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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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Cost-Effective Edge Data Caching With Failure Tolerance and Popularity Awareness

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IEEE Transactions on Mobile computing 2025年第6期24卷 5357-5369页

作者： Luo, Ruikun Zhang, Zujia He, Qiang Xu, Mengxi Chen, Feifei Dai, Xiaohai Wu, Song Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan430074 China Deakin University School of Information Technology GeelongVIC3125 Australia

In the mobile edge computing environment, caching data in edge storage systems can significantly reduce data retrieval latency for users while saving the costs incurred by cloud-edge data transmissions for app vendors. Existing edge data caching (EDC) methods prioritize popular data and aim to minimize users’ data retrieval latency and system storage costs jointly. However, these EDC methods often rely on the assumption that data popularity always follows certain distributions. As a result, they cannot properly adapt to the fluctuations in data popularity due to user mobility or unexpected increases in user demands. Meanwhile, unlike cloud data centers, complex and fragile edge servers are more likely to experience physical failures or network outages, presenting new challenges for EDC strategies. Specifically, when an edge server fails or experiences an outage, cached data may become temporarily unavailable, leading to increased latency as requests are redirected to alternative servers or the cloud. In this paper, to enable uncertainty-aware edge data caching (uEDC), we first model the problem as a robust optimization problem and propose an optimal algorithm named uEDC-B to find the optimal uEDC solution. To address the high computational complexity of uEDC-B, we introduce an approximate algorithm named uEDC-L based on linear decision rules. Theoretical analysis and extensive experiments on a real-world dataset demonstrate that the proposed methods outperform two state-of-the-art approaches in handling the uncertainties in data popularity and edge server failure with a significant performance improvement of 59.27% in data retrieval latency and 55.07% in data caching cost. © 2002-2012 IEEE.

关键词： Mobile edge computing

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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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Enabling Cursor Control Through Eye Movement Using Hidden Markov Model 2nd

Enabling Cursor Control Through Eye Movement Using Hidden Ma...

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2nd International Conference on Data science and Network Engineering, ICDSNE 2024

作者： Tanusha, G. Havirbhavi, P. Ashwini, K. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (纸本)9789819783359

First and foremost, we present a novel scheme for controlling the cursor based on eye movement. Other strategies rely on physical items like touchpads or a mouse and place strict requirements on people with motor handicaps. Our solution connects digital interaction with human visual attention through eye-tracking technology. We examine the nuanced gaze patterns that develop, allowing for cursor control while also developing a sense of interaction context. Gaze data is transformed by our method into the motion of a cursor. It is highly accurate and adjustable. Cursor motions are generated based on the gaze movement pattern, making the interface more dynamically accurate and more tailored to individual behaviors. The context-aware interface maximizes efficiency through its adaptability as it learns and adopts the behaviors. In addition, our research introduces a novel scheme through the use of software tools to offer an eye-controlled mouse system. This system accurately recognizes facial features and interprets eye movements through image processing techniques. The system enables intuitive cursor control by interpreting observable eye movements. Transforming eye motions into a cursor's actions, it enhances user accessibility and hands-free interaction;in other words, its performance is captured in the experimental analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Eye movements

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QuickPark: Efficient Parking with Real-Time Pre-Booking 3

QuickPark: Efficient Parking with Real-Time Pre-Booking

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

作者： Dharshan, J.Y. Amarnath, Arjun R. Adithya, Gadamsetty Siva Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

The parking is one of the biggest problems. One of the emerging features of parking management is congestion in urban centres due to the increase in the number of vehicles on the road, which has added anxiety to drivers. These conventional or legacy parking systems fail to respond adequately to the increasing needs, especially in Smart City contexts. To this end, a Smart Parking Management System (SPMS) is developed with real-time data, incorporating a parking sensor, parking information, an easy-to-navigate parking lot, and favourable methods of payment accepted. This prototype optimises parking space, provides better convenience to drivers, and leads to the sustainability of such a structure in the urban area. The proposed SPMS promises to be a revolutionary and practical approach to addressing some of the modern parking management issues in delivering an efficient mobility regime. © 2025 IEEE.

关键词： Parking

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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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Advanced Adaptive Traffic Management System for Urban Environments 3

Advanced Adaptive Traffic Management System for Urban Enviro...

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

作者： Sai Srujan Reddy, P. Naveen Raj, B.U. Jose, Nikhil Tom Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Viswa Vidhyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Urban traffic congestion is still a major problem that causes delays, collisions, and wasteful use of resources. Conventional fixed-schedule systems, which frequently exacerbate problems at junctions, U-turns, and pedestrian crossings, are insufficient for dynamic traffic situations. The Smart Dynamic Traffic Management System described in this work makes use of servo motors, proximity sensors and ultrasonic sensors, Arduino microcontrollers, and AI-powered cameras. To improve safety and streamline traffic flow, the system prioritizes emergency vehicles, controls U-turns, dynamically modifies traffic signals based on real-time data, and monitors road conditions. Scalability and adaptability for a range of urban scenarios are ensured by the integration of IoT technology and intelligent intercommunication between crossings. A visualization tool based on Pygame was used to simulate and assess the suggested solution. The findings showed that traffic flow had significantly improved, with an average increase in the exit-to-entry ratio of 30.71% for the three roadways. More specifically, traffic on Road A decreased by 15.28%, on Road B decreased by 31.25% and on Road C decreased by 45.61%. The outcomes confirm just how well the system works for reducing traffic and giving priorities to critical traffic situations, such as emergency response and turning. This system uniquely integrates real-time adaptive traffic control algorithms with IoT and machine learning to dynamically prioritize traffic flow and emergency vehicles, overcoming the limitations of existing static systems. © 2025 IEEE.

关键词： Traffic congestion

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DSCR: A Dynamic Secure Clustering Routing Scheme for UANETs Based on Reputation Mechanism

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IEEE Internet of Things Journal 2025年第10期12卷 14109-14123页

作者： Gong, Yinyan Chen, Yuxiang Li, Kuanching Liang, Wei Li, Xiong Wang, Jin Xiang, Yang Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China Sanya Research Institute Hunan University of Science and Technology Sanya572024 China School of Computer Science and Engineering Hunan Key Laboratory for Service Computing and Novel Software Technology Xiangtan411201 China Institute for Cyber Security School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Swinburne University of Technology School of Software and Electrical Engineering HawthornVIC3122 Australia

In UAV ad hoc networks (UANETs), rapid movement of nodes leads to frequent changes in network topology, increasing the risk of packet loss and affecting data transmission. Furthermore, current research on drone clustering lacks security considerations, which reduces the reliability of data transmission. Due to this, improving the stability and reliability of network data transmission in dynamically changing UANETs remains a challenge. In this work, we propose the reputation mechanism dynamically secure cluster routing scheme (DSCR) for UANETs, a design for cluster head election in UANETs using the evaluated value and reputation value of drones and forms clusters through this reputation mechanism to avoid malicious nodes from interfering with the clusters to improve the security of UANETs. We apply a residual link survival time-based intra- and inter-cluster algorithm based on residual link survival time for data forwarding of nodes, optimizing the dynamic routing strategy and reducing the packet loss rate of nodes. In addition, reinforcement learning is used in UANETs to achieve cluster decisions based on the current network state and cluster dynamics, effectively improving the stability of clusters. Experiments were conducted on the proposed method to verify its efficiency and stability. Compared to the ICRA, RICR, and DCA algorithms, the stability of the cluster is improved by 11.92%, 28.12%, and 75.2%, respectively, and the packet loss rate reduced by 41.48%, 44.17%, and 55.74%, demonstrating that DSCR is a compelling dynamic routing solution applicable to UANETs. © 2014 IEEE.

关键词： Drones

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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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IoT-based Door Automation and Smart Health Monitoring System 3

IoT-based Door Automation and Smart Health Monitoring System

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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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