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检索条件"任意字段=3rd IEEE International Conference on e-Science and Grid Computing"

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A Game Theory-based Reverse Vickrey Auction for Dynamic Pricing in edge computing 3

A Game Theory-based Reverse Vickrey Auction for Dynamic Pric...

引用

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

作者： Rasane, Atharva Tapale, Manisha Dept. Computer Science and Engineering KLE Technological University’s Dr. M. S. Sheshgiri College Belagavi India

ISBN: (纸本)9798331527549

Low-latency communication is critical for effectively functioning Internet of Things (IoT) systems, including applications in healthcare monitoring, industrial automation, and smart cities. However, the vast number of IoT Devices often overwhelms cloud providers, necessitating the adoption of edge computing to reduce latency and distribute computational load. This paper introduces a novel dynamic pricing mechanism for edge computing based on a reverse Vickrey auction, leveraging game theory to balance competitive pricing with profitability for edge Servers. We develop utility functions for both IoT Devices and edge Servers, optimizing the markup to maximize edge server utility while adhering to the budget constraints of IoT Devices. Simulations were conducted with 10 edge Servers and 50 IoT Devices over 2,000 time units. Results show that the proposed mechanism significantly reduces wait times, with most tasks completed within 10-time units. Moreover, dynamic pricing increases edge Server profits by up to 10 times in some instances compared to fixed markup approaches. Notably, one server’s total profit rose from 7,702 to 76,130 and another from 57,965 to 94,298, underscoring the enhanced profitability and utilization. These findings confirm that our reverse Vickrey auction strategy effectively balances low-latency demand with sustainable operational revenue for edge Servers, offering a robust and scalable solution for edge-centric IoT environments. © 2025 ieee.

关键词： Budget control

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Design of energy efficient SRAM Based In Memory computing 3

Design of Energy Efficient SRAM Based In Memory Computing

引用

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

作者： Roshna, M.R. Suresh Kumar, e. College of Engineering Trivandrum Department of Electronics and Communication Thiruvananthapuram India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508456

As the gap between processing speed and memory bandwidth widens, In-Memory computing (IMC) has emerged as a vital approach to achieve energy-efficient and high-performance computing. The traditional Von Neumann architecture separates memory from computation (CPU/GPU). This research proposes an innovative SRAM-based IMC architecture as a potential solution to the Von Neumann bottleneck. By integrating computational capabilities directly within the memory, this architecture minimizes data movement between memory and processing units, leading to significant reductions in energy consumption and latency. The design features a novel SRAM based IMC, capable of performing all basic Boolean functions within the memory array. This work presents a promising solution for next-generation computing systems, where energy efficiency and high performance are critical requirements. The project utilizes SCL 180nm CMOS technology to implement the proposed SRAM-based IMC architecture. © 2025 ieee.

关键词： Static random access storage

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Dual-Plate Verification System for Vehicle Identifcation using IoT and embedded Systems 3

Dual-Plate Verification System for Vehicle Identifcation usi...

引用

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

作者： Sampath, A.V.S.S. Malagati, Nischal S. Kanapathi, V. Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This research uses a dual-plate verification system for improving vehicle security by using IoT and embedded systems. The system compares front and rear license plates to detect any anomaly, which signals unauthorized modifications. Using real-time image processing and IoT-based data communication, this solution gives us an accurate plate matching system, making sure of reliable vehicle identity verification. Its possible applications include traffic monitoring, parking management, and detecting any unlawful activity. This project is unique because it integrates the dual plate verification system with an Arduino IoT setup. For hassle-free text recognition, this system uses deep learning frameworks combined with a wireless mobile setup that serves as a camera. The system’s accuracy is shown through experiments, displaying its value in improving transportation security with automation. The number plates were detected, and the respective penalties for the vehicles were imposed accordingly. © 2025 ieee.

关键词： Anomaly detection

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Sentiment Analysis on Telugu Text Translated from english using NLP and ML 3

Sentiment Analysis on Telugu Text Translated from English us...

引用

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

作者： Karthik, A.H.N. Aneesh, Ch. Saumik, Gembali Varun, K.V.V. Kavitha, C.R. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This research study mainly uses Natural Language Processing (NLP) and Machine Learning. The general approach of this tool is to apply sentiment analysis in Telugu Text translated from english. The Technique contains many preprocessing steps, for example, tokenization of texts, normalization and noise removal for translating english text into Telugu which then will use machine translation services. It is followed by sentiment analysis of the statement using NLP models and machine learning approaches and classified them as;positive, negative, or neutral. The main objective of this study is to enhance the accuracy of sentiment identification with non-english language. environments and also to develop rigorous sentiment analysis tools optimized for Telugu, which are designed as to the language and context-related difficulties to be taken into account. Additionally, the research examines analyses the impact of bilingual datasets on increasing translation accuracy and sentiment classification, while also tackling the obstacles given by idiomatic idioms and context-specific interpretations in Telugu Language. © 2025 ieee.

关键词： Machine translation

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IoT-based Door Automation and Smart Health Monitoring System 3

IoT-based Door Automation and Smart Health Monitoring System

引用

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

作者： Chaurasiya, Ruchi Yadav, Shakshi Malik, Swagata Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This project presents the design of an automated access control system that aims to enhance security through the use of an ultrasonic motion sensor and a live heartbeat check. This system makes use of an ultrasonic sensor which detects any motion within a certain radius directing a signal to the controller based on Arduino. The controller is able to communicate with a script written in Python that queries API for the pulse of the user in question. Using these parameters,the system compares the real-time heartbeat of the pulse taken against the thresholds set *** the parameters exceed the range,the control unit within the Arduino will trigger the servo to unlock the door. Another scenario the parameters are within range,the door will remain closed. Such a system is able to increase the control measures in biological information system as it enables people to open the door while maintaining their hands free. The outcome demonstrates that by combining simple hardware components with data processing techniques, a reliable and secure automated access system can be created with minimal manual intervention, improving security while ensuring ease of use. © 2025 ieee.

关键词： Access control

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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...

引用

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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Li-Fi enabled Gas Detection: A Novel Approach for Navy Ship Safety 3

Li-Fi Enabled Gas Detection: A Novel Approach for Navy Ship ...

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

作者： Ashwanth, G.P.N. Reddy, Gajjala Venkat Rushith Abhiram, Prayaga Shashank Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

The major risk of gas leakages to naval ships and vessels is to both personnel and machinery. Traditional types of gas detectors use fixed wired sensors, which tend to be extremely challenging for maintenance in complex ship contexts. This work addresses applying Li-Fi technology for successful wireless detection of gas leaks. Li-Fi has been employed to measure the gas level in real time, hence enabling fast reaction in case of possible leaks or damage. The foundation of this project is to establish a LiFi-driven communication system in areas where Radio Frequency(RF) communication is restricted and provides safer and more reliable detection system for navy ships. Preliminary results show that in this Li-Fi-based system, accurate real-time gas detection with high speed data transfer in RF challenged environments should be possible. This type of approach not only will increase response times but the need for vast wiring diminishes, hence enhancing effectiveness in maintenance and operational dependability in complex ship spaces. © 2025 ieee.

关键词： Warships

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Integration of Traffic Shaping with Time-Sensitive Networking for effective Traffic Management 3

Integration of Traffic Shaping with Time-Sensitive Networkin...

引用

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

作者： Penumada, Archana Reddy Gundapaneni, Divya Jyothi Chennupati, Akshitha Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Time-Sensitive Networking (TSN) has recently become an important standard to support time-sensitive reliable low-latency data transmission in industrial and real-time applications. This work explores the use of different traffic shaping algorithms, namely, credit-based shaping (CBS) and time-aware shaping (TAS) alongside frame preemption—a TSN instance which gives precedence to high-importance frames by means of lower-priority traffic interruption—to extend TSN’s traffic management capabilities. By controlling data flow and allowing for high priority packets to pass through unimpeded, traffic shaping algorithms serve an essential function in making the network more efficient and reducing congestion rates. The work compares these algorithms in isolation and also in combination over a network model, comprising of four switches and three end users for each switch, using the OMNeT++ simulation environment. This study aims to contribute insights into optimal shaping techniques for TSN, enhancing its suitability for critical network applications. © 2025 ieee.

关键词： Traffic congestion

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AI-based Pneumonia Detection using a Deep Context Axial Reverse Capsule Neural Network with Sea-Horse Optimizer 3

AI-based Pneumonia Detection using a Deep Context Axial Reve...

引用

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

作者： Mohideen AbdulKader, M. Tuteja, Ankush Joshi, Darsh Tholath, Joshua Bobby Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Tamilnadu Chengalpattu India

ISBN: (纸本)9798331527549

Pneumonia detection with AI uses advanced deep learning algorithms for identifying the patterns in the chest X-ray images which makes diagnosis faster and efficient for physicians. AI-powered radiography improved the diagnostic approaches, even then existing methods face some limitations such as reduced accuracy and high computational costs. The Deep Context Axial Reverse Capsule Neural Network with Sea-Horse Optimizer (ADpCARCNNet+SHO) for pneumonia detection is proposed to overcome these challenges. This framework processes chest X-ray images from the Chest X-ray 14 dataset, beginning with Color Wiener Filtering (CWF) for noise reduction. Key features are then extracted using the Dynamic Range Quantized Discrete Haar Wavelet Transform (DRQDHWT), followed by classification using the ADpCARCNNet, optimized with the Sea-Horse Optimizer (SHO) to ensure high precision. Proposed method achieves a remarkable 99.9% accuracy on the Chest X-ray 14 dataset, outperforming existing techniques. The results demonstrate improved diagnostic accuracy, faster image analysis, enhanced reliability, and reduced computational cost, highlighting the potential of the ADpCARCNNet+SHO framework for efficient and reliable AI-driven pneumonia detection. © 2025 ieee.

关键词： Diagnostic radiography

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Optimization of Power Distribution Network Dispatching Auxiliary Decision-Making and Intelligent Ticketing System Based on PPO Algorithm 3

Optimization of Power Distribution Network Dispatching Auxil...

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

作者： Qiu, Zejian Shao, Weitao Han, Zhanvuan Mei, Aoqi Wang, Zhengqing Guangdong Power Grid Corp Dongguan Power Supply Bureau Dongguan China

ISBN: (纸本)9798331508456

The existing intelligent ticketing system has problems such as insufficient automation, weak dynamic adaptability, and limited ability to cope with complex fault scenarios. Based on the PPO algorithm, this paper designs and implements an improved intelligent ticketing system. This paper introduces a graph neural network (GNN) to model the power grid topology, so that the system can dynamically generate operation tickets based on the multi-dimensional state of the power grid. Combined with the exploratory and adaptive nature of the PPO algorithm, it autonomously learns and optimizes the process of generating operation tickets under a changing dispatching environment to reduce the risk of misoperation. In the load experiment, the dispatch success rate of the PPO algorithm under low and medium loads reached 96.5% and 95.3% respectively, maintaining a fast response;under high load, the success rate dropped slightly to 91.8%, but it can still meet the real-time requirements. The fault experiment shows that the success rate of PPO is 98.2% in single-point failures and slightly decreased to 92.5% in multi-point failures, but it has strong robustness. The system achieves a balance between efficiency and safety in complex dispatching tasks. © 2025 ieee.

关键词： Graph neural networks

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