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Intelligent Fall Detection and Alert System for the Elderly Using Yolov8 and Cloud-Based Analytics 5

Intelligent Fall Detection and Alert System for the Elderly ...

引用

5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Papan, Vishal Maheswari, S. Vellore Institute of Technology Dept. of Computer Engineering Chennai India

ISBN: (纸本)9798350379945

As people age, the frequency and impact of falls among the elderly continue to escalate, presenting significant health and mobility risks. Efficient detection and immediate response are crucial in reducing the severity of injuries and potentially life-threatening complications associated with such falls. This research study introduces a real-time alert system for the elderly by utlilizing the cutting-edge capabilities of YOLO v8, the latest iteration in the You Only Look Once series of models known for its high speed and accuracy in object detection tasks. The system is designed to operate with inputs from a variety of sources, including direct video feeds, RTSP streams from existing CCTV infrastructure, static images, and data from wearable sensors. This multi-source approach ensures that the system is adaptable for use in a wide range of environments, from personal residences to care facilities, providing continuous monitoring with enhanced accuracy. Upon the detection of a fall, the system immediately activates an alert protocol via Amazon Web Services (AWS) Simple Notification Service (SNS), ensuring that caregivers or family members are promptly notified to respond swiftly to the incident. This data-driven approach not only enhances the accuracy and responsiveness of the system over time but also aids caregivers and healthcare providers in understanding fall patterns and potential risk factors associated with specific environments or individuals, effectively addressing the critical challenges in elderly fall prevention and care. © 2024 IEEE.

关键词： Web services

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Deep Learning-Driven Cloud Intrusion Detection: Internet of Things and Cloud Networks 1

Deep Learning-Driven Cloud Intrusion Detection: Internet of ...

引用

1st International Conference on Advances in computer Science, electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Moon, Iffath Tanjim Islam Mondal, Md. Nazrul Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798331518578

In this paper, we have utilized deep learning approaches to detect cloud intrusion for the Internet of Things (IoT). The emerging growth of IoT and cloud environments has revolutionized many industries by allowing real-time data sharing and storage. Cloud platforms offer the essential infrastructure for managing the massive volumes of data produced by IoT devices. However, due to several flaws, including insufficient encryption, insecure APIs, and weak authentication, intruders can exploit the vulnerabilities to interrupt services and obtain unauthorized access. Therefore, deep learning can be an effective solution to detect cloud intrusion in IoT. In this research, we have developed individual convolutional neural network (CNN) and long short-term memory (LSTM) models, along with a hybrid CNN-LSTM model for multiclass classification and binary classification to detect cloud intrusion. In addition, we have examined which models perform the best for cloud intrusion detection for IoT among the individual and hybrid models. The proposed models are effective in detecting cloud intrusion, as CNN can extract spatial features, and LSTM can capture temporal dependencies from network traffic data. Furthermore, we have utilized one of the most recent and comprehensive datasets for IoT, the ToN-IoT dataset, containing real-world data. In multiclass classification, the hybrid CNN-LSTM has given the best performance, achieving an accuracy of 97.65%, precision of 97.72%, recall of 97.65%, f1 score of 97.67%, and AUC of 99.93%. In binary classification, all CNN, LSTM, and hybrid CNN-LSTM have demonstrated high performance, where LSTM has achieved the highest accuracy of 99.97%. Moreover, we have evaluated the performance of multiclass classification for detecting nine distinct kinds of attacks. In this instance, CNN has shown better performance in detecting backdoor attacks. Thus, this research can make the IoT platform more secure by efficiently detecting cloud intrusion. © 2025

关键词： Network intrusion

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Enhancing Privacy Through Time Aggregation of Load Profiles in Energy Management 8

Enhancing Privacy Through Time Aggregation of Load Profiles ...

引用

8th IEEE International Energy Conference, ENERGYCON 2024

作者： Varenhorst, Ivo A.M. Hoogsteen, Gerwin Gerards, Marco E.T. Hurink, Johann L. dept. of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands

ISBN: (纸本)9798350382150

Demand side management (DSM) applications rely on the exchange of load profiles to effectively manage the operation of energy systems. However, sharing detailed energy profile data raises substantial privacy concerns, such as potential misuse of personal information. To mitigate these concerns, we investigate the potential of time aggregation (TA), which involves merging multiple samples of a profile into a single value representing multiple intervals. TA reduces data exchange and computational requirements in energy management and helps preserve user privacy by reducing granularity of user data. We show that, for an effective implementation of TA in energy management, it is important to make the right choice of TA method. We compare and evaluate seven different TA methods. Furthermore, we perform TA across various time frames using an optimization based DSM approach. Our findings reveal that if we aggregate load profiles from 15 minutes to 4 hours, we obtain both enhanced privacy and a 21% decrease in the required number of iterations with the investigated DSM method, albeit at the cost of a 15% decrease in objective value performance. Based on this, we conclude that depending on the application needs, TA with a carefully selected aggregation method has the potential to bring value to energy management, even when aggregating to a considerable extent. ©2024 IEEE.

关键词： Energy management

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Multi-Layered Approach to IoT Cybersecurity in Smart Cities 3

Multi-Layered Approach to IoT Cybersecurity in Smart Cities

引用

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

作者： Benjamine, Daniel Anto Madhavan, K. Pavithra, S. Dept. of Computer Science and Engineering Chennai Institute of Technology Chennai India

ISBN: (纸本)9798331527549

Internet of Things (IoT) has been rapidly growing over the past years. There have been many cybersecurity challenges faced by IoT-based smart cities in existing work for the energy, health and transportation sectors. These cybersecurity challenges are crucial to remove in the IoT sector to implement a safe and secure IoT based smart city. Vulnerabilities across layers in IoT are analyzed and a multi-layered model of security is proposed to enhance data integrity and communication security by using AI, blockchain and ML. This paper would also present several policy recommendations to stakeholders and IoT developers for building a safe urban IoT ecosystem. © 2025 IEEE.

关键词： Cybersecurity frameworks IoT smart city technologies urban

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Enhancing Micro-LED Pixel Circuit Performance through Threshold Voltage Compensation Utilizing LTPO technology

Enhancing Micro-LED Pixel Circuit Performance through Thresh...

引用

International Conference on Display technology, 2024

作者： Li, Yan Im, Hwarim Moon, Kook Chol Kim, Yong-Sang Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

In this paper, we proposed a new low-temperate polycrystalline silicon and oxide (LTPO) thin film transistor (TFT) pixel circuit for micro light-emitting diode (µLED) displays. This design considers the current-sensitive attributes of µLEDs and employs a hybrid driving approach involving Pulse Width Modulation (PWM) and Pulse Amplitude Modulation (PAM). The proposed pixel circuit can not only compensate the threshold voltages of the two driving TFTs, but also reduce the voltage drop by current (IR drop) of the entire backplane through compensation and offset. © 2024 John Wiley and Sons Inc. All rights reserved.

关键词： Pixels

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Frequency Control of a Solar/Wind/Fuel Cell/Biogas/Biodiesel/Flywheel/Battery Storage based Microgrid under Dynamic Conditions 1

Frequency Control of a Solar/Wind/Fuel Cell/Biogas/Biodiesel...

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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Reddy, Galiveeti Hemakumar Bhattacharya, Devjani Bisht, Pushpanjali Singh Kulshreshtha, Akanksha Gunaga, Sruthi R Mathur, Neha Dpg Institute of Technology and Management Dept. of Electrical Engineering Gurugram India Dpg Institute of Technology and Management Dept. of Electronics and Communication and Engineering Gurugram India Dayananda Sagar College of Engineering Dept. of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798350360707

Renewable energy sources (RES) are the remedy for pollution free power generation. Availability of power from RES is uncertain in nature and this issue is mitigated with the help of energy storage system (ESS). The combination of RES and ESS leads to the formation of microgrids which can serve the loads by itself. The proposed microgrid in this paper consist of different energy sources and storage systems such as solar, wind, biogas, biodiesel, fuel cell, battery and flywheel energy storage system. It is very important to stabilize the frequency fluctuations due to changes in load, solar and wind output powers. In this work, frequency of the proposed microgrid is stabilized by using the PID controller. The unavailability of solar and wind output powers are also considered for the analysis. The proposed microgrid is modelled and validated using MATLAB/SIMULINK. © 2024 IEEE.

关键词： Biodiesel

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Enhancing Doodling Experience Using Generative Adversarial Networks 2

Enhancing Doodling Experience Using Generative Adversarial N...

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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Ashtagi, Rashmi Rathi, Devanshu Handoo, Ripul Purohit, Rishi Madhavaswala, Abbas Nogamawala, Mohammad Vishwakarma Institute of Technology Dept. Of Computer Engineering Pune India

ISBN: (纸本)9798350388916

Interacting with AI systems solely through textual prompts often encounters limitations due to the challenges of expressing complex visual ideas in text. This paper introduces an advanced AI system that interprets and visualizes users' sketches by employing state-of-the-art Generative Adversarial Networks (GANs), such as pix2pix, SketchGAN, DCGAN, and ESRGAN. This system not only significantly enhances real-time interactions but also shows exceptional proficiency in image editing tasks, thus facilitating more intuitive communication between humans and AI. By enabling rapid and accurate visualizations, this technology substantially streamlines and improves design workflows in the architecture and fashion industries. The advancements fostered by this system contribute significantly towards achieving greater capabilities akin to Artificial General Intelligence, enhancing creative processes and production efficiencies. © 2024 IEEE.

关键词： Generative adversarial networks

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Anti-Counterfeit Product Identification System: A Paradigm Shift in Supply Chain Integrity 8

Anti-Counterfeit Product Identification System: A Paradigm S...

引用

8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Dhore, M.L. Loya, Riya Sasne, Rohan Rokade, Tejas Chandak, Rushikesh Vishwakarma Institute of Technology Dept. Of Computer Engineering Pune India

ISBN: (纸本)9798350391770

Counterfeiting is a continuous and global issue that afflicts sectors, undermines consumer trust, and causes economic harm. To effectively fight this issue, the Anti-Counterfeit Product Identification System Using Blockchain has developed as a novel solution. This article provides an in-dept. examination of this game-changing solution, which uses blockchain technology, QR codes, smart contracts, and the Ethereum network to provide a secure and transparent platform for certifying items across several industries. This study emphasizes the system's critical role in tackling complicated supply chain difficulties by providing a tamper-proof way for verifying product authenticity. The document describes the fundamental technologies used, significant features, and essential project setup steps. Finally, this approach has the potential to drastically reduce counterfeit goods while also creating transparency and confidence among supply chain players ranging from manufacturers to consumers, making it a critical tool in today's linked and fragile marketplaces. © 2024 IEEE.

关键词： Smart contract

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Towards Vision Based Bi-Cycles Detection and An Autonomous Decision Making System for Driving Situation Awareness 13

Towards Vision Based Bi-Cycles Detection and An Autonomous D...

引用

13th International Symposium on computer Science and Educational technology, ISCSET 2024

作者： Nine, Julkar Mehta, Ayushkumar Rajkumar, Sai Rohit Hardt, Wolfram Chemnitz University of Technology Dept. of Computer Engineering Chemnitz Germany

ISBN: (纸本)9798350390803

In response to the growing global emphasis on healthy living and environmental consciousness, the popularity of eco-friendly transportation options like bicycles has surged. However, cyclist safety remains a critical concern, particularly in interactions with automobiles, where accidents often result in severe consequences. This project aims to enhance cyclist safety through machine learning-based bicycle detection and situational awareness techniques, aiming to mitigate vehicle-bicycle collisions. By integrating OpenCV lane detection and YOLOv8-based vehicle/bicycle detection with distance estimation, the system can analyze real-Time road conditions and make informed decisions, including speed reduction, overtaking safety assessment, and maintaining safe distances from cyclists. Testing validates the system's accurate detection, precise analysis, and effective decision-making capabilities, ensuring vehicles respond appropriately to encountered road scenarios. Ultimately, this project addresses the pressing need for cyclist safety in vehicle-rich environments, leveraging machine learning, real-Time analysis, and advanced detection technologies to foster safer roads. © 2024 IEEE.

关键词： Bicycles

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Traction Locomotive Incipient Fault Analysis using Wavelet based Particle Swarm Optimization 3

Traction Locomotive Incipient Fault Analysis using Wavelet b...

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3rd IEEE International Conference on Control, Instrumentation, Energy and Communication, CIEC 2024

作者： Ray, Debopoma Kar Roy, Tamal Chattopadhyay, Surajit Mckv Institute of Engineering Dept. of Electrical Engineering WB Howrah India Ghani Khan Chowdhury Institute of Engineering and Technology Dept. of Electrical Engineering WB Malda India

ISBN: (纸本)9798350313703

The present work aspires to pursue a qualitative research on the loosening of brushes in Indian induction motor locomotives, observing the traction transformer input current. At the initial step, the locomotive has been built in programming and the current input to the transformer has been documented at normal condition. Brushes have been gradually loosened and the transformer inputs have again been recorded. Both the currents have been assessed using a novel Wavelet Transform (WT) coefficient statistical analysis based Particle Swarm Optimization (PSO) Technique. From the computed Skewness, Kurtosis and RMS values, global bests have been disintegrated and optimization has been done in PSO plane to assess different conditions in the engine associated with an incipient brush fault. Here multi-objective PSO (MOPSO) has been used for the assessment and decision making. With the outcome of the refinement, a credo has been developed at the end to segregate the faulty traction engine from the healthy one. The technique used here has been validated in offline mode with satisfactory outcome. © 2024 IEEE.

关键词： Wavelet transforms

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