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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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2016 ieee 3rd International Symposium on Wireless systems within the ieee International Conferences on intelligent data acquisition and advanced computing systems, IDAACS-SWS 2016 - Proceedings

2016 IEEE 3rd International Symposium on Wireless Systems wi...

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3rd ieee International Symposium on Wireless systems within the ieee International Conferences on intelligent data acquisition and advanced computing systems, IDAACS-SWS 2016

ISBN: (纸本)9781509043163

The proceedings contain 24 papers. The topics discussed include: NS3 simulation studies for optimized neighbor discovery in 6LoWPAN networks;integration and analysis of an extended ieee 802.15.4 modules with smartMAC and wake-on-radio functions into the network simulator NS3;automatic signal strength map construction in indoor positioning system based on round trip time of flight measurements and inertial navigation;non disjoint set covers approach for wireless sensor networks lifetime optimization;the multi-mode inertial tracking system for unconstrained indoor positioning;high Q impedance matching for RF energy harvesting applications;backhaul infrastructures in building automation systems: wired or wireless?;and radio module for fast real-time control of inverse triple pendulum.

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Privacy and Security Concerns in Edge-Cloud systems: An In-Depth Analysis 3

Privacy and Security Concerns in Edge-Cloud Systems: An In-D...

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

作者： Kaki, Samuel Suhas Kantareddygari, Jagadeswara Reddy Aishwarya, R. School of Computing Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9798331527549

Edge-Cloud systems provide efficient computation and storage close to data sources, with lower latency, scalability, and application performance for various applications, such as IoT, autonomous vehicles, and real-time analytics. These systems are highly vulnerable to significant security and privacy challenges, which include the following: data confidentiality and integrity in the process of transmission, secure protection of sensitive data stored on the edge against physical and remote attacks, and maintaining availability under dynamic network conditions. More challenges related to ensuring users' private nature through anonymizing data, obtaining consent for all processes involved, and compliance with specific regulations like GDPR and CCPA. This work incorporates more enhanced cryptographic methods in the transfer of data between heterogeneous systems and environment-based anomaly detection, advanced privacy-preserving analytics to avoid extraction of private data, adaptive control mechanisms in place for Edge-Cloud for minimizing vulnerability with enhanced trust along with the maintenance of data integrity. The key benefits would be robust mitigation of threats, better interoperability between edge and cloud platforms, and alignment with evolving security standards, which promotes wider adoption across various sectors. © 2025 ieee.

关键词： Cloud platforms

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Blockchain-Enhanced data Integrity and Authentication in WSN-IoT systems for Dynamic Spectrum Access 3

Blockchain-Enhanced Data Integrity and Authentication in WSN...

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3rd International Conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Tuteja, Gaurav Rani, Shalli Sharma, Ankita Nasra, Parul Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

ISBN: (纸本)9798331515911

Wireless Sensor Networks (WSN) that work hand in hand with IoT are crucial for contemporary smart city solutions. However, as these are dynamic and decentralized, they pose additional issues related to network data and authentication. Therefore, the deep analysis of blockchain technologies in WSN-IoT to improve the data integrity and authentication of the systems is proposed in this paper. Based on the consensus mechanisms and the tamper-proof nature of the blockchain ledger, the proposed method is effective in managing the cognitive radio spectrum access. This paper also seeks to discuss previous methods, their inefficiencies, and potential enhancement through the application of blockchain based on various performance metrics. © 2025 ieee.

关键词： data integrity

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A Review of Signature Schemes for Enhanced Information Retrieval and Privacy in Blockchain systems 3

A Review of Signature Schemes for Enhanced Information Retri...

引用

3rd International Conference on intelligent systems, advanced computing, and Communication, ISACC 2025

作者： Sheikh, Mustak Kalita, Chandan Gauhati University Department of Information Technology Guwahati India

ISBN: (纸本)9798331523893

Blockchain technology has revolutionised data sharing and storage by offering decentralised, impenetrable solutions in a variety of fields. But because of its intrinsic transparency, there are serious privacy issues, especially when handling sensitive data. To improve information retrieval and protect user privacy in blockchain systems, this paper offers a thorough analysis of many cryptographic signature algorithms. It looks at the advantages and disadvantages of current strategies, highlights important obstacles, and talks about possible fixes to privacy issues. This paper also provides a comparative evaluation of related works according to criteria like security, scalability, and efficiency. The knowledge acquired aids in the creation of privacy-protecting techniques that maximise data retrieval in blockchain-based applications. © 2025 ieee.

关键词： Blockchain Digital Signatures Information Retrieval Privacy Preservation Security

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AK-Medoids-based Framework for Traffic Monitoring in Low Illumination Conditions 3

AK-Medoids-based Framework for Traffic Monitoring in Low Ill...

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

作者： Ganesh Ram, R. Joshua Samuel, P. Vigneshwaran, V. Rajagopal, S. National Engineering College Kovilpatti India

ISBN: (纸本)9798331527549

A novel unsupervised framework employs YOLOv4 (You Only Look Once, Version 4) to enable real-time object detection on roadways, significantly enhancing intelligent traffic monitoring. The system efficiently identifies vehicles, pedestrians, and other road objects in various challenging conditions, such as low-light environments, varying weather, and high-traffic density. By adopting an unsupervised approach, the framework eliminates the need for large labeled datasets, ensuring scalable deployment across diverse road networks. With integrated difference image analysis and K-medoids clustering, the framework boosts detection accuracy, achieving an impressive 92% detection accuracy—representing a 7% improvement over YOLOv4 and a 12% improvement over YOLOv3. Difference images highlight significant frame-to-frame changes, essential in low-illumination scenarios, while K-medoids clustering refines object grouping and reduces detection noise. These techniques complement YOLOv4’s object detection capabilities, providing a robust solution for real-time monitoring. With edge computing for low-latency performance, the system is well-suited for large-scale deployment in intelligent Transportation systems. By combining unsupervised methods with advanced object detection, this framework delivers a scalable, efficient, and adaptive solution for continuous traffic monitoring, contributing to improved road safety. © 2025 ieee.

关键词： intelligent systems

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Next-Generation Intrusion Detection systems with Machine Learning and Deep Learning-Based Firewalls 3

Next-Generation Intrusion Detection Systems with Machine Lea...

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3rd International Conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Rani, Ritu Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798331515911

The growing complexity of cyber-attacks has underlined the requirement of strong Intrusion Detection systems (IDS) able to instantly recognize a variety of hazards. This work offers a strategy for improving Next-Generation Intrusion Detection systems (NGIDs) combined with firewalls by use of machine learning (ML) and deep learning (DL) approaches. Using the NSL-KDD dataset - which includes both normal and attack network traffic - the work creates a system able to classify traffic patterns into "Normal"and "Attack"categories. The proposed method consists in four phases: data collecting, data preprocessing, feature selection and extraction, and classifier application. In the preprocessing stage, the dataset is cleaned and normalized;hence, suitable feature selection follows to increase classification accuracy. Trained and tested for classification using performance criteria including accuracy, precision, recall, and F1-score, naïve bayes and support vector machine (SVM) models are then compared in efficacy. The results reveal that the SVM classifier has low misclassification and great accuracy (97.29%), therefore proving its prospective use in advanced IDS. The article underlines how several models could be merged inside a firewall system to offer real-time network protection. Future studies will look at using deep learning techniques and ensemble methods to raise detection accuracy even more, therefore allowing NGIDS to be more adaptable and efficient in countering evolving cyber threats. © 2025 ieee.

关键词： Network intrusion

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Real-Time Object Detection for an intelligent Retail Checkout System 3

Real-Time Object Detection for an Intelligent Retail Checkou...

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3rd International Conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, IITCEE 2025

作者： Vaneeta, M. Mugada, Swathi Patil, Prachi Bhausaheb Preethi, V.J. Deeksha, K. M.S.Ramaiah Institute of Technology Department of Artificial Intelligence & Data Science Bangalore India

ISBN: (纸本)9798331515911

Customers are made to wait for extended hours in busy shopping settings as traditional limits of barcode and RFID-based billing systems have a predisposition towards errors and inefficiencies in scanning untagged or weighted items. The methods that are in use today can't keep up with the demand and lead to queues at check-out counters causing customer discontentment. This paper presents an idea of a novel Smart Billing Counter, based on Object Detection using advanced deep learning, YOLOv8, and OCR technologies for smooth billing processes. It captures the image of items placed at the counter, identifies what it is with minimal error, extracts necessary information from labels concerning weighted items, and generates a bill automatically. The unique capability of this solution is to recognize identical items in one frame with total cost by quantity to optimize checkout times and minimize the possibility of errors or fraud. At an inference speed of 37.2ms per image with 93.6% accuracy, this significantly enhances operational efficiency and ensures that grocery retailers provide their customers with smooth, error-free, and swift checkout processes. This innovation is likely, therefore, to bring about a transformation in retail billing systems. It will enhance customer satisfaction and operations efficiency quite highly. © 2025 ieee.

关键词： Sales

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Internet of Things Cloud-based System for Continuous Heart Disease Management and Diagnosis using intelligent Neuro-Fuzzy systems and Improved Imperialist Competitive Algorithm 3

Internet of Things Cloud-based System for Continuous Heart D...

引用

3rd International Conference on Electronics and Renewable systems, ICEARS 2025

作者： Shalini, K. Rani, M. Pushpa Mother Teresa Women's Tamilnadu Kodaikanal India Mother Teresa Women's University Department of Computer Science Kodaikanal India

ISBN: (纸本)9798331509675

This research aims to develop an Internet of Things (IoT) cloud-based system that integrates intelligent neuro-fuzzy systems and the IICA for continuous health monitoring and timely medical interventions. The objective is to provide personalized care for elderly patients and improve the accuracy and efficiency of heart disease diagnosis. The research problem addresses the limitations of traditional healthcare systems in managing heart disease. Many systems cannot provide continuous monitoring and timely medical responses. This gap leads to ineffective management of heart disease, especially among the elderly. Existing systems often fail to optimize feature selection and parameter tuning, which are crucial for accurate diagnosis. Manual methods for these tasks result in suboptimal performance and reduce the reliability of diagnosis. The precision of the proposed system can be enhanced by improving data quality, optimizing the neuro-fuzzy system, and refining the IICA. The proposed method integrates several advanced technologies, including IoT devices, cloud computing, intelligent neuro-fuzzy systems, and IICA. IoT devices collect real-time health data from patients, which is transmitted to the cloud for storage and processing. The intelligent neuro-fuzzy system analyzes the health data using neural networks and fuzzy logic. IICA optimizes the system's parameters to enhance accuracy and reliability. This integrated approach ensures continuous health monitoring and quick response to health changes. The results show that the proposed system significantly improves the accuracy of heart disease diagnosis. The system achieves an accuracy of 97.0%, precision of 96.2%, and recall of 96.8%. These metrics demonstrate the effectiveness of the system in providing reliable health monitoring and accurate diagnosis. © 2025 ieee.

关键词： Electronic health record

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Recommendation System using Emotion Detection 3

Recommendation System using Emotion Detection

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

作者： Susindra, S. Sweta, B. Keerthikha Shri, R. Brindha, K. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798331527549

The need for a personalized user experience brought recommendation systems to the forefront of digital innovation. However, traditional approaches tend to often forget human emotions, which represent a critical driver in decision making. The paper proposes a new framework in which the detection of emotions becomes part of the recommendation system through advanced facial expression analysis and sentiment evaluation. The paper discusses a hybrid architecture combining emotion recognition via CNN and a collaborative filtering technique for dynamic recommendations. The study outcome demonstrated an enormous improvement in user engagement and satisfaction. It further underlines the transformative potential of emotion-aware systems. © 2025 ieee.

关键词： Emotion Recognition

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An intelligent Disaster Management System: Integrating Technology for Effective Response and Recovery

An Intelligent Disaster Management System: Integrating Techn...

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3rd International Conference on intelligent systems, advanced computing, and Communication, ISACC 2025

作者： Pandey, Nandini Rani, Priya Kundu, Sumana Dr. B. C. Roy Engineering College Department of Computer Science and Engineering Durgapur India

ISBN: (纸本)9798331523893

This proposed Disaster Management System (DMS) is an advanced application aimed to improve disaster preparedness, response, and recovery efforts through real-time data integration, predictive analytics, and efficient communication. It leverages Artificial Intelligence to predict disasters like earthquakes and floods, providing early alerts and resource management to minimize impact. Key features include role-based access, geolocation tracking, incident reporting, and multilingual support. DMS facilitates coordination between government agencies, NGOs, and volunteers, ensuring rapid response and effective resource allocation. With future integration of IoT and blockchain technologies, the system aims to enhance transparency, optimize resource distribution, and support international disaster management efforts. By integrating real-time data, predictive analytics, and communication tools, this system supports efficient coordination during emergencies. © 2025 ieee.

关键词： AI in disaster response blockchain technology Disaster Management System predictive analytics real-time data

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