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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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IOT BASED SMART IRRIGATION SYSTEM USING DUAL AXIS SOLAR TRACKER 2

IOT BASED SMART IRRIGATION SYSTEM USING DUAL AXIS SOLAR TRAC...

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2nd IEEE International Conference on Advances in Information technology, ICAIT 2024

作者： Madhu, B.G. Manoj, H.K. Belavadi, Arun Tejas, C.M. Chinthan, H.K. Department of Computer Science and Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India

ISBN: (纸本)9798350383867

In agriculture, proper water management is important for crop growth and resource conservation. This brief describes a smart water system designed to optimize water use by integrating dual-axis solar trackers. The system combines renewable energy sources with smart water management to increase environmental sustainability and agricultural performance. To get stronger every day. This makes the use of solar energy for water supply efficient, continuous and reliable. The saved energy is stored in batteries that provide reliable power for the equipment. Sensors constantly monitor humidity and send the information to the central control center in a timely manner. When soil moisture drops below the threshold, this indicates the need for irrigation, control room pump. This allows remote monitoring and control of water flows via a mobile app or web interface. Farmers have access to real-time information on soil moisture and processes, so timely adjustments and interventions can be made anytime, anywhere. Combining renewable energy with smart water management, the system offers a solution for agricultural water management. This brief demonstrates the potential of integrating solar technology into smart water systems, helping to improve efficiency and increase yields in modern agriculture. ©2024 IEEE.

关键词： Soil moisture

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Optimizing Automatic Test Case Generation Using Singular Value Decomposition Approach 15

Optimizing Automatic Test Case Generation Using Singular Val...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Bisi, Manjubala Srivastava, Aryan Verma, Abhishek Kumar, Aditya National Institute of Technology Department of Computer Science and Engineering Warangal India

ISBN: (纸本)9798350370249

Test case generation is a complex problem when dealing with multiple objectives, which hinders search efficiency with algorithms like DynaMOSA in the EvoSuite framework. To address this issue, we propose SVD-DynaMOSA, utilizing Singular Value Decomposition for dimensionality reduction. This approach aims to optimize the test case generation process, leading to improved efficiency. Experimentation with 49 projects and 110 classes from the SF110 dataset, selected for their complexity and number of objectives, demonstrates SVD-DynaMOSA's superiority over DynaMOSA. It achieves higher or comparable coverage in multiple metrics, enhancing test case generation performance significantly. SVD-DynaMOSA shows promise in producing comprehensive test suites in practical time frames, overcoming the limitations of current methods. © 2024 IEEE.

关键词： EvoSuite Many-objective search optimization Principal Component Analysis (PCA) Singular Value Decomposition (SVD) Test case generation

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Advancing Data Sovereignty in Distributed Environments: An In-Depth Exploration of Data Localization Challenges

Advancing Data Sovereignty in Distributed Environments: An I...

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2024 International Conference on computer, Electronics, Electrical engineering and their Applications, IC2E3 2024

作者： Kancharla, Jaganmohan Reddy Madhu Kumar, S.D. National Institute of Technology Department of Computer Science & Engineering Calicut India

ISBN: (纸本)9798350388534

Data localization in distributed computing has gotten a lot of attention because it has the potential to improve data sovereignty, make sure regulations are followed, and make data easier to access. However, this practice also brings forth a multitude of challenges and threats to cybersecurity, data privacy, and overall information security. In this comprehensive survey paper, we delve into the complex landscape of challenges and threats associated with data localization in distributed computing environments. We explore the intricate interplay between data localization, distributed infrastructure, cybersecurity, and privacy concerns. This paper provides an in-depth analysis of various challenges such as regulatory compliance, data integrity, authentication, and access control, along with potential threats like data breaches, insider attacks, and unauthorized access. Furthermore, we investigate the state-of-the-art security mechanisms, encryption techniques, privacy-preserving methods, and access control strategies that researchers and practitioners have developed to address these challenges. Through this survey, we aim to provide a comprehensive overview of the critical issues surrounding data localization within cloud computing and shed light on the emerging trends and potential solutions that can pave the way for secure and privacy-aware data localization practices. © 2024 IEEE.

关键词： Data integrity

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Enhancing Occluded Face Recognition Through Device-Edge Collaboration and Cross-Domain Feature Fusion with Heatmaps 3

Enhancing Occluded Face Recognition Through Device-Edge Coll...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Prasanth, Ashwin Annie Micheal, A. Department of Computer Science & Engineering Sathyabama Institute of Science & Technology Chennai India

ISBN: (纸本)9798331527549

Face recognition under occlusion presents a persistent challenge in computer vision, primarily due to difficulties in capturing and effectively integrating visible and obscured facial features. This paper introduces a novel device-edge collaborative framework that advances occluded face recognition through an innovative cross-domain feature fusion technique. Our method employs a software-generated, occlusion-aware heatmap created from standard visible-light images, which emphasizes key facial landmarks even when regions of the face are partially covered. This heatmap provides a complementary data layer that enhances traditional visible facial features, allowing the cross-domain feature fusion process to synthesize a more comprehensive set of features for reliable recognition under occlusion. The combined feature set leverages both visible and simulated heatmap information to improve model robustness, even in complex occlusion scenarios. Additionally, a delay-optimized task scheduling method is applied on the edge, ensuring efficient resource allocation, faster processing, and minimal latency. Although this project is ongoing, preliminary evaluations indicate the potential effectiveness of this approach, with expected outcomes to include high recognition accuracy and reduced latency. This framework provides a scalable solution for occluded face recognition by integrating complementary data sources without requiring specialized hardware. © 2025 IEEE.

关键词： Face recognition

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Vision Aid For Blind People Using YOLOV8 2

Vision Aid For Blind People Using YOLOV8

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2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： More, Priyanka Sangamkar, Satvik Vishwakarma Institute Of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350367461

This assistive system for the visually impaired integrates real-time YOLOv8 object detection with distance estimation and text-to-speech conversion, empowering users with enriched environmental awareness. Leveraging robust datasets and architectures, it identifies over 90 everyday objects amidst clutter while concurrently approximating object proximity through trigonometric translations of size metrics. Audio cues enunciate recognized items and distances in real time for accessibility. This combination of precise visual recognition, spatial metrics, and assistive feedback holds promise for enhanced mobility, independence, and safety during navigation for visually impaired individuals. © 2024 IEEE.

关键词： Vision aids

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A GUI-Based Approach to Predict Heart Disease Using Machine Learning Algorithms and Flask API 5th

A GUI-Based Approach to Predict Heart Disease Using Machine ...

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5th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2023

作者： Bose, Sayan Kumar Ghosh, Shinjohn Das, Sibarati Bhowmick, Souhardya Talukdar, Arpita Dey, Lopamudra Department of Computer Science and Engineering Heritage Institute of Technology Kolkata India

ISBN: (纸本)9783031488757

Heart conditions are classified as diverse illnesses with numerous subgroups. To make patient clinical treatment easier, early heart disease diagnosis and prognosis are crucial. Although much research has been done to predict the cause of heart disease. We have tried to build a heart disease detection system using machine learning algorithms. The basic goal of work is to detect whether a person is suffering from heart disease or not. We have also built a GUI using HTML and CSS for our front end and integrated both using flask for the back end. The user interface is available at https://***/SayanKumarBose/***. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Support vector machines

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Real-Time Pose based Gaming 15

Real-Time Pose based Gaming

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Bhardwaj, Rakhi J. Dharashive, Rajnandini N. Rajvaidya, Arya J. Nimje, Rachit D. Shende, Riddhi S. Department of Computer Engineering Vishwakarma Institute of Technology Maharashtra Pune India

ISBN: (纸本)9798331300579

The gaming industry is poised for a revolution with the advent of a novel system that utilizes cameras and computer vision to accurately track and analyze player body positions and movements, eliminating the need for wearable sensors. This groundbreaking technology promises to transform the gaming landscape, ushering in an era of immersive and interactive experiences. By harnessing the power of OpenCV, the proposed system seamlessly captures and interprets player movements, enabling natural and intuitive game control. This approach offers a myriad of benefits, including enhanced gameplay, heightened user engagement, and unprecedented accessibility for individuals with physical limitations. The introduction of this sensor-free gaming technology marks a paradigm shift, paving the way for a future where gaming is more engaging, accessible, and immersive than ever before. © Grenze Scientific Society, 2024.

关键词： Photons

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Software Reliability Growth Testing Effort Function Model Dependent on Machine Learning and Neural Network Algorithm

Software Reliability Growth Testing Effort Function Model De...

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2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024

作者： Farooq, Refath Chishti, Mohammad Ahsan National Institute of Technology Department of Computer Science Engineering Srinagar India

ISBN: (纸本)9798350372229

The quantification of dependency stands as a crucial element in programming quality. The Software Reliability Growth Model (SRGM) is a commonly utilized tool for evaluating reliability across diverse and challenging scenarios. However, the accuracy of traditional time-sensitive SRGMs may be compromised when test execution extends over a prolonged period. In response to this limitation, the SRGM approach is adapted to center around testing practices rather than relying exclusively on the progression of time. Earlier methods proposed restricted testing capabilities, but the notion of unlimited test time introduces an infinite testing scenario, rendering it impractical. To overcome this, the method introduces Neural Heterogeneous Poisson Process (NHPP) models, which operate without being bound by time limitations. Furthermore, the approach incorporates Artificial Neural Networks (ANNs) to model program failures based on available information. The application of an AI model selection method ensures precise representation of both historical and future load fitting location information Artificial Neural Networks (ANNs) showcase an adept capacity for effective generalization from the input provided to a comparable model, proficiently capturing patterns from prior instances of failure data. Through the integration of common-sense information into programming failure indicators, the suggested Testing Effort Function (TEF) and Software Reliability Growth Model (SRGM) proficiently depict extensive failure data. The incorporation of Machine Learning (ML) and Artificial Neural Networks (ANN) notably enhances the precision of traditional boundary estimation when compared to release time, thereby ensuring robust software reliability. © 2024 IEEE.

关键词： ANN Machine Learning NHPP SRGM Testing Effort Function (TEF)

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Articulation Node Based Mobile Node Routing Protocol in a Hybrid IoT Network 2

Articulation Node Based Mobile Node Routing Protocol in a Hy...

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2nd IEEE International Conference on Recent Advances in Information technology for Sustainable Development, ICRAIS 2024

作者： Leelavathi, R. Vidya, A. Vivekananda Institute of Technology Computer Science and Engineering Department Bengaluru India

ISBN: (数字)9798350354461

ISBN: (纸本)9798350354461

In static IoT networks, fixed sensor nodes can create a bottleneck at central hubs, leading to congestion and rapid energy depletion, which may result in network partitioning or failure. Existing routing protocols, such as RPL, are not well-equipped to handle these issues effectively. To overcome these challenges, we propose the Articulation Node-Based Mobile Node Routing Protocol for LLNs (AMRPL), designed to address the limitations of traditional static networks. AMRPL dynamically identifies articulation nodes, which are critical for maintaining connectivity, and instructs mobile nodes to balance the load by moving towards these points. This approach mitigates the congestion and energy depletion issues found in traditional methods. Simulation results, conducted in the Cooja environment, demonstrate that AMRPL outperforms RPL by improving Packet Delivery Ratio (PDR), reducing End-to-End delay, and lowering energy consumption through efficient load distribution by mobile nodes. These improvements underscore the protocol's capability to enhance the overall performance and reliability of hybrid IoT networks. © 2024 IEEE.

关键词： Energy efficiency

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