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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Parisa Shirinabadi Amirreza Samadi Bonab Khadim Moin Siddiqui Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Electrical & Electronics Engineering Department S.R. Institute of Management & Technology Lucknow India

ISBN: (数字)9798331525132

ISBN: (纸本)9798331525149

The rapid advancements in Artificial Intelligence (AI) and the Internet of Things (IoT) have paved the way for innovative solutions to address global energy challenges. This paper explores the integration of AI and IoT in energy conservation, focusing on their combined potential to optimize energy consumption, enhance system efficiency, and support sustainable development. AI-driven predictive analytics and machine learning algorithms enable accurate energy demand forecasting and real-time decision-making, while IoT devices facilitate seamless data collection, monitoring, and control of energy systems. The synergy of these technologies has been instrumental in transforming energy management across various sectors, including smart grids, industrial automation, and smart buildings. However, their adoption comes with significant challenges, such as data security, interoperability, and the high cost of deployment. This review discusses the current state of AI and IoT in energy conservation, identifies key challenges, highlights emerging opportunities, and examines future trends, such as the role of blockchain and edge computing in decentralized energy systems. The paper concludes by emphasizing the need for interdisciplinary research and collaboration to unlock the full potential of AI and IoT in creating sustainable energy solutions.

关键词： Renewable energy sources Energy consumption Technological innovation Collaboration Real-time systems Smart grids Internet of Things Artificial intelligence Sustainable development Predictive analytics

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Post-Processing of Thresholding or Deep Learning Methods for Enhanced Tissue Segmentation of Whole-Slide Histopathological Images

Post-Processing of Thresholding or Deep Learning Methods for...

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18th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Marczyk, Michal Wrobel, Agata Merta, Julia Polanska, Joanna Department of Data Science and Engineering Silesian University of Technology Gliwice44-100 Poland Yale Cancer Center Yale School of Medicine New HavenCT06511 United States Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland

Digital pathology allows for the efficient storage and advanced computational analysis of stained histopathological slides of various tissues. Tissue segmentation is a crucial first step of digital pathology aimed at eliminating background, pen markings, and other artifacts, reducing image size, and increasing the efficiency of further analysis. In most cases, color thresholding or deep learning models are used, but their effectiveness is reduced due to complex artifacts and huge color variations between slides. We propose a post processing method to increase the tissue segmentation performance of any initial segmentation algorithm. Using a set of 197 manually annotated histopathological images of breast cancer patients and 63 images of endometrial cancer patients, we tested our method with 3 thresholding techniques and 3 deep learning-based algorithms by calculating the Dice index, Jaccard index, precision, and recall. In both datasets, applying post processing increased precision and recall for thresholding methods and mostly precision for deep learning models. Overall, applying post-processing gave better tissue segmentation performance than initial segmentation methods, significantly increasing Dice and Jaccard indices. Our results proved that thanks to post-processing, the tissue segmentation pipeline is more robust to noises and artifacts commonly present in histopathological images. © 2025 by SCITEPRESS– Science and technology Publications, Lda.

关键词： Image segmentation

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Improving WiFi Fingerprint Database With Irregular Distribution of Reference Points Using Interpolation Methods

Improving WiFi Fingerprint Database With Irregular Distribut...

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2024 International Conference on Advanced Technologies for Communications, ATC 2024

作者： Vu-Thanh, Trung He, Jing Duong-Bao, Ninh Lee, Seon-Woo Thi, Luong Nguyen Nguyen-Huu, Khanh College of Computer Science and Electronic Engineering Hunan University Changsha China Dalat University Faculty of Mathematics and Informatics Dalat Viet Nam Hallym University Division of Software Chuncheon Korea Republic of Dalat University Faculty of Information Technology Dalat Viet Nam Dalat University Department of Electronics and Telecommunications Dalat Viet Nam

ISBN: (纸本)9798350353983

Using WiFi Fingerprinting for indoor positioning is becoming increasingly popular due to its cost-effectiveness. However, to ensure the system can operate with high accuracy and stability, this technique requires a burden of data collection tasks from a dense distribution of reference points (RPs). To decrease the cost of data collection, as well as to improve the WiFi fingerprint database with irregular distribution of RPs, this study applies and compares different interpolation methods. Evaluating these methods in a public dataset including multiple sub-datasets with irregular distributions of RPs, the results highlight the Linear Barycentric interpolation (LB) as the most favorable method due to its low complexity and stable performance. The LB-based fingerprint database achieves an average interpolation error of less than 3 dBm compared to the original one. When applying the interpolated database to positioning tasks, it can help reduce acquisition costs by up to 50% while improving positioning accuracy by up to 11%. The study reveals the feasibility of interpolation in optimizing WiFi fingerprint data collection, especially in large and complex environments where regular distribution of RPs cannot be deployed. © 2024 IEEE.

关键词： Interpolation

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Study of Substrate-Materials Impact on Compact Antenna Performance 6

Study of Substrate-Materials Impact on Compact Antenna Perfo...

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6th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2022

作者： Mahmood, Sarmad Nozad Saeidi, Tale Ismael, Arkan Raoof Alani, Sameer Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq Istinye University Faculty of Engineering and Natural Sciences Electrical and Electronics Engineering Department Istanbul34396 Turkey College of Law Department of Law University of Mashreq Baghdad Iraq

ISBN: (数字)9781665470131

ISBN: (纸本)9781665470131

Improving bandwidth and reducing size are significant design aspects for practical compact antenna applications. To reach wideband and decrease the scale of microstrip antennas, numerous strategies were brought into practical action. This article demonstrates a survey of various miniaturization strategies. It analyzes the effectiveness of the compact and miniaturized multi-use antennas in terms of their size, forms of substrate material, conductivity, loss tangent, and thickness that can influence the bandwidth, gain, radiation efficiency, Specific absorption rate (SAR) value antenna type, feeding techniques, and further significant parameters. Noteworthy, the most popular technique is to use a high dielectric constant for its substratum content to reduce the size of a printed antenna. Thus, the directed wavelength under the patch and the resonant patch size can be decreased correspondingly. © 2022 IEEE.

关键词： Microstrip antennas

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AI and IoT in Energy Conservation: Challenges, Opportunities, and Trends 12

AI and IoT in Energy Conservation: Challenges, Opportunities...

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12th Iranian Conference on Renewable Energies and Distributed Generation, ICREDG 2025

作者： Shirinabadi, Parisa Bonab, Amirreza Samadi Siddiqui, Khadim Moin University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran S.R. Institute of Management & Technology Electrical & Electronics Engineering Department Lucknow India

ISBN: (纸本)9798331525132

关键词： Energy efficiency

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A Dynamic Resource-Aware Routing Protocol in Resource-Constrained Opportunistic Networks

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computers, Materials & Continua 2022年第2期70卷 4147-4167页

作者： Aref Hassan Kurd Ali Halikul Lenando Slim Chaoui Mohamad Alrfaay Medhat A.Tawfeek Department of Computer Systems and Communication Technologies Faculty of Computer Science and Information TechnologyUniversiti Malaysia Sarawak(UNIMAS)Kota Samarahan94300Malaysia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka2014KSA Unit-Lab of Sciences of Electronics Technologies of Information and TelecommunicationsSfax UniversitySfaxTunisia Department of Basic Sciences First Common Year DeanshipJouf UniversitySakaka2014KSA Department of Computer Sciences College of Computer and Information SciencesJouf UniversitySakaka2014KSA Department of Computer Sciences Faculty of Computers and InformationMenoufia UniversityEgypt

Recently,Opportunistic Networks(OppNets)are considered to be one of the most attractive developments of Mobile Ad Hoc Networks that have arisen thanks to the development of intelligent *** are characterized by a rough and dynamic topology as well as unpredictable contacts and contact *** is forwarded and stored in intermediate nodes until the next opportunity ***,achieving a high delivery ratio in OppNets is a challenging *** is imperative that any routing protocol use network resources,as far as they are available,in order to achieve higher network *** this article,we introduce the Resource-Aware Routing(ReAR)protocol which dynamically controls the buffer usage with the aim of balancing the load in resource-constrained,stateless and non-social *** ReAR protocol invokes our recently introduced mutual informationbased weighting approach to estimate the impact of the buffer size on the network performance and ultimately to regulate the buffer consumption in real *** proposed routing protocol is proofed conceptually and simulated using the Opportunistic Network Environment *** show that the ReAR protocol outperforms a set of well-known routing protocols such as EBR,Epidemic MaxProp,energy-aware Spray and Wait and energy-aware PRoPHETin terms of message delivery ratio and overhead ratio.

关键词： Opportunistic networks mobile ad hoc networks routing protocols resource-constrained networks load balancing buffer management

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Brain Sensing with Ultrasound Tomography and Deep Learning Algorithms 23

Brain Sensing with Ultrasound Tomography and Deep Learning A...

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29th Annual International Conference on Mobile Computing and Networking, MobiCom 2023

作者： Klosowski, Grzegorz Rymarczyk, Tomasz Soleimani, Manuchehr Faculty of Management Lublin University of Technology Lublin60011739 Poland Institute of Computer Science and Innovative Technologies Wsei University Lublin60274650 Poland Department of Electronics and Electrical Engineering University of Bath Bath60030480 United Kingdom

ISBN: (纸本)9781450399906

Ultrasound computer tomography (USCT) represents a medical imaging modality designed to visualize alterations in the speed of ultrasonic waves. The primary objective of the study presented was to devise a lightweight, portable, and cost-effective tomographic device capable of non-invasively capturing internal images of the human brain in real-time. To achieve this aim, a prototype ultrasonic tomograph was developed, comprising a lightweight head hoop integrated with ultrasonic transducers and a tomograph unit. Ultrasonic measurements were transformed into images using a heterogeneous convolutional neural network (CNN). The USCT system was engineered to facilitate wireless communication between the sensors embedded within the wearable head cap and the tomographic apparatus. © 2023 ACM.

关键词： Ultrasonic transducers

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Image Denoising for Smart Laser Osteotomy Using Deep Learning-based Fast Optical Coherence Tomography (OCT) 2

Image Denoising for Smart Laser Osteotomy Using Deep Learnin...

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2nd International Conference on electronics and Renewable Systems, ICEARS 2023

作者： Ghate, Shubhangi N. Kalpanadevi, D. Amudha, K. Velayutham, Priya Balu, S. Shah, Mohd Asif D. Y. Patil Deemed to Be University Ramrao Adik Institute of Technology Department of Electronics and Telecommunication Engineering Maharashtra Navi Mumbai Nerul India Kalasalingam Academy of Research and Education Department of Computer Applications Krishnan Koil Tamil Nadu Srivilliputhur India Kongunadu College of Engineering and Technology Department of Electronics and Communication Engineering Thottiyam Tamilnadu Trichy India Paavai Engineering College Department of Computer Science and Engineering Tamilnadu Namakkal India Vivekanandha College of Engineering for Women Department of Computer Science and Engineering Tiruchengode Tamilnadu Namakkal India Chandigarh University Adjunct Faculty University School of Business Gharuan Punjab Mohali India

ISBN: (纸本)9798350346640

With laser osteotomy, patients may expect clean incisions and minimal damage to bone structure. With the smart laser osteotomy method, this study has suggested using Optical Coherence Tomography (OCT) to track the ablation as it occurred. The OCT image is useful for distinguishing different types of tissue and giving the ablation laser guidance on where to focus its energy to avoid damaging vital structures like bone marrow and nerves. Furthermore, the application relies on the quality of the OCT picture to determine the tissue classifier's exactness. Because of this, establishing a reliable feedback system depends heavily on picture denoising. The frame averaging approach is widely utilized as a means of picture denoising in Optical Coherence Tomography (OCT). The more photographs that are used, the better the final image will seem. However, this method requires more time to acquire data and makes the system more vulnerable to motion abnormalities. To get around these restrictions, a deep learning denoising algorithm is used to simulate the frame-averaging approach. The generated image was of higher quality than traditional digital filtering techniques while maintaining the same level of detail as when using a frame-averaging approach. This study also analyzes how the proposed strategy impacts the precision of the tissue classifier model to inform the ablation laser's adjustments. After applying image denoising, a significant improvement has been observed in the tissue classifier's performance. It is also evident that the classifier trained with deep learning denoised images was as accurate as the classifier trained with frame-averaged images. © 2023 IEEE.

关键词： Optical tomography

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Intelligent Farm Irrigation and Safety System

Intelligent Farm Irrigation and Safety System

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Information technology (ACIT)

作者： Adnan Al-Smadi Murar Al-Nusairat Ammar Erjoub Laith Freitekh Mohammed Khouj Department of Computer Science Faculty of Information Technology Zarqa Univeristy Zarqa Jordan Depatrment of Electronics Engineering Engineering Faculty Yarmouk University Irbid Jordan Department of Electrical Engineering University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

In recent years, there has been growing interest in utilizing technology to improve agricultural practices and optimize crop yield. One area of focus is the development of intelligent farm irrigation systems that integrate automation, sensing, and control mechanisms to enhance the efficiency and effectiveness of farming operations. An important aspect of automated agriculture is the management of irrigation, as well as ensuring the safety of the farming environment. Plastic houses have become a cornerstone in modern agriculture, enabling controlled cultivation environments and increased yields. However, managing these environments efficiently requires a harmonious integration of various factors. This paper proposes an intelligent for irrigation, temperature, humidity, flame, gas detection, and fire alarm functions in a plastic house. The system presented here uses Arduino Microcontroller based system that integrates various sensors technology to monitor soil conditions accompanied by audible and visual alerts. Fire safety is ensured through flame and gas sensors, triggering immediate alerts. Python language was used to write the code for the Arduino microcontroller.

关键词： Temperature sensors Irrigation Visualization Codes Microcontrollers Fires Sensor systems Plastics Intelligent sensors Farming

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Alternately Coupled Magnetoinductive Waveguide with Nulls-Free Characteristic for Two-Way Wireless Power Transfer Application

Alternately Coupled Magnetoinductive Waveguide with Nulls-Fr...

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2022 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2022

作者： Rakluea, Chawalit Worapishet, Apisak Chaimool, Sarawuth Zhao, Yan Akkaraekthalin, Prayoot Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunication Engineering Pathum Thani Thailand Mahanakorn Institute of Innovation Mahanakorn University of Technology Bangkok Thailand Khon Kaen University Faculty of Engineering Department of Electrical Engineering Khon Kaen Thailand International School of Engineering Chulalongkorn University Faculty of Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (数字)9781665432382

ISBN: (纸本)9781665432382

Two-way alternately coupled magnetoinductive waveguide for wireless power transfer is presented in this paper. With the use of the alternate coupling polarities between consecutive resonator cells and quadrature phase termination at the last cell, the nulls-free characteristics were clearly achieved for all locations. The power is transferred to a single receiver with 74% from the input power. For two receivers placed separately on each path, a small variation of power transfer percentage ranging from 40% to 43% is obtained. Finally, the proposed configuration model can be developed to power and charge multiple electronic devices, robots and EVs without nulling effect. © 2022 IEEE.

关键词： Energy transfer

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