Network (CNN)

Automation Lamp Healing Application based on Face Expression...

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2023 International Conference on Electrical engineering and Informatics, ICEEI 2023

作者： Saduki Simangunsong, Devin Onil Mahesh Puji, Muhammad Nurul Astuti, Winda Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9798350381290

The disruption of routines, education, recreation, as well as concerns about family income and health, has left many young people feeling fearful, angry, and worried about their future. In this system, a smart system will be developed that can capture, process, and interpret facial expressions so that a person's emotions can be easily and accurately identified, which is one of the best solutions. The system will use artificial intelligence that has been trained beforehand using suitable datasets. In the processed of developing the system, Face image with the size of 48 x 48 x 1 became the input of the system, processes by Convolution layer using Relu activation function. The activation function used in the output layer is softmax because it is suitable for more than 2 classifications. by applying CNN based on Adam optimization which have result on 98.96% and 70%, for training and testing accuracy, respectively. Furthermore, the system accurately turn-on the healing lamp based on the emotion identified. © 2023 IEEE.

关键词： Face recognition

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