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2024 International conference on Communications control and Computing Technologies for Smart Grids

作者： Guo, Xiaoyu Qu, Yanfeng Chen, Gong Jin, Dong Univ Arkansas Elect Engn & Comp Sci Fayetteville AR USA Illinois Inst Technol Comp Sci Chicago IL USA

ISBN: (纸本)9798350318562;9798350318555

Phasor measurement unit (PMU) networks deliver accurate and timely measurements, which is essential for managing today's electric power systems. To ensure data quality and enhance the cyber-resilience of PMU networks against malicious attacks and data errors, this study presents an online PMU missing data recovery scheme by leveraging P4 programmable switches. The data plane incorporates a customized PMU protocol parser that abstracts the necessary payload data for recovery. Recovery processes are executed in the control plane using a pre-trained machine learning model. Both traditional and advanced ML models, such as transformer and TimeGPT, are explicitly employed for data prediction. This approach ensures rapid and precise data recovery. performance evaluations focus on recovery speed and accuracy, using a real dataset from a campus microgrid. With 20% missing PMU data, the mean absolute percentage error for voltage magnitude is 0.0384%, and the phase angle error discrepancy is approximately 0.4064%.

关键词： Phasor Measurement Unit Machine Learning Programmable network P4 Smart Grid

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IoDAPM: A Reinforcement Learning Approach for Dynamic Assignment of Protection Mechanisms in IoD 23

IoDAPM: A Reinforcement Learning Approach for Dynamic Assign...

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26th ACM International conference on Modelling, Analysis, and Simulation of Wireless and Mobile systems (MSWiM)

作者： Svaigen, Alisson R. Boukerche, Azzedine Ruiz, Linnyer B. Loureiro, Antonio A. F. Univ Ottawa PARADISE Res Lab Ottawa ON Canada Univ Fed Minas Gerais DCC Belo Horizonte MG Brazil Univ Estadual Maringa Manna Res Grp Maringa Parana Brazil

ISBN: (纸本)9798400703669

Location Privacy Protection Mechanisms (LPPMs) have been designed to enhance privacy in the internet of Drones (IoD), however, they present suitable privacy levels only in specific network conditions. Also, they can lead to a lack of quality of Service (QoS) if applied in unfavorable conditions. Thus, the dynamic assignment of the most suitable LPPM, given the IoD conditions, is a significant challenge. Reinforcement Learning (RL) represents a useful concept to handle this problem, given its exploratory characteristics and being able to enhance the knowledge about network dynamics. In this study, we propose IoDAPM, an RL-based approach for the Dynamic Assignment of Protection Mechanisms in IoD. Through simulations, we extensively trained the RL-based model, exploring the possible IoD network conditions. With this model, we carried out a comparative evaluation of existing LPPMs. The results highlighted that IoDAPM outperforms the compared mechanisms considering the QoS, providing enhanced performance regarding location privacy, energy efficiency, and flight delay.

关键词： internet of Drones Location Privacy Reinforcement Learning

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Ensuring Fruits and Vegetables Freshness in Sustainable Agricultural Supply Chain networks: A Deep Learning Approach 43rd

Ensuring Fruits and Vegetables Freshness in Sustainable Agri...

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43rd IFIP WG 5.7 International conference on Advances in Production Management systems (APMS)

作者： Bahaddou, Youness Tamym, Lahcen Benyoucef, Lyes Aix Marseille Univ Univ Toulon LIS CNRS Marseille France

ISBN: (纸本)9783031716317;9783031716294;9783031716287

Ensuring fruits and vegetables' freshness within a sustainable agricultural supply chain network (SASCN) is a critical and multifaceted challenge. This demands comprehensive solutions that integrate new technologies, sustainability philosophy, and effective management practices, to name a few. In this regard, computer vision (CV) and machine learning/deep learning (ML/DL) have increasingly been utilized in various sustainable agricultural areas, demonstrating significant efficacy in image analysis and processing. To this end, this research study proposes a novel approach leveraging advanced Deep learning techniques, including convolutional neural network (CNN) for fruit and vegetable quality detection and assessment throughout a SASCN. Therefore, an approach based on CNN is developed, utilizing a varied dataset that includes several types of fruit like Apples, Oranges, Bananas, and Grapes, alongside a single type of vegetable, namely Bitter-gourd. Notably, the proposed approach takes into consideration criteria, namely sustainability, and quality management thereby facilitating a holistic approach to fruit and vegetable quality control. The significant finding results in this study demonstrate the applicability of the developed approach for SASCN. After conducting thorough experimentation and assessment, the effectiveness of the developed approach attained an accuracy rate of 98.39%, indicating its high performance.

关键词： Deep Learning Convolutional Neural network (CNN) Computer Vision quality assessment Fruits and Vegetables

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Analysis of Real-World LoRaWAN network performance Across Outdoor and Indoor Scenarios 11

Analysis of Real-World LoRaWAN Network Performance Across Ou...

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11th IEEE International conference on systems and control, ICSC 2023

作者： Alkhazmi, Esmaeil H. Elkawafi, Salma M. Aldarrat, Assem A. Abbas, Mohammed A. Abubakr, Hussameldin Shamatah, Hana A. University of Benghazi Electrical and Electronics Engineering Department Benghazi Libya

ISBN: (纸本)9798350304886

With the rapid expansion of the internet of Things (IoT) technologies, low-power wide-area networks (LPWANs) have emerged as effective solutions for long-range wireless connectivity. Long Range Wide Area network (LoRaWAN) is a promising LPWAN architecture that enables robust, energy-efficient communication for distributed IoT devices. This paper presents an experimental performance analysis of a LoRaWAnnetwork deployed in urban and suburban environments across Benghazi, Libya. The results demonstrate LoRaWAN's capabilities in terms of reliability, transmission range, and adaptation to varied conditions. Packets were transmitted between LoRa32 nodes using different spreading factor (SF) configurations. Key performance metrics, including packet error rate, received signal strength indicator (RSSI), and signal-to-noise ratio (SNR), were measured across outdoor and indoor scenarios. The findings showcase LoRaWAN's resilience to channel noise and interference, achieving minimal packet loss over several kilometers. Furthermore, tuning parameters, such as the spreading factor, allow effective tradeoffs between data rate, communication range, and power consumption. This research validates LoRaWAnas a versatile IoT networking solution and offers insights to inform optimal deployment in diverse real-world settings. © 2023 IEEE.

关键词： internet of things

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A Comprehensive Analysis of Applications in internet of Things networks in 5G and 6G 2

A Comprehensive Analysis of Applications in Internet of Thin...

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2nd International conference on Computer, Communication and control, IC4 2024

作者： Rawat, Bhupender Singh Srivastava, Animesh Shrivastava, Vivek Singh, Gulbir Garg, Navin Coer University College of Smart Computing Roorkee India Graphic Era Hill University Department of Computer Science & Engineering Dehradun India Mmict&bm Haryana Ambala India Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350387933

This paper survey explores the 5G and 6G IoT networks in wireless networks, focusing on their applications in various domains such as healthcare, smart cities, agriculture, industrial automation, transportation, and environmental monitoring. The study provides a comprehensive description of the mutually beneficial association between IoT and 5G/6G networks, highlighting how the integration of IoT with 5G technology can enhance network performance and address *** goal of this survey is to help readers gain a firmer grasp of the technical state of 5G IoT, as well as the milestones and key performance indicators that will need to be achieved to bring in 6G IoT. © 2024 IEEE.

关键词： 5G mobile communication systems

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performance Analysis of Multipath TCP Congestion control Algorithms

Performance Analysis of Multipath TCP Congestion Control Alg...

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International conference on Communication systems and network Technologies (CSNT)

作者： Subhra Priyadarshini Biswal Akash Chatterjee Khair Alanam Sanjeev Patel Department of Computer Science and Engineering National Institute of Technology Rourkela Odisha India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

In modern high-speed networks, providing reliable and high-quality internet services is essential. However, maintaining consistent network performance in dynamic environments with varying scenarios presents significant challenges. To address these, Multipath TCP (Transmission control Protocol) offers a viable solution by aggregating multiple network paths, resulting in improved bandwidth utilization, higher throughput, and reduced delay. This approach overcomes the limitations of traditional single-path TCP by enhancing responsiveness, friendliness, and reducing window oscillation. Moreover, MPTCP incorporates congestion control mechanisms that couple several subflows, ensuring efficient traffic distribution across multiple paths, thereby improving overall network performance and fairness. In this paper, we analyze the performance of LIA (Linked Increases Algorithm), OLIA (Opportunistic Linked Increases Algorithm), and BALIA (Balanced Linked Adaptation) congestion control algorithms using the ns-3 network simulator. The results show that BALIA achieves 21% higher throughput compared to LIA.

关键词： Protocols High-speed networks Web and internet services Bandwidth Throughput Delays performance analysis MPTCP Reliability Oscillators

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Data Driven Neural Speech Enhancement for Smart Healthcare in Consumer Electronics Applications

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2024年第2期70卷 4828-4838页

作者： Paikrao, Pavan D. Mukherjee, Amrit Ghosh, Uttam Goswami, Pratik Novak, Milan Jain, Deepak Kumar Al-Numay, Mohammed S. Narwade, Pradeep Dr DY Patil Inst Technol Dept Elect & Telecommun Engn Pune 411018 India South Bohemia Univ Ceske Budejovice Fac Sci Comp Sci Dept Ceske Budejovice 37005 Czech Republic Meharry Med Coll CS & DS Dept Nashville TN 37208 USA Yeungnam Univ Sch Comp Sci & Engn Gyongsan 38541 South Korea Dalian Univ Technol Key Lab Intelligent Control & Optimizat Ind Equipm Minist Educ Dalian 116024 Peoples R China Symbiosis Int Univ Symbiosis Inst Technol Pune 412115 India King Saud Univ Coll Engn Elect Engn Dept Riyadh 11421 Saudi Arabia Shri Guru Gobind Singhji Inst Engn & Technol Dept Elect & Telecommun Engn Nanded 431606 India

This paper presents the practical response and performance-aware development of online speech enhancement from a consumer electronic perspective. To improve the efficiency of human-machine interaction, speech can play a vital role as a transmission medium on the internet of Medical Things (IoM). However, some intelligent speech recognition systems cannot preserve the confidentiality of speech data. Additionally, the preservation of privacy is onerous, especially for model training and speech recognition in real-time. The recent development of big data-oriented wireless technologies associated with edge computing, interconnected devices of the internet of Medical Things (IoMT), and big data analytics has great demand for connected human-machine interaction for many applications like automated cars, health monitoring, and consumer personal health care monitoring systems. Although big data-oriented wireless technologies serve these applications, the challenge remains of ignoring emotional care. This paper starts by explaining how to make a neural network-based architecture that can improve the speech of multichannel first-order Ambisonics mixtures and lower the need for human intervention through ambient intelligence (AmI). This will make the system work better overall in medical situations. Second, we demonstrate the effectiveness of different noise estimation techniques on proposed modulation domain processing (MDP) applications in smart hospitals, including electronic medical documentation, disease diagnosis, and evaluation. The proposed approach outperforms the enhancement of the conventional modulation domain in the cortex with several objective evaluation parameters such as Log Likelihood Ratio (LLR), Weighted Spectral Slope (WSS), Perceptual Evaluation of Speech quality (PESQ), Csig and segmental (SNR seg.) Different noise estimators are used to figure out what effect the system has on different spectral modification parameters, like the over-subtraction factor

关键词： Medical services Speech enhancement Speech recognition Consumer electronics Monitoring Noise measurement Real-time systems Consumer healthcare system speech recognition ambient intelligence big data computing

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A Measurement-Derived Functional Model for the Interaction Between Congestion control and QoE in Video Conferencing 24th

A Measurement-Derived Functional Model for the Interaction B...

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24th Annual International conference on Passive and Active Measurement (PAM)

作者： He, Jia Ammar, Mostafa Zegura, Ellen Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9783031284854;9783031284861

Video Conferencing Applications (VCAs) that support remote work and education have increased in use over the last two years, contributing to internet bandwidth usage. VCA clients transmit video and audio to each other in peer-to-peer mode or through a bridge known as a Selective Forwarding Unit (SFU). Popular VCAs implement congestion control in the application layer over UDP and accomplish rate adjustment through video rate control, ultimately affecting end user quality of Experience (QoE). Researchers have reported on the throughput and video metric performance of specific VCAs using structured experiments. Yet prior work rarely examines the interaction between congestion control mechanisms and rate adjustment techniques that produces the observed throughput and QoE metrics. Understanding this interaction at a functional level paves the way to explain observed performance, to pinpoint commonalities and key functional differences across VCAs, and to contemplate opportunities for innovation. To that end, we first design and conduct detailed measurements of three VCAs (WebRTC/Jitsi, Zoom, BlueJeans) to develop understanding of their congestion and video rate control mechanisms. We then use the measurement results to derive our functional models for the VCA client and SFU. Our models reveal the complexity of these systems and demonstrate how, despite some uniformity in function deployment, there is significant variability among the VCAs in the implementation of these functions.

关键词： Video conferencing

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quality of control Based Resource Dimensioning for Collaborative Edge Robotics 22

Quality of Control Based Resource Dimensioning for Collabora...

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22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Roy, Neelabhro Dhullipalla, Mani H. Sharma, Gourav Prateek Dimarogonas, Dimos V. Gross, James School of Electrical Engineering and Computer Science Digital Futures Research Center Kth Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9798331508050

With the increasing focus on flexible automation, which emphasizes systems capable of adapting to varied tasks and conditions, exploring future deployments of cloud and edge-based network infrastructures in robotic systems becomes crucial. This work, examines how wireless solutions could support the shift from rigid, wired setups toward more adaptive, flexible automation in industrial environments. We provide a quality of control (QoC) based abstraction for robotic workloads, parameterized on loop latency and reliability, and jointly optimize system performance. The setup involves collaborative robots working on distributed tasks, underscoring how wireless communication can enable more dynamic coordination in flexible automation systems. We use our abstraction to optimally maximize the QoC ensuring efficient operation even under varying network conditions. Additionally, our solution allocates the communication resources in time slots, optimizing the balance between communication and control costs. Our simulation results highlight that minimizing the delay in the system may not always ensure the best QoC but can lead to substantial gains in QoC if delays are sometimes relaxed, allowing more packets to be delivered reliably. © 2025 IEEE.

关键词： Industrial robots

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Online harmonic extraction and synchronization algorithm based control for unified power quality conditioner for microgrid systems

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ENERGY REPORTS 2022年 8卷 962-971页

作者： Hasan, Kamrul Othman, Muhammad Murtadha Meraj, Sheikh Tanzim Rahman, Nor Farahaida Abdul Noor, Siti Zaliha Mohammad Musirin, Ismail Abidin, Izham Zainal Univ Teknol MARA Solar Res Inst SRI Sch Elect Engn Coll Engn Studies Shah Alam 40450 Selangor Malaysia Univ Teknol PETRONAS Dept Elect & Elect Engn Seri Iskandar 32610 Perak Malaysia Univ Tenaga Nas Coll Engn Dept Elect Power Engn Jalan IKRAM UNITEN Kajang 43000 Selangor Malaysia

This manuscript proposes an Adaptive Linear Neural network (ADALINE) based control for the unified power quality conditioner to protect the critical loads from voltage related power quality problems and mitigate the current related power quality problems produced by nonlinear loads. Due to parallel computing feature and simple algorithm, ADALINE is utilized widely in parameter estimation. In this manuscript, unified ADALINEs based current harmonic extractor for the shunt active power filter is utilized, and an ADALINE based control technique is utilized to produce reference voltages for load voltage compensation. Due to ADALINE control, the necessity of a phase locked loop and conventional filters are omitted, therefore, enabling the system to extract the fundamental components more accurately. Besides, the ability of self-regulating transition from islanded mode to grid-connected mode has ensured that uninterrupted power supply is provided to the critical loads. The system performance is validated through simulation results utilizing MATLAB-Simulink software considering several dynamic conditions, namely unbalanced grid voltage, self-regulating transition, and grid unavailability. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/). Peer-review under responsibility of the scientific committee of the 8th International conference on Power and Energy systems Engineering, CPESE 2021.

关键词： Battery energy storage Microgrid Neural network Power quality Solar photovoltaic Unified power quality conditioner

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