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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

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A Review of IoT-Driven Innovations in Supply Chain Management 3

A Review of IoT-Driven Innovations in Supply Chain Managemen...

引用

3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Chandankhede, Arpit Gourshettiwar, Palash Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Sawangi Meghe Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science and Engineering Sawangi Meghe Maharashtra Wardha442001 India

ISBN: (纸本)9798331509675

Supply Chain Management (SCM) worldwide makes major advancements through the Internet of Things (IoT) by enabling real-time monitoring and prediction analytics and automatic decision capabilities in worldwide deliver chains. Through IoT technology integration with Artificial Intelligence (AI) and blockchain and cloud computing the supply chain solves major operational problems including monitoring difficulties and waste reduction and regulatory compliance requirements and operation leadership deficits. The implementation of IoT for supply chain management encounters major adoption barriers from high installation costs combined with security risks and operability complications as well as limited scalability capacity that affects especially small to medium enterprises (SMEs) and developing markets. The evaluation paper examines the shifting impact of IoT in supply chain management which enhances performance metrics and brings greater clarity and strengthens supply chain resilience. A scientist studied existing papers and case studies to reveal several essential advantages which include better inventory management, predictive analysis systems and more effective supply-chain collaborations. The analysis emphasizes effective solutions for security privacy and moral and environmental issues to guarantee sustainable expanded IoT adoption. This paper delivers practical knowledge alongside best practices to help organizations adopt IoT systems which create adaptable efficient deliver chains with sustainability at their core thus achieving long-term market benefits in today's complex global marketplace. © 2025 IEEE.

关键词： Inventory control

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3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

3rd International Conference on Trends in Electronics and He...

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3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

ISBN: (纸本)9789819739363

The proceedings contain 52 papers. The special focus in this conference is on Trends in Electronics and Health Informatics. The topics include: An Effective Combination of Deep and Machine Learning Models for Monkeypox Detection from Dermatographic Image;a Time-Efficient and Effective Image Contrast Enhancement Technique Using Fuzzification and Defuzzification;An Ensemble Machine Learning-Based Approach for Detecting Malicious Websites Using URL Features;The Multi-class Paradigm: How Transformers Are Reshaping Language Analysis in NLP;deep Learning Precision Farming: Identification of Bangladeshi-Grown Fruits Using Transfer Learning-Based Detection;Deep Learning Solutions for Detecting Bangla Fake News: A CNN-Based Approach;a Two-Stage Stacking Ensemble Learning for Employee Attrition Prediction;ensemble Learning Approaches for Alzheimer’s Disease Classification in Brain Imaging Data;pseudo-Knighted Cocktail Shaker Sort;sentiment Analysis in Twitter Data Using Machine Learning-Based Approach;road Object Detection for Visually Impaired People in Bangladesh;newBreeze: A Comprehensive Solution to a Beginner-Friendly Arch Linux Distribution with Zen Kernel;deep Ensemble Learning Approach for Multimodal Emotion Recognition;Tri Focus Net: A CNN-Based Model with Integrated Attention Modules for Pest and Insect Detection in Agriculture;detection and Classification of Spam Email: A Machine Learning-Based Experimental Analysis;predictive Modeling and Early Detection of White Spot Disease in Shrimp Farming Using Machine Learning: A Case Study in Bangladesh;bangla License Plate Detection and Recognition Approach Based on computer vision for Authentic Vehicle Identification;feature Techniques with a Custom Convolutional Model for Breast Tumor Surveillance in Mammograms;An AI-Based Clinical Recommendation System Using Ensemble-Based Soft Voting Classifier;machine Learning-Based Approach to Predict Heart Diseases Using Fused Dataset;an Optimal Feature Selection-Based Approach to P

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Neural Contextual Adaptation (NCA): For Unsupervised Learning in Dynamic Environments 3

Neural Contextual Adaptation (NCA): For Unsupervised Learnin...

引用

3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Praveen Kumar, G.D. Sanjan, S. Suraj, P. Rohan, U.A. Srinivas, R. Thanush, V. Visvesvaraya Technological University P.E.S College of Engineering Department of Computer Science and Engineering Mandya India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515911

In recent years, artificial intelligence (AI) has made significant strides in various domains, primarily driven by supervised learning techniques requiring vast amounts of labeled data. However, real-world applications, particularly those involving rapidly changing environments, demand models capable of autonomous adaptation without the need for extensive labeled datasets. In this paper, we present a novel framework for unsupervised learning that allows AI models to dynamically adapt in real-time to changing environments. Our approach leverages a combination of self-organizing maps and contrastive predictive coding to enhance model flexibility and adaptability across diverse settings. We introduce an architecture that incorporates temporal data processing and on-the-fly adaptation mechanisms, enabling the model to learn and generalize from evolving data distributions. Through extensive practical assessments and experimentation, we demonstrate our model's ability to outperform existing unsupervised approaches in real-time object detection and decision-making scenarios. The results, which show a significant reduction in model retraining time and increased adaptability to novel environments, suggest that our framework can be applied to various fields including robotics, autonomous vehicles, and dynamic control systems. © 2025 IEEE.

关键词： Self-supervised learning

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3rd international conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

3rd International Conference on Intelligent Computing Techni...

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3rd international conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

ISBN: (纸本)9789819784639

The proceedings contain 50 papers. The special focus in this conference is on Intelligent Computing Techniques For Smart Energy Systems. The topics include: Analysis of Fault and Current-Limiting Methods in the Power System;UDS for Data Communication in Temperature Monitoring;approximation in the Weighted Lipschitz Class by (C,α,θ)(E,q) Mean of Its Fourier Series;demand Response and Load Profile Analysis in Modern Electricity Systems;First-Principles Study of the Structural, Optical and Electronic Properties of Zinc Blende GaN Through PBEsol and TB-mBJ Functionals;optimization-Based Cost Analysis for Energy Management System in Microgrids;classification and Prediction of Knee Osteoarthritis by Deep Learning Approach;Predicting Stock Price and Market Direction Using Statistical and LSTM Models;Comprehensive Evaluation of Time Management with Balancing Resistors in Passive Cell Balancing Using the 1RC Model;PAWnnect: Pioneering IoT-ML Driven Pet Monitoring;transactive Energy Management for Microgrids: Peer-To-Peer Trading Using Stackelberg Game Approach;Unravelling the Mind's Emotions: A Review of EEG-Based Emotion Detection Using Machine Learning and Deep Learning;unlocking IoT Security: Enabling the Future with Lightweight Cryptographic Ciphers;Optimal Design of Nano Scale Voltage Amplifier Using Evolutionary Techniques for DG-MOSFET;flower Patterned with Elliptical Petals Multiband Microstrip Fractal Patch Antenna for Wireless Applications;Optimal Scheduling of Solar PV Generators and Network Assets in Distribution Network;revolutionizing Biomedical Engineering with Microcontroller Applications: A Comprehensive Review;investigation of Battery Temperature Impact on High Voltage Cable of Electric Vehicles;deep Learning Technique for computer vision-Based Pose Estimation for Augmented Reality;Rectangular Shape Patch Antenna with Defected Ground Plane for 5G Sub 6 GHz Wireless Communication Systems.

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3rd international conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

3rd International Conference on Intelligent Computing Techni...

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3rd international conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

ISBN: (纸本)9789819784288

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Integrated Hydroponics Automation System Utilizing IoT for Enhanced Plant Growth 3

Integrated Hydroponics Automation System Utilizing IoT for E...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Nilahni, N. Sivasakthi, P. Kavitha, P. Madhumathi, S.M. Sakthi Lakshmi Priya, C. Saranyavaishalini, V.G. Department of Computer Science and Engineering PSR Engineering College Sivakasi India

ISBN: (纸本)9798331527549

Growing plants in nutrition solution with any growing medium or roots dipped in distilled water is Hydroponics. Hydroponics, the practice of growing plants in a nutrient-rich solution without soil, offers significant advantages such as higher yield, reduced water usage, and efficient resource management compared to traditional farming. However, existing hydroponic systems often require separate monitoring and control platforms for different setups, such as Wick and Drip systems, increasing complexity and cost. This paper proposes a Combined Hydroponics Automation System utilizing IoT, integrating both Wick and Drip systems into a single, unified platform. The system employs Nodemcu ESP8266 to monitor key parameters such as pH, humidity, moisture, and water levels, with data transmitted to a cloud platform for real-time access and control. The unified approach reduces development and operational costs while simplifying the monitoring process. The outcome demonstrates improved efficiency in plant management, with streamlined data visualization, remote control, and optimized resource allocation, making it a cost-effective solution for urban and resource-limited farming environments. © 2025 IEEE.

关键词： Hydroponics

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Research and Application of computer vision and Predictive Maintenance in Health Management of Conveying Equipment 3rd

Research and Application of Computer Vision and Predictive M...

引用

3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Long, Zhongyi Gao, Fan Tang, Li Hunan Valin Xiangtan Iron and Steel Co. Ltd. Xiangtan China ChongQing ChuanYi Automation Co. Ltd. Chongqing China

ISBN: (纸本)9789819616930

As an indispensable part of realizing mechanization and automation of handling system in ports, metallurgy, chemical, thermal power, building materials and other fields, conveying equipment faults account for 50% of delivery system faults. In order to improve the maintenance mode of conveying equipment based on manual inspection and record, this paper deals with the research and application of computer vision and predictive maintenance in health management of conveying equipment. Firstly, based on the research of mechanical structure of conveying equipment drive unit, failure cause analysis of conveying equipment and overview of common detection techniques were introduced. Secondly, an health management system based on computer vision and predictive maintenance was designed, the computer vision model was built based on Pangu large-sized model and trained by artificial intelligence training platform, and StressWave analysis method was applied for predictive maintenance of conveying equipment driving unit. In the application case of main belt of blast furnace and the key belt of sintering in the iron making process, this health management system issue alarms accurately and timely, minimize the impact of unplanned downtime on the production process, resulting in significant economic and social benefits. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Predictive maintenance

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Next-Gen IoT Battery and Cooling System for EV Safety and Efficiency 3

Next-Gen IoT Battery and Cooling System for EV Safety and Ef...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Selvanayagi, A. Kaleeswaran, T. Bhuvaneshwaran, M. Kavinraj, N. Logesh, C.N. Department of Computer Science and Engineering M.Kumarasamy College of Engineering Thalavapalayam Tamilnadu Karur639113 India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

The increasing adoption of EVs requires efficient battery management systems for optimal performance, safety, and increased battery life. An investigation of an IoT-based intelligent smart battery management system for EVs is presented. Here, real-time monitoring and analysis of important key parameters such as voltage, current, state of charge (SOC), and temperature are considered. It includes sensors, a microcontroller, and wireless communication transferring data to a cloud platform, hence allowing remote monitoring and control. It utilizes adaptive cooling to avoid overheating. It contains a display showing the status of the battery. The experimental results showed that the system had improved the performance of the battery, prevented thermal runaway for safety purposes, and made the lifespan of the battery longer. This is the nature of such methodology to create dependable, efficient, sustainable transportation using EV batteries. © 2025 IEEE.

关键词： Battery management systems

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Enhancing Smart Grid Security with Quantum Cryptography: A BB84-based Framework 3

Enhancing Smart Grid Security with Quantum Cryptography: A B...

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3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Garg, Shail Gayatri, Yerukola Surya Kausthub, A. Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

The study investigates how quantum cryptography can be employed to improve security in smart grid communication networks. Attempting to use the BB84 QKD protocol, it allows secure creation and management of those cryptographic keys that cannot be broken with the help of quantum and traditional hacking techniques. It depends on symmetric encryption mechanisms like AES to provide high data confidentiality during transmission. Regarding the key management, the system provides a key management server that distributes keys to the grid nodes and performs key updating to ensure control with the managing authority. It also presents reliability under practical conditions through performance analogs such as Quantum Bit Error Rates (QBER), and system latency. This approach shows that quantum cryptography can provide a highly secure and efficient communication network for the next-generation smart grid. © 2025 IEEE.

关键词： Smart power grids

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Comparing the Pre-Trained Models with LSTM Combination to Improve Image Captioning Technology 3

Comparing the Pre-Trained Models with LSTM Combination to Im...

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3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Mukil, L.D. Singh, Tripty Sharma, Mansi Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India Graphic Era University Department of Computer Science and Engineering India

ISBN: (纸本)9798331508456

Image captioning, integrating computer vision and natural language processing, has become one of the critical areas of work for better accessibility and advancing technology. In this study, the performance of pre-trained convolutional neural networks-DenseNet, VGG-16, ResNet, and Xception-has been evaluated when coupled with LSTM units for generating captions on Flickr8k. These models have been evaluated on the basis of BLEU and ROUGE scores. The best scores were produced by ResNet-LSTM, which indicates the model's stronger ability to produce captions that are accurate and contextual. VGG-16 with LSTM ranked second;it was almost on par. Xception with LSTM gave results that were moderate. DenseNet with LSTM had the worst score, indicating that the feature extraction mechanism of this model is weak. The following results provide evidence for the practical use of ResNet-LSTM to facilitate access: from assistive technology for visually impaired users to automatically generated content. The comparative study would further indicate which one has more merits or drawbacks compared with others and thereby enable a more informed selection of the models suitable for each particular application. © 2025 IEEE.

关键词： Convolutional neural networks

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