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2023 International Symposium on Green Technologies and Applications, ISGTA 2023

作者： Chehri, Abdellah Chaibi, Hasna Rhajbal, Zineb Chegri, Badre Eddine Dep. of Math. and Computer Science Royal Military College of Canada Kingston Canada Polydisciplinary Faculty Molay ISmail University Errachidia Morocco SUPMTI GENIUS Laboratory Rabat Morocco Mohamed V University Rabat Morocco

Currently, we are confronted with the presence of two significant transformations. The emergence of technologies like artificial intelligence, the Internet of Things, social media, Industry 4.0, and Society 5.0 is significantly impacting the behavior of individuals, societies, and countries in the 21st century. The second transformation pertains to various critical issues such as climate change, desertification, food and water security, and the future of life on our planet. This paper aims to analyze the impact of emerging technologies on mitigating climate change. The central inquiry at hand is whether humanity possesses the ability to transform the ongoing digital revolution into effective climate action. Specifically, we will analyze the fundamental question. Do digital technologies and information management contribute to the problem or offer a solution? © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Energy efficiency

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The Impact of GPU on Containerized computer Vision Applications on Edge Nodes

The Impact of GPU on Containerized Computer Vision Applicati...

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IEEE International Conference on Edge Computing (EDGE)

作者： Osamah I. Alqaisi Ali Şaman Tosun Turgay Korkmaz Department of Computer Science University of Texas at San Antonio San Antonio TX USA Dep. of Math. and Computer Science The University of North Carolina at Pembroke NC USA

ISBN: (数字)9798350368499

ISBN: (纸本)9798350368505

Edge computing revolutionizes computer vision, but faces challenges due to computational demands and complexities in dep.oyment and platform integration. In addressing these hurdles, container technology emerges as a crucial solution, particularly in mitigating dep.oyment and security issues. However, the impact of GPU acceleration on containerized computer vision applications remains understudied. This paper explores containerized computer vision applications across ARM edge devices, analyzing performance on different CPUs and GPUs. Insights cover processing time, CPU usage, memory utilization, and application performance, highlighting the importance of ARM processor selection. Integrating CPU and GPU enhances execution time but leads to significant memory usage increases. Workload escalation strains the GPU, resulting in slowed processing, and its performance becomes comparable to that of the CPU. Furthermore, the performance of computer vision applications varies with different containers. These findings underscore the delicate balance between CPU and GPU utilization and the pivotal role of algorithm selection in optimizing containerized computer vision applications on edge devices.

关键词： Performance evaluation computer vision Graphics processing units Containers Complexity theory Security Faces

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Analysis and Design of Terahertz Elliptical Slot Antenna Based on Photonic Crystal Substrate

Analysis and Design of Terahertz Elliptical Slot Antenna Bas...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Temmar, Mohamed Nasreddine Nedil, Mourad Chehri, Abdellah Val-d'OrQCJ9P 1Y3 Canada Royal Military College of Canada Dep. of Math. and Computer Science KingstonON11 K7K 7B4 Canada

ISBN: (纸本)9781665442282

This paper aims to develop a photonic band gap substrate-based slot microstrip patch antenna for terahertz applications. The proposed antenna is based on an elliptical slotted patch placed on the top of a photonic crystal structure to improve the conventional microstrip patch antenna in terms of the undesirable surface waves and its electrical properties. As a result, good radiation characteristics are achieved. Besides, an enhancement of more than 35% and 91% are observed for a total bandwidth of 203.5 GHz and a realized gain of 9.1 dBi, respectively. © 2023 IEEE.

关键词： Slot antennas

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Vision of IoT, 5G and 6G Data Processing: Applications in Climate Change Mitigation

Vision of IoT, 5G and 6G Data Processing: Applications in Cl...

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2022 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2022

作者： El Maachi, Soukaina Saadane, Rachid Wahbi, Mohamed Chehri, Abdellah Badaoui, Abdelmounaim Hassania School of Public Works SIRC-LAGES-EHTP Casablanca Morocco Royal Military College Dep. Math. and Computer Science Kingston Canada University Mohamed v LASTIMI-EST Sale Morocco

ISBN: (纸本)9798350332421

The Earth is becoming increasingly hot as we experience more record-breaking heat waves, ice melting, and an increase in average temperatures. The repercussions of global climate change are becoming increasingly evident, which led to climate change being named the 'greatest global health threat of the twenty-first century.' As a result, the international community established an ambitious plan for going green, promoting human development, and preserving the biosphere by adopting the Paris Agreement and the Sustainable Development Goals. As a result, international cooperation efforts have been increasingly put forward. This paper presents ways in which the Internet of Things could benefit the current efforts toward climate change mitigation endeavors. We discuss state-of-the-art projects that have been established worldwide to use recent advancements in 5G/6G technologies and IoT to monitor, model, and combat the impacts of global climate change on agriculture, water resources dep.etion, and coastal erosion. © 2022 IEEE.

关键词： Water resources

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Containerized computer Vision Applications on Edge Devices

Containerized Computer Vision Applications on Edge Devices

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IEEE International Conference on Edge Computing (EDGE)

The proliferation of IoT devices has led to various computer vision applications, where addressing bandwidth and latency challenges through edge nodes presents significant benefits. However, there are still existing gaps and a need for improvements to optimize IoT applications, especially in the field of computer vision, by overcoming limited resources and enhancing device performance. Addressing these challenges is essential to unlock the full potential of IoT applications in real-world scenarios. This paper evaluates the use of lightweight container technology for computer vision applications which using different algorithms, such as Haar Cascades, HOG and CNN with YOLO algorithm, on edge devices and provides a comprehensive comparison and analysis of different versions of computer vision applications in containers in terms of processing ability, and performance. It focuses on containerizing computer vision applications using Docker to achieve safe execution of multiple applications on these devices without interference and to enable flexibility, efficiency, portability, scalability, and isolation. The study also examines the resource usage, execution time, and receiving time of containerized computer vision applications. The research findings significantly advance our understanding of computer vision processing in IoT and edge computing, thereby opening up new avenues for real-time computing scenarios. These insights have the potential to drive transformative advancements in the field, enabling more efficient and accurate computer vision applications in IoT and paving the way for enhanced real-time decision-making, automation, and intelligent systems.

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Can Digital Technology Breakthroughs Contribute to Climate Change Mitigation?

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Procedia computer science 2024年 236卷 265-272页

作者： Abdellah Chehri Hasna Chaibi Zineb Rhajbal Badre Eddine Chegri Dep. of Math. and Computer Science Royal Military College of Canada Kingston Canada Polydisciplinary Faculty Errachidia Molay ISmail University Morocco SUPMTI GENIUS Laboratory Hassan-Rabat Morocco Mohamed V University Rabat Morocco

关键词： Sustainability ICT Smart Grid Energy Efficiency Artificial Intelligence

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Glaucoma Retinal Image Classification Based on Multichannel Gabor Filtering and Transfer Learning

Glaucoma Retinal Image Classification Based on Multichannel ...

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IEEE Conference on Vehicular Technology (VTC)

作者： Mohamed Chaabane Abdellah Chehri Hasna Chaibi Abdessamad Elrharras Rachid Saadane Laboratory of SIRC-LaGeS Casablanca Dep. Math. and Computer Science Royal Military College Kingston Canada Genuis Laboratory Supmti Rabat Morocco

The retina is affected by glaucoma and diabetic retinopathy (DR). Glaucoma must be detected early because it is irreversible and one of the leading causes of blindness. A delayed diagnosis will result in permanent vision loss. It is characterized primarily by ganglion cell dysfunction, which changes the thickness of the retinal nerve fiber layer and the shape of the optic nerve head. As a result, early detection of glaucoma is critical for preventing vision loss. This study employs a hybrid approach to glaucoma diagnosis by combining its powerful Multichannel Gabor filtering and Principal Component Analysis (PCA) capabilities with various transfer learning architectures such as MobileNet, MobileNetV2, and NASNet. These classifiers divide the source retinal images into two groups: glaucoma and non-glaucoma. The suggested approaches are used and evaluated on a dataset of Retinal Fundus Images. For the glaucoma diagnostic method, this strategy yields 99% Precision, 97% Recall, and 98% Accuracy.

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Machine Learning Classification of Hermite Gaussian Beams for 5G and Beyond Free-Space Optical Backhaul Links

Machine Learning Classification of Hermite Gaussian Beams fo...

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IEEE Conference on Global Communications (GLOBECOM)

作者： A. Chehri A. Ahmed M. Z. Shakir Dep. of Math. and Computer Science Royal Military College of Canada Kingston Canada School of Electronic Engineering and Computer Science Queen Mary University of London University of the West of Scotland UK

Free space optical (FSO) communication offers an excellent opportunity to develop energy-efficient, secure, and ultrafast data links for 5G and beyond applications, including heterogeneous networks with massive connectivity and wireless backhauls for cellular systems. However, the effect of an optical beam's pointing inaccuracy combined with the impact of climate factors must be considered in the FSO communication system. In this paper, we first evaluate the performance reliability and availability of NRZ-based mode division multiplexing (MDM)-FSO backhaul. In particular, a single wavelength laser is used to transmit four different optical beams, using four different wavelengths. It also explores and classifies four beams used for capacity enhancement in mode division multiplexed MDM-FSO backhaul links. Several Machine Learning (ML) models are used to classify the four optical modes. Results indicate successful transmission of 80 Gbps. Furthermore, the primary findings indicate that the ML model exhibits an impressive accuracy rate of approximately 97% in classifying four distinct beams.

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Poster: Selection of Optimal Neural Model using Spiking Neural Network for Edge Computing*

Poster: Selection of Optimal Neural Model using Spiking Neur...

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International Conference on Distributed Computing Systems

作者： Sanaullah Kaushik Roy Ulrich Ruckert Thorsten Jungeblut Dep. of Eng. and Math. Industrial IOT University of Applied Sciences and Arts Bielefeld Germany Dep. of Computer Science Cyber Defense and AI Lab Lab North Carolina A&T State University NC USA Dep. of Faculty of Technology Cognitive Interaction Technology Universitat Bielefeld Bielefeld Germany

ISBN: (数字)9798350386059

ISBN: (纸本)9798350386066

Spiking Neural Networks (SNNs), are inspired by the biological brain's complicated signaling mechanisms and possess unique characteristics that set them apart from traditional artificial neural networks. This research study explores the challenging domain of image classification, specifically utilizing the well-known MNIST dataset through the development and thorough evaluation of different neural models for edge computing. However, the primary contribution is the autonomous selection of the best-performing SNN model through various early stopping approaches and validation functions, allowing the models to autonomously adapt during training. In addition, this article presents the standalone AutoML-SNN model, which is the introduction of dynamic elements into selected SNN domains, enhancing their adaptability to complex patterns within the dataset. Furthermore, the early stopping methodologies are used to reduce overfitting hazards, and using the 3000-neuron set, the LIF appeared as the most proficient neural model.

关键词： Training Adaptation models Computational modeling Biological system modeling Neurons Spiking neural networks Hazards

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Reconfigurable Intelligent Surfaces and DF-relay Improved Spectral Efficiency in Cognitive Radio Networks 97

Reconfigurable Intelligent Surfaces and DF-relay Improved Sp...

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97th IEEE Vehicular Technology Conference, VTC 2023-Spring

作者： El Mettiti, Abderahmane Saber, Mohamed Chehri, Abdellah Chaibi, Hasna Badaoui, Abdel Saadane, Rachid Faculty of Sciences University Mohamed v Ehtp LRIT-GSCM Morocco SIRC/LAGeS Ehtp Laboratory Engineering System Casablanca Morocco Royal Military College Dep. Math. and Computer Science Kingston Canada Supmti Genuis Laboratory Rabat Morocco Mohammed v University Laboratory Lastimi Casablanca Morocco

ISBN: (纸本)9798350311143

Cognitive radio (CR) is considered a primary technology for spectrum usage efficiency and dynamic spectrum management. Spectrum sensing is an essential cognitive radio cycle function. Recently, reconfigurable intelligent surfaces (RIS) technology has emerged as a promising new enabler of 6G wireless communication, with the ability to control signal propagation and increase signal coverage and spectrum management. This paper investigates how integrating RISs with CR can improve spectral efficiency. First, we optimize the RIS parameters by identifying the optimal transmit powers and number of RIS antennas. Then, we compare the novel RIS technology with the traditional decode-and-forward (DF) relaying technology. Next, we investigate how adopting RIS can enhance spectral efficiency. Finally, we demonstrate how integrating the novel technology of reconfigurable intelligent surfaces with CR can significantly increase spectrum detection, the most crucial step in the cognitive radio process. Simulation studies indicate that RIS is more energy-efficient than SISO and DF-relay communications in various setups. Moreover, by boosting spectrum sensing capability in CR situations, RISs can significantly enhance the efficiency of frequency spectrum usage. © 2023 IEEE.

关键词： Cognitive radio

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