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Smart ANPR: A Checkpoint-Based Toll and Parking Management System Using Hybrid OCR and Blockchain 3

Smart ANPR: A Checkpoint-Based Toll and Parking Management S...

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Samarth, M.N. Gopisetti, Sampriti Chaitra, M. Bnm Institute of Technology Affiliated to Vtu Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331515911

Automated Number Plate Recognition is one of the most important applications of computer vision, employed in the enforcement of traffic law, vehicular management, security, and even at toll collection. This paper proposed an advanced system for ANPR that can move away from the traditional booth and establish a checkpoint. The strategically located cameras with checkpointing will automatically capture the plates of passing vehicles, permitting road tax and parking fees to be deducted without making contact. A hybrid approach that combines the capabilities of OpenCV, Tesseract OCR, and deep-learningbased OCR models helps tackle such challenges as stable images from live video feeds and highly accurate text recognition. To this end, since the system integrates high-resolution frame stabilization using OpenCV to ensure crystal clear captures, it further employs the use of YOLOv8 to boost the precision of real-time detection. The blockchain technology is further implemented to ensure that transactions are tamper proof, therefore ensuring secure and transparent billing systems. This makes the ANPR solution deployable on edge devices, which opens real-time processing capabilities for high-speed and high-volume environments, thereby offering a scalable and efficient approach for intelligent transportation and smart city applications. © 2025 IEEE.

关键词： Blockchain

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Advances in Deep Learning for Tuberculosis Detection in Chest X-Rays: A Review of Diagnostic Accuracy 3

Advances in Deep Learning for Tuberculosis Detection in Ches...

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

作者： Jayakumar, K. Muthupandi, G. Dhayanidhi, R. Pavithra, S. Dept. of Computer Science and Engineering Chennai Institute of Technology Tamilnadu Chennai600069 India

ISBN: (纸本)9798331527549

Tuberculosis (TB) is one of the leading causes of deaths globally, mainly in low- and middle-income countries. Early and accurate detection is crucial for effective treatment and disease control. In this paper, models like CNNs-VGG16, ResNet, and DenseNet, to name a few, are taken into an exhaustive study. Optimization techniques, including transfer learning and ensemble methods, which can increase accuracy in the challenging diverse clinical settings, will be presented. Equitable healthcare outcome is achieved in terms of future research directions which include representative datasets and interpretability of the model. © 2025 IEEE.

关键词： Disease control

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SYSTEMATIZATION OF TRUSTED I/O SOLUTIONS FOR ISOLATED EXECUTION ENVIRONMENTS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and computer science 2022年第2期84卷 3-14页

作者： Stancu, Florin-Alexandru Mircea, Alexandru-Alin Rughiniș, Răzvan Chiroiu, Mihai Dept. of Computer Science and Engineering University POLITEHNICA of Bucharest Romania

Nowadays, operating systems have become increasingly complex, with codebases of millions of lines inadvertently containing security bugs. Modern CPUs promise a solution to this with Trusted Execution technologies (e.g., ARM TrustZone, Intel SGX) which can be employed to isolate critical applications from unauthorized access even from more privileged ac-tors (e.g., system kernel or hypervisor). However, as the traditional way to interface with I/O peripherals is by using drivers part an now-considered untrustworthy OS, separate solutions must be devised to secure user input or output to trusted environments by ensuring an authenticated pathway. Our paper provides a systematization of the available trusted I/O path solutions by reviewing the scientific works in this field and extracting common attributes and differences. We categorize them by supported peripheral type and trusted platform, comparing the usability, security and complexity of their implementations. Finally, we discuss the results and give future directions for improvement. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Virtualization

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Smart Oral Health Monitor 3

Smart Oral Health Monitor

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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Kamkar, Spandana Anilkumar Sanjay, Srushti Vaishnavi, P.S. Karthik, S. Bnm Institute of Technology Affiliated to Vtu Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331515911

Oral health is vital to overall well-being but is often overlooked due to inefficient monitoring tools and delayed diagnosis. This project presents a smart handheld device featuring a miniaturized camera for detecting oral issues like plaque, cavities, teeth discoloration and gum diseases in real-time. Using image processing and deep learning algorithms, the device provides precise feedback and actionable insights. Paired with a mobile application offering detailed analysis and recommendations, it empowers users to adopt proactive oral hygiene practices to prevent teeth disorder. © 2025 IEEE.

关键词： Electronic health record

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Real-Time Network Monitoring: A Big data Approach 14

Real-Time Network Monitoring: A Big Data Approach

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Jaswanth, Kunisetty Sruthi, S. Ramachandrula, Pranav Saravanan, S. Amrita School of Computing Dept. of Computer Science Engineering Bengaluru India Amrita School of Computing Dept. of Computer Science Engineering Chennai India

ISBN: (纸本)9798350335095

Real-time network monitoring is a critical requirement for tracking user activities and ensuring optimal network performance. In this paper, we propose a big data approach to real-time network monitoring that leverages the capabilities of Apache Spark, MongoDB, and Apache Kafka with Python. Our approach utilizes distributed stream processing of network data, enabling real-time analytics for user activity monitoring and network performance optimization. Our approach demonstrates the effectiveness of our system through experiments with real network traffic data, showing how it can identify and track user activities in real-time. Our system can be used by network administrators and IT professionals to optimize network performance, improve user experience, and enhance security through real-time monitoring and analysis of user activity data. This approach can also be opted as a feature in SDNs. © 2023 IEEE.

关键词： Network performance

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Enacting Rural Empowerment: Implementing Cooperative Commerce in Communities using Machine Learning 2

Enacting Rural Empowerment: Implementing Cooperative Commerc...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Skandarsini, R.R. Sangavi, M.S. Harika, Ravitla Varun, C.M. RMK Engineering College Dept. of Computer Science and Business Systems Thiruvallur India

ISBN: (纸本)9798350365269

In order to revitalize rural economies through the empowerment of self-help organizations and the promotion of economic growth, this study offers a revolutionary cooperative commerce platform. The platform integrates cutting-edge features such as digital ledger and inventory management for sellers, demand forecasting, and dynamic pricing, thereby fostering optimized production and efficient marketplaces. Central to the platform's efficacy is the implementation of user segmentation, which categorizes users based on income and spending behaviors, enabling targeted marketing strategies and continuous application improvements to enhance user engagement and profitability. Leveraging machine learning algorithms, personalized user experiences are cultivated, elevating buyer satisfaction and overall engagement. Additionally, administrative tools provide valuable insights for informed decision-making. Preliminary results demonstrate improved financial management for self-help groups, heightened economic activities, and an enriched user-centric experience. Identified challenges and proposed future enhancements underscore the platform's commitment to adaptability and responsiveness to the evolving needs of rural communities, ensuring sustained relevance and impact. © 2024 IEEE.

关键词： Predictive analytics

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Deep Neural Network-Based Approach to Identify the Paddy Leaf Disease using ResNet50-V2

Deep Neural Network-Based Approach to Identify the Paddy Lea...

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2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Islam, Md. Ashiqul Rahman, Md. Mizanur Shohan, Abdul Alim Pulok, Rishad Amin Akter, Sanzida Ahmed, Md. Tanvir Daffodil International University Dept. of Computer Science and Engineering Dhaka Bangladesh East-West University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350313413

South Asian countries especially Bangladesh, India, and Srilanka are very involved in paddy cultivation. In Bangladesh and India, one of the key producing crops is paddy. Worldwide more than 40 percent of the world's population derives most of its calories from rice and traditionally farmers are directly involved production of rice. But every year lot of farmers have to face a tremendous amount of loss due to paddy leaf disease. Major of the farmers do not know how to identify perfectly in the primary stage that's why they are facing loss. Due to the increase in population, it is very important to make paddy cultivation scientific and produce more. There are more than 30 types of paddy leaf disease and from there in Bangladesh, approximately 10 types of disease are quite similar. If it is possible to ensure the leaf disease in the very primary stage within a very short time, then every farmer can reduce their loss. Nowadays many researchers are interested in identifying paddy leaf disease using modern science. In this paper, we worked on paddy leaf disease detection and it has worked on 4 types of disease and 1 healthy and without any disease leaf class of paddy. This paper through an automated detection approach using deep learning techniques achieved the highest accuracy instead of the previous applicable working model and traditional manual disease detection process. In this paper, we have analyzed it using 4 different types of models. ResNet50-V2, Inception-V3, MobileNet-V2, and DensNet-201 algorithm models have been applied here and the finding of the research is, that all the models achieved more than 95% accuracy from these ResNet50-V2 has achieved the best accuracy and it is 99.06%. We hope that these deep learning models and techniques will detect the disease with high accuracy in the very beginning time and it will help reduce damage and loss of paddy cultivation. © 2023 IEEE.

关键词： Deep Neural Network DenseNet-201 MobileNet-V2 ResNet50-V2

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LiDAR-Based Elderly Fall Detection System for Indoor Environments Using Neural Network Algorithms 4

LiDAR-Based Elderly Fall Detection System for Indoor Environ...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Vignesh, Puthucode Ganesh Nithin Kumar, S. Senthil Kumar, T. Jeyakumar, G. Amrita School of Computing Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham India

ISBN: (纸本)9798331523923

Fall detection systems are critical in elderly care and healthcare monitoring, but traditional camera-based solutions raise significant privacy concerns. This research presents a novel approach utilizing LiDAR (Light Detection and Ranging) sensors for fall detection in indoor environments, addressing privacy issues while maintaining high accuracy. We introduce LiFall, a new dataset captured using a Velodyne VLP 16 Puck LiDAR sensor, comprising 12 scenes and over 500 frames simulating various fall scenarios (including back falls, bed falls, and walking falls), contributing to the scarcity of LiDAR-based fall detection datasets. Our methodology employs two advanced deep learning architectures: Annularly Convolutional Neural Networks (ACNN) and Dynamic Graph Convolutional Neural Networks (DGCNN). Evaluating these models on both the ModelNet40 dataset and our custom LiFall dataset, results show DGCNN outperforms ACNN, achieving an accuracy of 84% on the ModelNet40 dataset with a 70:30 train-test split. On the LiFall dataset, despite challenges with dataset imbalance and achieving lower detection accuracy even after data augmentation, our approach demonstrates the potential of LiDAR-based fall detection systems. Compared to other fall detection methods, our LiDAR-based system offers significant advantages beyond privacy preservation, such as robust performance in low-light conditions and the ability to capture detailed 3D spatial information. While our current implementation is limited to laboratory settings, future work will focus on real-world deployments and further addressing dataset imbalance issues to enhance overall system performance. This research contributes to the field by providing a privacy-preserving, high-performance alternative to camera-based fall detection systems, paving the way for more acceptable monitoring solutions in sensitive indoor environments. © 2025 IEEE.

关键词： Fall detection

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Distinguish between Obese and Normal Body Types Through Gait Analysis Using Classification Models 6

Distinguish between Obese and Normal Body Types Through Gait...

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6th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2024

作者： Yi, Jae-Sik Han, Ji Hun Kim, Min Jeong Hong, Youn-Sik Incheon National University Dept. of Computer Science and Engineering Incheon Korea Republic of

ISBN: (纸本)9798350344349

For gait analysis, an IMU sensor was mounted on the knee and gait related data was collected. Various gait parameters such as gait time, stance swing ratio, heel strike, and toe off can be extracted from the dataset. To explore the relationship between gait parameters and individual gait characteristics, we analyzed the gait patterns of normal and obese people were analyzed based on BMI (Body Mass Index). To apply it to a classification model of machine learning, different gait cycles between subjects were normalized. Gait data was collected from eight subjects in their 20s. Using this dataset, we applied a logistic regression model, and obtained the classification accuracy of 92%. We also investigated the correlation between BMI and gait parameters and found that, the correlation between BMI and cadence was-0.66. © 2024 IEEE.

关键词： Gait analysis

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Securing of Cloud Storage data Using Hybrid AES-ECC Cryptographic Approach

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Journal of Mobile Multimedia 2023年第2期19卷 363-388页

作者： Kumar, Sunil Kumar, Dilip Dept. of Computer Science and Engineering National Institute of Technology Jamshedpur India

Internet has revolutionized the world in a way no one could have ever imagined. It paved the way for various different technologies, that have transformed the world exceptionally. Internet enabled cloud technology which provides cost-effective, scalable, on-demand computing resources with little to no downtime. Cloud storage allows its users to store and access private data from anywhere in the world without needing any high-end computing system. Cloud storage isn’t always secure, but that doesn’t imply it isn’t. The security of a data depends on the security policies followed by the provider along with the security of the communication channel via which the data is being sent. Encryption is used to obfuscate the data so that it can only be viewed when correct credentials, known as encryption keys, are provided. Following study proposes an encryption technique using ECC (Elliptic Curve Cryptography) along with AES (Advance Encryption Standard) to provide data confidentiality in an efficient way for securing data on cloud and hence, protect the personal information of user from any adversary. This new method is more effective, and the results are superior as a consequence. © 2022 River Publishers.

关键词： AES asymmetric encryption authentication blowfish cloud storage security ECC Symmetric encryption

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