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32nd Wireless and Optical Communications Conference, WOCC 2023

作者： Petkovic, Milica Tegos, Sotiris A. Diamantoulakis, Panagiotis D. Vukobratovic, Dejan Panayirci, Erdal Stefanovic, Cedomir Karagiannidis, George K. Faculty of Technical Sciences Novi Sad Serbia Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Greece Kadir Has University Istanbul Turkey Aalborg University Aalborg Denmark Cyber Security Systems and Applied Ai Research Center Lebanon

ISBN: (纸本)9798350337150

In this work, we design and analyse a Slotted ALOHA (SA) solution for Optical Wireless Communication (OWC)-based Internet of Underwater Things (IoUT). In the proposed system, user devices exchange data with an access point (AP) which exploits the capture effect. The space spanned by the IoUT nodes is three-dimensional, i.e., users are located in half-sphere centered at the AP placed at the bottom of a floating object at the water surface level. The analytical expressions for the system throughput and reliability expressed in terms of the outage probability are derived. Based on the simulated signal-to-noise-and-interference-ratio statistics and derived analytical expressions, we present numerical results that investigate the trade-off between the system performance and the IoUT system parameters, such as the number of users, activation probability and type of water medium. The presented conclusions provide valuable insights into the design of an SA-based solution for IoUT communications. © 2023 IEEE.

关键词： Signal to noise ratio

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Design & Business Modelling of An Innovative Energy Storage Unit combined with Supercapacitor & Capacitor Bank for MagLev Piezoelectric Wind Turbine 7

Design & Business Modelling of An Innovative Energy Storage ...

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7th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2023

作者： Khan, Md Shahrukh Adnan Chew, Kristin Kabir, Md. Ashraful Islam, Muhammad Jahirul Aziz, Abid Vaithilingam, Chockalingam Aravind Khatun, Sufia Chua, Kein Huat Kamal, Ainun Uttara University Electrical & Electronic Engineering Dhaka Bangladesh Senior Custom Switchboard Estimator Schneider Electric Sydeny Australia Canadian University of Bangladesh Computer Science and Engineering Dhaka Bangladesh Matribhumi Real Estate Matribhumi Group Dhaka Bangladesh Uttara University Fintech Research Group Dhaka Bangladesh Taylor's University School of Engineering Subang Jaya Malaysia Canadian University of Bangladesh Electrical & Electronic Engineering Dhaka Bangladesh Universiti Tunku Abdul Rahman Faculty of Engineering and Sciene Kajang Malaysia Canadian University of Bangladesh Department of Business Administration Dhaka Bangladesh

ISBN: (纸本)9798350305517

This research provides a thorough description of the original research on developing, evaluating, and putting into practice an energy harvesting system that operates under ambient settings using a Charging bank combined of Supercapacitor, Capacitor and batteries adopted to piezoelectric transducer integrated Vertical Axis Wing Turbine. This research intends to investigate alternate energy-generating techniques in order to satisfy the rising need for power sources brought on by the quick development of electronic gadgets. The actual results of this study definitely show that using a capacitor bank significantly increases the output of piezoelectric transducers, leading to a noticeably more effective supercapacitor bank charging process. © 2023 IEEE.

关键词： Piezoelectricity

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An Augmented Reality Technology in Indoor Navigation for Smart Museum Using Bluetooth Low Energy Communication

An Augmented Reality Technology in Indoor Navigation for Sma...

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International Conference on ICT For Smart Society (ICISS)

作者： Dewi Tresnawati Asri Mulyani Cepi Nugraha Leni Fitriani Nina Lestari Dani Nugraha Department of Computer Science Institut Teknologi Garut Garut Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Sangga Buana Bandung Indonesia Division of IT Digital Transformation Darma Henwa Tbk Jakarta Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Large buildings like museum generally have multiple rooms, necessitating efficient directional information services to ensure visitors receive accurate location details. However, traditional information services often fail to convey the necessary information effectively. Indoor navigation addresses this issue by providing real-time navigation within rooms or spaces, identifying the position of objects or people. This study aims to enhance indoor navigation by implementing smart technology, enabling users to locate rooms within large buildings quickly. The application developed utilizes Augmented Reality (AR) technology, interfaced with Bluetooth Low Energy (BLE) signals emitted from an ESP32 Microcontroller, serving as location points. The methodology adopted in this study follows the Multimedia Development Life Cycle, encompassing six stages: Concept, Design, Material Collecting, Assembly, Testing, and Distribution. The results demonstrate the successful integration of AR technology in indoor navigation, using microcontrollers as location markers and BLE for seamless communication between the AR interface and microcontroller. This smart technology application significantly improves user experience by providing intuitive and accurate indoor navigation.

关键词： Accuracy Microcontrollers Indoor navigation Buildings Prototypes Information services Museums User experience Bluetooth Low Energy Augmented reality

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Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances

arXiv

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arXiv 2024年

作者： Lu, Ke Li, Dongjun Wang, Qun Yang, Kaidi Zhao, Lin Song, Ziyou Department of Mechanical Engineering National University of Singapore Singapore117575 Singapore School of Automation Science and Engineering South China University of Technology Guangzhou510641 China Department of Civil and Environmental Engineering National University of Singapore Singapore117576 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore119077 Singapore

This paper presents a safe learning-based ecodriving framework tailored for mixed traffic flows, which aims to optimize energy efficiency while guaranteeing safety during real-system operations. Even though reinforcement learning (RL) is capable of optimizing energy efficiency in intricate environments, it is challenged by safety requirements during the training process. The lack of safety guarantees is the other concern when deploying a trained policy in real-world application. Compared with RL, model predicted control (MPC) can handle constrained dynamics systems, ensuring safe driving. However, the major challenges lie in complicated eco-driving tasks and the presence of disturbances, which respectively challenge the MPC design and the satisfaction of constraints. To address these limitations, the proposed framework incorporates the tube-based enhanced MPC (RMPC) to ensure the safe execution of the RL policy under disturbances, thereby improving the control robustness. RL not only optimizes the energy efficiency of the connected and automated vehicle in mixed traffic but also handles more uncertain scenarios, in which the energy consumption of the human-driven vehicle and its diverse and stochastic driving behaviors are considered in the optimization framework. Simulation results demonstrate that the proposed algorithm, compared with RMPC technique, shows an average improvement of 10.88% in holistic energy efficiency, while compared with RL algorithm, it effectively prevents inter-vehicle collisions. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

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Energy Consumption Analysis of Elliptic Curve Cryptography Middleware Broker for MQTT Application in IoT Systems 24

Energy Consumption Analysis of Elliptic Curve Cryptography M...

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24th International Arab Conference on Information Technology, ACIT 2023

作者： Yusoff, Zainatul Yushaniza Mohamed Ishak, Mohamad Khairi Rahim, Lukman Ab Ammar, Khalid Yusof, Shafiz Affendi Mohd School of Electrical and Electronic Engineering Universiti Sains Malaysia Penang Nibong Tebal Malaysia Department of Computer Engineering Ajman University United Arab Emirates Universiti Sains Malaysia Penang Nibong Tebal Malaysia Faculty of Science and It Universiti Teknologi Petronas Seri Iskandar Perak Malaysia Ajman University United Arab Emirates

ISBN: (纸本)9798350384307

The Internet of Things(IoT)has become an expansion of connected smart devices from small sensors to complex fog and cloud nodes and various network technologies and communication protocols. Devices, including Intelligent Home Health Care, will infiltrate our lives in various application areas. The Internet of Things provides what is in the physical world the ability to interact with the Internet. However, due to their vulnerability, these connected devices offer new security challenges that can be overcome by performing strong validation and access control patterns. In this article, we propose to monitor and allow the use of middleware broker platforms, work, and resources effectively and use ECC for asymmetric monitoring. The security analysis demonstrates a robust resistance to common attacks, bolstered by the fact that each device operates within the energy constraints of just 4mJ, as stipulated by the original protocol. © 2023 IEEE.

关键词： Authentication Confidentiality ECC Integrity Internet of Things Lightweight cryptography MQTT Security

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A Novel Hybrid Evolutionary Mating Algorithm for Covid19 Confirmed Cases Prediction based on Vaccination

A Novel Hybrid Evolutionary Mating Algorithm for Covid19 Con...

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Next-Generation Computing, IoT and Machine Learning (NCIM), International Conference on

作者： Marzia Ahmed Ahmad Johari Mohamad Mostafijur Rahman Mohd Herwan Sulaiman Mohammod Abul Kashem Faculty of Electrical & Electronics Engineering Technology Universiti Malaysia Pahang (UMP) Pahang Malaysia Department of Software Engineering Daffodil International university Dhaka Bangladesh Department of Computer Science and Engineering Green University of Bangladesh Department of Computer Science and Engineering DUET Gazipur Bangladesh

Microorganisms may cause illness when they enter the body, multiply, and spread to other parts. The rapid spread of COVID-19 to neighboring countries is examined in this research. Anticipating a positive COVID-19 occurrence helps in determining risks and creating countermeasures. As a result, developing robust mathematical models with small error margins for predictions is crucial. Based on these findings, a combined method of evaluating confirmed cases of COVID-19 with universal immunization is recommended. First, the best hyperparameter values of the RBF kernel-based LSSVM (least square support vector machine) were determined using the most recent Evolutionary Mating Algorithm (EMA). After that, LSSVM will complete the task of prediction. This hybrid method has been utilized for time series forecasting in Malaysia since the country's immunization program against COVID-19 got underway. We evaluate our results next to those of well-known methodologies in nature-inspired metaheuristics.

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Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories

arXiv

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arXiv 2024年

作者： Yang, Ning Chen, Shuo Zhang, Haijun Berry, Randall The Institute of Automation Chinese Academy of Sciences Beijing100190 China The Department of Electrical and Electronic Engineering Imperial College London LondonSW72BX United Kingdom The Department of Computing and Communication Engineering Beijing University of Science and Technology Beijing100083 China The Department of Electrical and Computer Engineering Northwestern University Chicago60208 United States

Mobile Edge Computing (MEC) broadens the scope of computation and storage beyond the central network, incorporating edge nodes close to end devices. This expansion facilitates the implementation of large-scale "connected things" within edge networks. The advent of applications necessitating real-time, high-quality service presents several challenges, such as low latency, high data rate, reliability, efficiency, and security, all of which demand resolution. The incorporation of reinforcement learning (RL) methodologies within MEC networks promotes a deeper understanding of mobile user behaviors and network dynamics, thereby optimizing resource use in computing and communication processes. This paper offers an exhaustive survey of RL applications in MEC networks, initially presenting an overview of RL from its fundamental principles to the latest advanced frameworks. Furthermore, it outlines various RL strategies employed in offloading, caching, and communication within MEC networks. Finally, it explores open issues linked with software and hardware platforms, representation, RL robustness, safe RL, large-scale scheduling, generalization, security, and privacy. The paper proposes specific RL techniques to mitigate these issues and provides insights into their practical applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Fault Detection and Mitigation in Vehicle Platooning

Fault Detection and Mitigation in Vehicle Platooning

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Najeebuddin Ahmed Hassan Naser Amir Ameli Faculty of Engineering Lakehead University Thunder Bay Canada Department of Software Engineering Lakehead University Thunder Bay Canada Department of Electrical and Computer Engineering Lakehead University Thunder Bay Canada

This paper addresses the challenges posed by faults in the complex systems of autonomous vehicles within vehicle platoons. It presents a state-space model tailored for vehicle platoons, incorporating an Unknown Input Observer (UIO) to estimate internal states for each vehicle. By monitoring discrepancies between measured and estimated states, the framework effectively detects faults affecting a vehicle's position, velocity, and acceleration, often stemming from malfunctions in its control and navigation components. The paper also introduces fault detection and identification UIOs to pinpoint faulty parameters and estimate associated fault inputs. To validate its effectiveness, the proposed method undergoes MATLAB simulations across diverse scenarios, confirming its capability to mitigate faults within the vehicle platoon.

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DGONN: Depthwise Dynamic Graph Overparameterized Neural Network for 3D Point Cloud Object Recognition

DGONN: Depthwise Dynamic Graph Overparameterized Neural Netw...

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IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications

作者： Oddy Virgantara Putra Ardyono Priyadi Kohichi Ogata Eko Mulyanto Yuniarno Mauridhi Hery Purnomo Department of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan Department of Computer Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350322996

ISBN: (纸本)9798350323009

Rapid advancement in 3D point cloud object recognition is crucial for robotics, autonomous driving, and augmented reality applications. The traditional methods, including PointNet and its successors, though effective in handling unordered point cloud data, need help capturing local structures accurately and efficiently. This paper introduces a novel architecture, the Depthwise Dynamic Graph Overparameterized Neural Network (DGONN), which enhances point cloud object recognition by integrating graph-based features with overparameterized networks. Our method leverages local geometric formations through a neighborhood graph. It performs operations similar to convolutions, utilizing edge convolution (EdgeConv) and depthwise overparameterized convolution (DO-Conv) for dynamic graph updates and efficient feature representation. The proposed DGONN architecture dynamically updates the graph structure with each layer, allowing for adaptive learning and improved performance in 3D object recognition tasks. Through extensive experiments, DGONN demonstrated superior performance over state-of-the-art methods across various metrics on the ModelNet40 and ScanObjectNN datasets with accuracy scores of 92.9% and 78.3%, respectively. This performance highlights its effectiveness in preserving dense spatial relationships and patterns within point cloud data. Future work focuses on making the system faster and more efficient by improving the model’s ability to work well with different types of point cloud data, even in challenging conditions like outdoor scenes, and incorporating new features like texture.

关键词： Point cloud compression Measurement Three-dimensional displays Neural networks Virtual environments computer architecture Object recognition

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High Quality Factor Microcavity for Van der Waals Semiconductor Polaritons Using a Transferrable Mirror( vol 11 , 2201440 , 2023 )

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ADVANCED OPTICAL MATERIALS 2023年第23期11卷

作者： Paik, Eunice Y. Zhang, Long Hou, Shaocong Zhao, Haonan Chou, Yu-Hsun Forrest, Stephen R. Deng, Hui Department of Physics University of Michigan Ann Arbor Michigan USA Department of Physics University of Michigan Ann Arbor Michigan USA Department of Physics Xiamen University Xiamen China School of Electrical Engineering and Automation Wuhan University Wuhan China Department of Electrical and Computer Engineering University of Michigan Ann Arbor Michigan USA Department of Photonics National Cheng Kung University Tainan City Taiwan Departments of Electrical and Computer Engineering Physics and Materials Science and Engineering University of Michigan Ann Arbor Michigan USA

Semiconductor microcavities with a high quality‐factor are an important component for photonics research and technology, especially in the strong coupling regime. While van der Waals semiconductors have emerged as an interesting platform for photonics due to their strong exciton–photon interaction strength and engineering flexibility, incorporating them in photonic devices requires heterogeneous integration and remains a challenge. This study demonstrates a method to assemble high quality factor microcavities for van der Waals materials, using high reflectance top mirrors which, similar to van der Waals materials themselves, can be nondestructively and reliably peeled off the substrate and transferred onto the rest of the device. Microcavities are created with quality factors consistently above 2000 and up to 11000 ± 800; and the strong coupling regime is demonstrated. The method can be generalized to other types of heterogeneously integrated photonic structures and will facilitate research on cavity quantum electrodynamic and photonic systems using van der Waals materials.

关键词： distributed Bragg reflectors exciton–polaritons microcavity transition metal dichalcogenides van der Waals materials

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