International Journal of Reconfigurable and Embedded Systems

Increased traffic volumes resulting from urbanization, industrialization, and population growth have given rise to complex issues, including congestion, accidents, and traffic violations at intersections. In the absence of a functional smart traffic light system, traffic congestion occurs due to imbalanced traffic flow at intersections. Current traffic management lacks provisions for ensuring the unobstructed movement of emergency vehicles, even a small delay for which can have significant consequences. This paper presents a smart traffic light controller developed using Verilog hardware description language (HDL) in Quartus Prime 21.1 and Questa Intel field programmable gate array (FPGA) Starter Edition 2021.2, and implemented on an Altera DE2-115 FPGA. The controller is designed specifically to detect emergency vehicle at four-way intersections for inputs radio frequency identification (RFID) readers and infrared (IR) sensors. The RFID readers and IR sensors are managed through slide switches on the FPGA board. The smart traffic light controller contains three sub-modules: clock division, counter, and finite state machine (FSM) operation, enabling it to manage traffic in scenarios with emergency vehicles, high traffic density, and low traffic density. This proposed system can alleviate intersection congestion by controlling access and allocating time effectively. In conclusion, the project ensures the smooth passage of emergency vehicles by continuously monitoring their presence and giving them priority in traffic flow.

Nor Shahanim Mohamad Hadis

Samihah Abdullah

Muhammad Ameerul Syafiqie Abdul Sukor

Irni Hamiza Hamzah

Samsul Setumin

Mohammad Nizam Ibrahim

Azwati Azmin

International Journal of Reconfigurable and Embedded Systems (IJRES)

Design and implementation of smart traffic light controller with emergency vehicle detection on FPGA

基于FPGA的智能交通灯控制器设计与实现及紧急车辆检测

Citizen insecurity in underdeveloped third world countries is aggravated by poor management of arms control and illegal trafficking, which requires information technology solutions in intelligent video surveillance systems for the detection of lethal weapons. The literature review highlights the need for an intelligent video surveillance system to combat high crime, using fog computing, which processes data in real time for the detection of weapons and other crimes. Furthermore, at an international level, solutions based on artificial intelligence and deep learning are being implemented for object recognition and weapons detection. Therefore, this paper describes the design of an intelligent video surveillance system based on artificial vision, fog and edge computing to detect lethal weapons in domestic environments, performing weapon classification and data transmission to police centers. The intelligent video surveillance system allows detecting lethal weapons and operates in three stages: an edge node with a Raspberry Pi 4; a detection algorithm based on a convolutional neural network with YOLOv5; and streaming tagged images to a security unit via WhatsApp. The main conclusion is that the system achieved a precision greater than 0.85 and a quick and efficient response in sending alerts, representing a scalable and effective solution against home burglary.

Ricardo Yauri

José Monterrey

Video surveillance system based on artificial vision and fog computing for the detection of lethal weapons

基于人工视觉和雾计算的视频监控系统用于致命武器检测

&lt;p&gt;In the current furniture industry, making furniture goes through many steps. There are ordering materials, designing, building a prototype, and testing samples. This process is considered quite complex, requiring significant costs, and lengthy production time. The application of finite element analysis (FEA) can be a solution to simulate the furniture manufacturing process. Objective of this research was to determine FEA could substitute making and test prototype furniture thereby saving costs and time. This method utilizes ANSYS 18.1 software for more accurate and rapid calculations, incorporating load variables of 400 N, 600 N, 800 N, and 1,000 N, along with gravitational acceleration of 10 \frac{m}{s^2}. The research evaluates the difference (expressed as a percentage) between the results obtained from simulations and those obtained directly from experiments, considering maximum equivalent stress, maximum principal stress, and total deformation values. The final step involves comparing the simulation with direct testing in terms of cost and time. The research results show an average error factor of 5% across all aspect. In terms of cost, the method can save 1,807 USD and reduce production time by up to one month. From these findings, it can be concluded that the process of prototyping and sample testing can be replaced using the finite element method.&lt;/p&gt;

Fesa Putra Kristianto

Zain Amarta

Nicolas Hutasoit

Nuthqy Fariz

Fania Putri Herinda

Finite element analysis method as an alternative for furniture prototyping process and product testing

有限元分析方法作为家具原型制作和产品测试的替代方案

Agriculture is a leading sector in the economy as well as the most dominant provider of employment for the Indonesian people. The fertile soil factor allows various types of fruit to be grown, including chilies. However, complex problems make chili farmers have limitations in implementing conventional farming systems. Therefore, the development of an agrivoltaic system with internet of things (IoT) integrated sensors on chili plants can help farmers more easily control, add vitamins, fertilizers, and provide plant nutrients that can be done automatically periodically based on a real-time clock schedule. This system also operates using photovoltaic (PV) as a pumping machine for water circulation. Other technologies such as mini smart cameras are also being developed to monitor and take pictures of chilies which will later be converted using the graphical user interface (GUI) application for segmentation. The method used in this chili fruit classification uses an artificial neural network in classifying ripe, raw, and rotten chilies. The classification results obtained an R value of 0.9, which means it is close to a value of 1 in the suitability of the chili image. Therefore, farmers will find it easier to sort the chilies that will be harvested.

Wanayumini Wanayumini

Habib Satria

Rika Rosnelly

Design of agrivoltaic system with internet of things control for chili fruit classification using the neural network method

基于物联网控制的农光互补系统设计：采用神经网络方法进行辣椒果实分类

Monitoring cervical muscle pain during teleworking, exacerbated by the COVID-19 pandemic and increased remote work, highlights electrotherapy as a crucial physical therapy tool to mitigate muscle pain and promote tissue recovery, addressing ergonomic and occupational health problems that affect the well-being of remote workers. The research proposes to design a transcutaneous electrical nerve stimulation (TENS) device to monitor cervical muscle pain during teleworking, addressing the urgent need for technological solutions to mitigate this problem and improve the quality of life of teleworkers through data acquisition and processing, hardware development, implementation device monitoring, and evaluation software. For this, a TENS device was designed with a graphical interface to treat muscle pain in the neck of teachers who do remote work, dividing it into four stages: signal acquisition and generation, Bluetooth communication with an Android device, signal conditioning, and amplification and protection, following a development scheme that includes circuit design in Proteus and the creation of a mobile application in App Inventor. In conclusion, it was obtained that the power supplies have an average error of less than 1%, indicating good general performance and confirming the consistency and optimal performance of the proposed therapies.

Juan Balvin

Renzo Lobo

TENS device for cervical pain during teleworking controlled remotely by mobile application

通过移动应用程序远程控制的TENS设备用于缓解远程办公期间的颈部疼痛

Publication Information	Publisher: Institute of Advanced Engineering and Science (IAES)，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 2019，Proportion of original research papers: ，Self Citation Rate:， Gold OA Rate:

International Journal of Reconfigurable and Embedded Systems

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Design and implementation of smart traffic light controller with emergency vehicle detection on FPGA

Video surveillance system based on artificial vision and fog computing for the detection of lethal weapons

Finite element analysis method as an alternative for furniture prototyping process and product testing

Design of agrivoltaic system with internet of things control for chili fruit classification using the neural network method

TENS device for cervical pain during teleworking controlled remotely by mobile application

Design and implementation of smart traffic light controller with emergency vehicle detection on FPGA

Video surveillance system based on artificial vision and fog computing for the detection of lethal weapons

Finite element analysis method as an alternative for furniture prototyping process and product testing

Design of agrivoltaic system with internet of things control for chili fruit classification using the neural network method

TENS device for cervical pain during teleworking controlled remotely by mobile application

ISSN	2089-4864, 2722-2608
h-index	7