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

作者： Mihir, D.V.S. Pavan, Baramkula Vishnu Datta Aralaguppi, Yogen Avinash Nair, Pranav Biju Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Monitoring of environmental parameters in areas with a sparsely populated and less infrastructure is quite challenging due to issues such as high power consumption, limited range for transmission, and lack of scalability. The innovation of the system proposed here deals with these problems using an IoT-based monitoring system, using LoRa technology and NodeMCU microcontrollers. It can collect and transmit real-time data on temperature, humidity, air quality, and sound levels efficiently. Key outcomes of this research work are reliable range communication up to 2 km under line-of-sight conditions, minimal power consumption, and robust data integrity through sensor calibration and error-checking mechanisms. The solution, which is scalable and low-cost, is proven feasible in real-world applications, particularly in remote and underserved areas, and promises a great future enhancement, including range extension and energy harvesting. © 2025 IEEE.

关键词： Environmental monitoring

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Securing Wireless Communication: A Comprehensive Arduino-based Approach 3

Securing Wireless Communication: A Comprehensive Arduino-bas...

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

作者： Navaneeth, M. Vamsi Krishna, K. Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This research aims at developing Arduino solutions to improve the security of wireless communication systems for this work and to present a broad intervention plan for achieving this aim. Incorporating the features of Arduino microcontrollers the system has the potential of mitigating some of the weak wireless communications paradigms. The methodology consists in applying the use of such measures as the encryption algorithms and authentication and the use of secure data transmission protocols. The approach, proposed, not only enhances the security of wireless communication but also is cost effective and easy to install. In this respect, it is hoped that the outcomes of the project will offer effective and efficient solutions for implementing quality security elements for wireless transmission with practical and experimental *** purpose of this work is to generate and transmit the text message through a wireless communication system in a secured way. This facility prevails in the mobile network for which the user pays for it, whereas the system designed here can be used as personal communication system and information can be transmitted at free of *** result of the work is expected to be a secure information transmission with wireless technology implemented and encrypt the data that need to be transmitted without letting interception of a third party and reach the destination, convert and decrypt the message into readable *** work more particularly targets at reducing some of the risks associated with present wireless communication systems through use of effective encryption and authentication. The results are expected to include a major decrease in the interception risks, as well as the effective and safe text message transmission with real-world evidence as proof. © 2025 IEEE.

关键词： Microcontrollers

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Fall Detection using LiDAR Sensor with PointNet++ 4

Fall Detection using LiDAR Sensor with PointNet++

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

作者： Ayyagari, Anish Sai Ahmed, Syed Ashfaq Venkatakrishnan, Shri Thangavel, Senthil Kumar Jeyakumar, G. Nalluri, Madhusudana Rao Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9798331523923

In today's world, fall incidents pose a significant risk to the elderly, often resulting in severe consequences. Falls can cause damage to the body, especially in elders, where it can be *** is vital to detect falls in order to provide assistance. The simple solution is to install cameras in required areas, which would constantly monitor the area for any falls occurring, this poses a privacy issue in high-risk regions such as bathrooms and toilets. Keeping this in mind, this paper proposes the use of LiDAR sensors that do not cause any invasion of privacy for fall detection. The paper further uses the Pointnet++ to detect fall from the LiDAR scans. The model achieves an accuracy of 85.1 % and precision of 84.8 % on a 70-30 split of the dataset and an accuracy of 86.3 % and precision of 86.2 % on an 80-20 split of the dataset. © 2025 IEEE.

关键词： Fall detection

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IoT Environmental Monitoring with Anomaly Detection 3

IoT Environmental Monitoring with Anomaly Detection

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

作者： Abhiram, D. Dhanush Reddy, K. Koushik Reddy, P. Rajagopal, Shinu Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bangalore India

ISBN: (纸本)9798331527549

This project proposes an IoT-based environmental evaluation system taking into consideration its surroundings through a microcontroller ESP8266 and sensor DHT11. The system reads the current temperature and humidity in addition to providing alerts for changes as well as threshold and sensor integrity issues. It contains context awareness and adaptive monitoring. It connects to the Arduino IoT Cloud, which allows users to monitor data in real-time, or receive notifications, or set up thresholds right from the mobile or web application. The features such as real-time monitoring, real-time anomaly detection, and remote access make this project practical as the key application for smart homes, farming and industries applications. © 2025 IEEE.

关键词： Microcontrollers

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Federated Learning based Gender Classification in Heterogeneous and Distributed Data having Concept Drift 4

Federated Learning based Gender Classification in Heterogene...

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4th International Conference on Evolutionary computing and Mobile Sustainable Networks, ICECMSN 2024

作者： Sharma, Vishwash Reddy Challa, Venkatahemant Kumar Pranavi, Pasupuleti Singh, Rimjhim Padam Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

Federated Learning is gaining significant traction in recent times, due to its ability to protect privacy while giving comparable results across various use cases. However, it often falls short in delivering good results in scenarios where the client devices at different places store huge and heterogeneous data. The studies explore the effectiveness of federated learning, when utilized for model training on heterogeneous data having concept drift nature and being placed on different client devices. The paper proposes a novel combination of EfficientNet-B0 model fine-tuned with adaptive and weighted normalization layers in a federated learning setup for gender classification in heterogeneous Fairface dataset having human images from different races. Several other Convolutional Neural Network (CNN) models namely, ResNet50, DenseNet121, GoogLeNet, AlexNet etc. have also been trained in different traditional and federated setups. Experiments revealed that EfficientNet-B0 outperformed the other models trained in all the scenarios with an outperforming accuracy of 88.18% in the traditional federated setup and 90.56% when fine-tuned using normalization methods and evaluated in a federated setup with four client devices. These findings highlight the potential of normalization techniques to improve the effectiveness of federated learning, especially when dealing with concept drift data. © 2025 The Authors. Published by Elsevier B.V.

关键词： Federated learning

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Scheduling Policies in Edge computing for Real-Time Video Analytics 3

Scheduling Policies in Edge Computing for Real-Time Video An...

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

作者： Shreevatsan, S.S. Annambhotla, Yasasree Lasya Reji, Anaswara Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This study compares different scheduling algorithms used in edge computing for real-time video processing. Instead of sending video data to cloud servers, the video is processed directly at the edge, reducing delays and saving bandwidth. The focus is on how different scheduling methods manage resources, prioritize tasks, and reduce the time it takes to analyze video. The algorithms are tested in simulated environments to understand how they impact system efficiency and performance. The goal of this work is to find the best scheduling policies for real-time video processing at the edge, improving overall system performance and scalability. © 2025 IEEE.

关键词： Scheduling algorithms

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Smart Water Ball Launcher: An Arduino-based Fire Extinguishing System 3

Smart Water Ball Launcher: An Arduino-based Fire Extinguishi...

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

作者： Sridhar, Govindu L.V.N. Janakiram, M. Vishnu Ram Sai, M. Surya Narayana Reddy, G. Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

The proposed work offers the production of an Arduino controlled Fire-RoboCar equipped with a water ball launcher. In a world dominated by human-machine interaction in industry, the efficiency of any task to be done is promoted by this proposed work and delivers solutions to needs like fighting fires through the provision of a productive method. At a time when increased pollution and the expense of fossil fuel are becoming very high, this alternative is environment-friendly. The Fire-RoboCar is a moving robot that can accomplish fire extinguishing tasking in an industrial complex, proving that the system may easily transport water to desired locations. This proposed work advances robotic vehicles’ capabilities and provides innovative solutions to modern industrial challenges. © 2025 IEEE.

关键词： Fire extinguishers

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Blockchain based File Storage and File Sharing System with Time-Restricted Access using InterPlanetary File System 3

Blockchain based File Storage and File Sharing System with T...

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

作者： Venkat Prashanth, M. Hemesh Verma, K. Chauhan, Jaykishor Prasad Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bangalore India

ISBN: (纸本)9798331527549

This paper presents a file storage and sharing system implemented using IPFS Pinata, *** and Hardhat which offer decentralized, effective, and secure access to digital assets. This system also enables the ability to upload files to the IPFS network for distributed storage and the ability to share them with peers . It also implements a time based access control system using smart contracts to easily control access to the files uploaded. This innovation improves security and facilitates timely exchange of information while also eradicating the necessity of having to manage access. This is due to the versatility of blockchain’s unalterable nature together with IPFS distributed file-sharing system which provides a secure file-sharing method while keeping costs low and helps maintain adaptability. © 2025 IEEE.

关键词： Blockchain decentralized IPFS secure access Time Based Access Conrol

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Predicting and Evaluating Anomaly Detection and Traffic Analysis on Software Defined Networks Using a Hybrid Machine Learning Approach 5th

Predicting and Evaluating Anomaly Detection and Traffic Anal...

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5th International Conference on computing and Network Communications, CoCoNet 2023

作者： Darshan, S. Radhika, N. Radhika, G. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9789819745395

In the rapidly evolving landscape of Software Defined Networks (SDNs), network security is of paramount importance. This research paper presents a comprehensive study on anomaly detection and traffic analysis in SDNs using machine learning algorithms. The study addresses a critical research gap by proposing an effective methodology for detecting network anomalies and analyzing traffic patterns. Leveraging a carefully selected dataset, we evaluate the performance of Logistic Regression, Decision Tree, Random Forest, Neural Networks and Hybrid Models. The results demonstrate the superior performance of the hybrid model built using Decision Tree and Neural Networks and the competitive accuracy of Neural Networks in SDN anomaly detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Innovative Video Classification Method based on Deep Learning Approach

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Recent Patents on engineering 2025年第2期19卷 95-107页

作者： Hemamalini, V. Jayasutha, D. Vinothini, V.R. Devi, R. Manjula Kumar, A. Anitha, E. Department of Networking and Communications School of Computing SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering Arjun College of Technology Coimbatore Thamaraikulam India Department of Mathematics Bannari Amman Institute of Technology Sathyamangalam Erode638401 India Department of Computer Science and Design Kongu Engineering College Perundurai Erode638060 India Department of Civil Engineering University Institute of Engineering & Technology Maharshi Dayanand University Rohtak124001 India Department of Artificial Intelligence and Data Science Sri Eshwar College of Engineering Coimbatore641202 India

Background: The automated classification of videos through artificial neural networks is addressed in this work. To explore the concepts and measure the results, the data set UCF101 is used, consisting of video clips taken from YouTube to recognize actions. The study is carried out with the authors' resources to determine the feasibility of independent research in the area. Methods: This work was developed in the Python programming language using the Keras library with Tensorflow as the back-end. The objective is to develop a network that presents performance compatible with the state of the art in terms of classifying videos according to the actions taken. Results: Given the hardware limitations, there is considerable distance between the implementation possibilities in this work and what is known as the state-of-the-art. Conclusion: Throughout the work, some aspects in which this limitation influenced the development are presented, but it is shown that this realization is feasible and that obtaining expressive results is possible 98.6% accuracy is obtained in the UCF101 data set, compared to the 98 percentage points of the best result ever reported, using, however, considerably fewer resources. In addition, the importance of transfer learning in achieving expressive results as well as the different performances of each architecture are reviewed. Thus, this work may open doors to carry patent-based outcomes. © 2025 Bentham science Publishers.

关键词： Convolutional neural networks

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