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iDrone: IoT-Enabled Unmanned Aerial Vehicles for Detecting Wildfires Using Convolutional Neural Networks

SN computer Science 2022年第3期3卷 242页

作者： Sethuraman, Sibi Chakkaravarthy Tadkapally, Gaurav Reddy Mohanty, Saraju P. Subramanian, Anitha School of Computer Science and Engineering and Center of Excellence in Artificial Intelligence and Robotics (AIR) VIT-AP University Amaravati India Department of Computer Science and Engineering University of North Texas Denton 76207 TX United States School of Electronics Engineering and Center of Excellence in Artificial Intelligence and Robotics (AIR) VIT-AP University Amaravati India

The rise of global temperatures, over the past few decades, has disrupted the usual balance of nature. As a result of increasing temperatures, wildfires have destroyed millions of acres of land, thousands of structures, and homes. The pollution and toxic gases produced by the wildfires are carried out to thousands of miles, thus threatening the lives all around the world. Most wildfires occur due to anthropogenic factors, which cannot be predicted solely based on climate conditions. Henceforth, to detect wildfires before escalating, we propose iDrone, which is a wildfire detection system equipped with an end-to-end CNN image classification model: XtinguishNet, trained on a wildfire imagery dataset to detect the possible flames or smokes in an image. In addition, our approach also acquires the weather data and the intensity of the fire. Contrasting with existing wildfire detection systems, our proposed solution is a fusion of the Internet of Things (IoT) and Deep Learning, aiming to provide a one-stop solution for all the needs required to minimize the damage caused by wildfires. When validated and tested using various benchmark datasets, video surveillance, iDrone acquired a high accuracy of 98.36% with the least computational power. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： CNN computer vision Deep learning Forest fires iDrone Wildfires

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Power Quality of DQ Synchronous Frame for Wind Connected to Grid 13

Power Quality of DQ Synchronous Frame for Wind Connected to ...

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13th International Conference on Power, Energy and Electrical engineering, CPEEE 2023

作者： Alarbidi, Omar Mater F Awaji, Hassan Hadi H Althobiti, Ahmad Awadh Alhussainy, Abdullah Ali Alghamdi, Sultan Ajour, M.N. Rawa, Muhyaddin Abusorrah, A.M. King Abdulaziz University Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia K. A. Care Energy Research and Innovation Center King Abdulaziz University Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia King Abdulaziz University K. A. Care Energy Research and Innovation Center Smart Grids Research Group Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering Jeddah21589 Saudi Arabia King Abdulaziz University Smart Grids Research Group Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer Engineering 21589 Jeddah Saudi Arabia

ISBN: (纸本)9781665490146

A wind turbine in wind energy conversion systems (WECS) captures a portion of the wind energy. It converts it to mechanical energy through a dynamic interaction with the electrical generator, transforming this mechanical energy into electrical energy. Therefore, wind turbine dynamics are crucial when researching and developing the whole WECS. It is highly desirable to study the behavior of wind energy and monitor the impact on power quality and short circuit level. In this study, a wind turbine using a permanent magnet synchronous machine (PMSM) simulation system is designed, simulated, cases study is discussed. The PMSM is torque-controlled using the field orientation method. A three-phase IGBT inverter with closed loop current PI-controllers powers the PMSM. The study and control system are executed on MATLAB SIMULINK. © 2023 IEEE.

关键词： Wind turbines

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PUF-Based Privacy-Preserving Simultaneous Authentication Among Multiple Vehicles in VANET

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IEEE Transactions on Vehicular Technology 2024年第5期73卷 6727-6739页

作者： Awais, Syed Muhammad Yucheng, Wu Mahmood, Khalid Akram, Muhammad Wahid Hussain, Shafiq Das, Ashok Kumar Park, Youngho Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin64002 Taiwan University of Lahore Department of Software Engineering Punjab Lahore54590 Pakistan University of Sahiwal Department of Computer Science Punjab Sahiwal57000 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Telangana Hyderabad500032 India Kyungpook National University School of Electronics Engineering Daegu41566 Korea Republic of

The intellectual and immense attainment of a smart city and auto-mobile vehicles are gradually growing. This growth drives Vehicular Ad-Hoc Network (VANET), a broadly operated complex network for inter-vehicular transmission to acquire information relevant to the vehicle location, road condition, traffic congestion, and speed. Generally, this information is procured through an open-source communication, which is susceptible to various security threats. In broad terms, the privacy of data in VANET is considered an imperative task. In this regard, many authentication protocols are formerly initiated for VANET. Most of these protocols are precarious owing to eavesdropping, replay, and impersonation attacks, etc. Furthermore, most existing protocols operates on enormous communication and computation rate, which turns them inadequate for VANET. This paper exhibits a lightweight privacy-preserving authentication protocol for n number of vehicles in VANET using the physical unclonable function (PUF) technique, and offers efficient and secure communication via public channels. Moreover, we evaluate our protocol formally and informally, showing that it is scalable, lightweight, and safe compared to formerly protocols. The rate of computation and communication is less than most related protocols. We also simulate the proposed scheme using the NS-3 simulator to measure its various network performance parameters. As a result, it is apparent through the beheld statistics that the presented protocol is beyond practical, efficient, and reliable for the secure dissemination of information in VANET. © 1967-2012 IEEE.

关键词： Vehicular ad hoc networks

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Cache Memory Design for Single Bit Architecture with Different Sense Amplifiers

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computers, Materials & Continua 2022年第11期73卷 2313-2331页

作者： Reeya Agrawal Anjan Kumar Salman A.AlQahtani Mashael Maashi Osamah Ibrahim Khalaf Theyazn H.H.Aldhyani VLSI Center of Excellence GLA UniversityMathura281406India Computer Engineering Department Research Chair of New Emerging Technologies and 5G Networks and BeyondCollege of Computer and Information SciencesKing Saud UniversitySaudi Arabia Software Engineering Department King Saud UniversityRiyadh11543Saudi Arabia Al-Nahrain University Al-Nahrain Nano-Renewable Energy Research CenterBaghdadIraq Applied College in Abqaiq King Faisal UniversityAl-Ahsa31982Saudi Arabia

Most modern microprocessors have one or two levels of on-chip caches to make things run faster,but this is not always the *** of the time,these caches are made of static random access memory *** take up a lot of space on the chip and use a lot of electricity.A lot of the time,low power is more important than several *** is true for phones and *** memory design for single bit architecture consists of six transistors static random access memory cell,a circuit of write driver,and sense amplifiers(such as voltage differential sense amplifier,current differential sense amplifier,charge transfer differential sense amplifier,voltage latch sense amplifier,and current latch sense amplifier,all of which are compared on different resistance values in terms of a number of transistors,delay in sensing and consumption of *** conclusion arises that single bit six transistor static random access memory cell voltage differential sense amplifier architecture consumes 11.34μW of power which shows that power is reduced up to 83%,77.75%reduction in the case of the current differential sense amplifier,39.62%in case of charge transfer differential sense amplifier and 50%in case of voltage latch sense amplifier when compared to existing latch sense amplifier ***,power reduction techniques are applied over different blocks of cache memory architecture to optimize *** single-bit six transistors static random access memory cell with forced tack technique and voltage differential sense amplifier with dual sleep technique consumes 8.078μW of power,i.e.,reduce 28%more power that makes single bit six transistor static random access memory cell with forced tack technique and voltage differential sense amplifier with dual sleep technique more energy efficient.

关键词： Current differential sense amplifier(CDSA) voltage differential sense amplifier(VDSA) voltage latch sense amplifier(VLSA) current latch sense amplifier(CLSA) charge-transfer differential sense amplifier(CTDSA) new emerging technologies

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Position Control of Flexible Joint Carts Using Adaptive Generalized Dynamics Inversion

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computers, Materials & Continua 2022年第3期70卷 4691-4705页

作者： Ibrahim M.Mehedi Mohd Heidir Mohd Shah Soon Xin Ng Abdulah Jeza Aljohani Mohammed El-Hajjar Muhammad Moinuddin Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia Next Generation Wireless Research Group University of SouthamptonUK

This paper presents the design and implementation of Adaptive Generalized Dynamic Inversion(AGDI)to track the position of a Linear Flexible Joint Cart(LFJC)system along with vibration suppression of the flexible *** proposed AGDI control law will be comprised of two control *** baseline(continuous)control law is based on principle of conventional GDI approach and is established by prescribing the constraint dynamics of controlled state variables that reflect the control *** control law is realized by inverting the prescribed dynamics using dynamically scaledMoore-Penrose generalized *** boost the robust attributes against system nonlinearities,parametric uncertainties and external perturbations,a discontinuous control law will be augmented which is based on the concept of sliding mode *** discontinuous control law,the sliding mode gain is made adaptive in order to achieve improved tracking performance and chattering *** closed-loop stability of resultant control law is established by introducing a positive define Lyapunov candidate function such that semi-global asymptotic attitude tracking of LFJC system is *** computer simulations followed by experimental investigation will be performed on Quanser’s LFJC system to authenticate the feasibility of proposed control approach for its application to real world problems.

关键词： Adaptive control generalized dynamic inversion moore-penrose generalized inverse sliding mode control lyapunov stability semi-global asymptotic stability

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Improving the Educational Value of Operating Systems 23

Improving the Educational Value of Operating Systems

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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Sava, Cezar Deaconescu, Razvan Kroning, Martin Monti, Antonello Turcanu, Dinu POLITEHNICA of Bucharest Computer Science and Engineering Department Bucharest Romania RWTH Aachen University Institute for Automation of Complex Power Systems Aachen Germany Fraunhofer Center Digital Energy Fraunhofer FIT Aachen Germany University of Moldova Department of Software Engineering and Automatics Technical Chişinǎu Moldova

ISBN: (纸本)9798331540388

Educational operating systems are crucial for facilitating learning in the digital age, as they exist at the intersection of technology and education. While their technical role is well understood, improving their educational value requires enhancing traditional approaches. This paper explores ways to enrich educational operating systems not just through technological advancement, but also by integrating pedagogical principles. In an ever-changing world, the need for an adaptive and responsive educational operating system to meet diverse student needs is crucial. Through case studies, we analyze how design, interactivity, and accessibility can transform these systems into effective and appealing learning environments. We propose a series of recommendations for the future development of educational operating systems, focusing on enhancing the learning experience and promoting student autonomy, thereby offering a fresh perspective on how technology and education can blend harmoniously and efficiently. © 2024 IEEE.

关键词： Contrastive Learning

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Task Offloading and Resource Allocation in IoT Based Mobile Edge Computing Using Deep Learning

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computers, Materials & Continua 2023年第8期76卷 1463-1477页

作者： Ily s Abdullaev Natalia Prodanova KAruna Bhaskar ELaxmi Lydia Seifedine Kadry Jungeun Kim Dean of the Faculty of Economics Department of Management and MarketingFaculty of EconomicsUrgench State UniversityUrganch220100Uzbekistan Basic Department Financial Control Analysis and Audit of Moscow Main Control DepartmentPlekhanov Russian University of EconomicsMoscow117997Russia Department of Computer Science and Engineering KL Deemed to UniversityVaddeswaramGunturAndhra PradeshIndia Department of Computer Science and Engineering GMR Institute of TechnologyAndhra PradeshRajamIndia Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-based data *** city benefitted from offloading to edge *** a mobile edge computing(MEC)network in multiple *** comprise N MDs and many access points,in which everyMDhasM independent real-time *** study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization(TORA-DLSGO)*** proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,which enables an optimum offloading decision to minimize the system *** addition,an objective function is derived based on minimizing energy consumption subject to the latency requirements and restricted *** TORA-DLSGO technique uses the deep belief network(DBN)model for optimum offloading ***,the SGO algorithm is used for the parameter tuning of the DBN *** simulation results exemplify that the TORA-DLSGO technique outperformed the existing model in reducing client overhead in the MEC systems with a maximum reward of 0.8967.

关键词： Mobile edge computing seagull optimization deep belief network resource management parameter tuning

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Object Detection in Very Low-Resolution Thermal Images through a Guided-Based Super-Resolution Approach 17

Object Detection in Very Low-Resolution Thermal Images throu...

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17th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2023

作者： Rivadeneira, Rafael E. Velesaca, Henry O. Sappa, Angel Espol Polytechnic University Fiec - Cidis Guayaquil Ecuador University of Granada Software Engineering Department Granada18014 Spain Computer Vision Center Barcelona08193 Spain

ISBN: (纸本)9798350370911

This work proposes a novel approach that integrates super-resolution techniques with off-the-shelf object detection methods to tackle the problem of handling very low-resolution thermal images. The suggested approach begins by enhancing the low-resolution (LR) thermal images through a guided super-resolution strategy, leveraging a high-resolution (HR) visible spectrum image. Subsequently, object detection is performed on the high-resolution thermal image. The experimental results demonstrate tremendous improvements in comparison with both scenarios: when object detection is performed on the LR thermal image alone, as well as when object detection is conducted on the up-sampled LR thermal image. Moreover, the proposed approach proves highly valuable in camouflaged scenarios where objects might remain undetected in visible spectrum images. © 2023 IEEE.

关键词： Object recognition

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Exploiting the Potential of Self-Supervised Monocular Depth Estimation via Patch-Based Self-Distillation

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IEEE Internet of Things Journal 2025年第11期12卷 18042-18055页

作者： Yu, Ting Pan, Shan Chen, Wei Tian, Zijian Wang, Zehua Yu, F. Richard Leung, Victor C. M. Postdoctoral Research Station China RongTong Academy of Sciences Group Corporation Limited Beijing100022 China China RongTong Artificial Intelligence Research Center Beijing100022 China China University of Mining and Technology School of Artificial Intelligence Beijing100083 China China University of Mining and Technology School of Computer Science and Technology Xuzhou221116 China School of Artificial Intelligence Beijing100083 China The University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T 1Z4 Canada Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China

Perceiving scene depth and 3D structure is one of the key tasks for Internet of Video Things (IoVT) devices to understand and interact with the environment. Self-supervised monocular depth estimation has demonstrated significant potential in leveraging large-scale unlabeled datasets to achieve competitive performance, thereby playing an increasingly important role in depth estimation. Despite recent methods providing additional supervisory signals through self-distillation strategies to improve depth estimation, an effective method for generating pseudo-depth labels suitable for addressing occlusion issues among elements far from the camera remains unexplored. To address this limitation, we propose a Patch-based Self-Distillation Learning Framework to exploit the potential of self-supervised monocular depth estimation in recovering fine-grained scene depth. In the proposed framework, elements far from the camera within the input image are enlarged by enlarging and cropping operations in the patch-based self-distillation branch. Guided by photometric consistency, the model learns the detailed occlusion relationships among elements from the enlarged patches, producing patch depth maps with fine structures. In the main branch, which takes full-scale images as input, patch depth maps serve as pseudo-depth labels through self-distillation loss to provide additional supervisory signals for regions where photometric consistency fails to offer effective supervision. This forces the depth estimation network to recover fine structures of elements far from the camera in full-scale input images. Regarding the architecture of the depth estimation network, we introduce a bin-center prediction. In this prediction, a global aggregator based on self-attention provides additional scene structure queries for adaptive scene depth discretization. Finally, to encourage the model to explore more general cues for depth inference beyond road plane cues, we propose a PatchMix data augmentati

关键词： Image enhancement

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Service Level Agreement Monitoring as a Service: An Independent Monitoring Service for Service Level Agreements in Clouds

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Big Data 2023年第5期11卷 339-354页

作者： Badshah, Afzal Jalal, Ateeqa Farooq, Umar Rehman, Ghani-Ur Band, Shahab S. Iwendi, Celestine Department of Computer Science and Software Engineering International Islamic University Islamabad Pakistan Department of Computer Science University of Science and Technology Bannu Pakistan Department of Computer Science and Bioinformatics Khushal Khan Khattak University Karak Pakistan Future Technology Research Center College of Future National Yunlin University of Science and Technology Douliou Taiwan School of Creative Technologies University of Bolton Bolton United Kingdom

The cloud network is rapidly growing due to a massive increase in interconnected devices and the emergence of different technologies such as the Internet of things, fog computing, and artificial intelligence. In response, cloud computing needs reliable dealings among the service providers, brokers, and consumers. The existing cloud monitoring frameworks such as Amazon Cloud Watch, Paraleap Azure Watch, and Rack Space Cloud Kick work under the control of service providers. They work fine;however, this may create dissatisfaction among customers over Service Level Agreement (SLA) violations. Customers’ dissatisfaction may drastically reduce the businesses of service providers. To cope with the earlier mentioned issue and get in line with cloud philosophy, Monitoring as a Service (MaaS), completely independent in nature, is needed for observing and regulating the cloud businesses. However, the existing MaaS frameworks do not address the comprehensive SLA for customer satisfaction and penalties management. This article proposes a reliable framework for monitoring the provider’s services by adopting third-party monitoring services with clearcut SLA and penalties management. Since this framework monitors SLA as a cloud monitoring service, it is named as SLA-MaaS. On violations, it penalizes those who are found in breach of terms and condition enlisted in SLA. Simulation results confirmed that the proposed framework adequately satisfies the customers (as well as service providers). This helps in developing a trustworthy relationship among cloud partners and increases customer attention and retention. © Mary Ann Liebert, Inc.

关键词： Sales

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