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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Le, Viet Truong
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Performance enhancement of high-speed free space optical transmission link for the implementation of 5G and internet of things Ai, Duong Huu; Nguyen, Van Loi; Luong, Khanh Ty; Le, Viet Truong
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6373-6379

Abstract

Internet of things (IoT) with continuous development allows multiple devices to be connected to each other through the external environment. With that, free space optical (FSO) transmission links provide high data transmission rates, so that enhanced quality of services, that is very suitable for deployment for fifth generation (5G) and IoT. FSO is known as license free, cost effective and line-of-sight green communication technology, which is employed in various circumstances, such as high data rate connections between buildings within campus or city. This study performs enhancement of FSO link for reconfigurable intelligent surfaces (RISs) aided over free space with gamma-gamma distribution channels. The paper analyzes the performance of FSO links affected by misalignment fading, RISs aided, and link distance with the subcarrier quadrature amplitude modulation scheme. Several numerical outcomes obtained for average electrical end-to-end signal-to-noise ratio, misalignment fading displacement standard deviation and link distance are shown to illustrate the average channel capacity of systems.
Notice of Retraction Design of mean filter using field programmable gate arrays for digital images Ai, Duong Huu; Nguyen, Van Loi; Luong, Khanh Ty; Le, Viet Truong
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i3.pp1430-1436

Abstract

Notice of Retraction-----------------------------------------------------------------------After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IAES's Publication Principles.We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.The presenting author of this paper has the option to appeal this decision by contacting ijeecs.iaes@gmail.com.-----------------------------------------------------------------------In this paper, we design and analysis of mean filter using field programmable gate arrays (FPGAs) for digital images, FPGAs are integrated circuits consisting of interconnections that connect programmable internal hardware blocks allows users to customize operations for a specific application. FPGA is an ideal choice for real-time image processing, these FPGA devices are controlled in Verilog or VHDL languages, allowing to design at different levels and adapt to design changes or even support new applications throughout the life of the component. Digital image filtering is the most important task in image processing and with the help of computers, image recognition involves identifying and classifying objects in an image. This paper design of mean filter for digital image processing, implementation and analysis of image processing algorithms on FPGAs. The results obtained on the FPGA are compared and analyzed with the results by MATLAB software.
Applications of artificial intelligence in indoor fire prevention and fighting Huu Ai, Duong; Nguyen, Van Loi; Luong, Khanh Ty; Le, Viet Truong
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp2646-2654

Abstract

In this study, we design and analysis of artificial intelligence (AI) in indoor fire prevention and fighting. The application of image recognition processing technology has progressed from the early stages using color recognition and feature extraction methods, a newer approach is optical flow using image sequence data to identify motion regions. Image recognition processing technology, a subset of computer vision and AI, has numerous applications across different industries. It allows machines to interpret and make decisions based on visual data, such as photos, videos, or live camera feeds. Recently, AI has many applications in the field of indoor fire prevention and firefighting, leveraging real-time data analysis, predictive modeling, and automation to enhance safety and efficiency. With the application of a neural network, the simulated flame features in the laboratory are used as the input; The image containing the flame from the animation and the features of the image are fed into the artificial neural network obtained from the image from the charge-coupled device camera.
Co-Authors Ai, Duong Huu Huu Ai, Duong Luong, Khanh Ty Nguyen, Van Loi