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Intelligent Edge-based System for Driver Drowsiness Monitoring in Mobile Crowd-sourcing Environments 2

Intelligent Edge-Based System for Driver Drowsiness Monitori...

引用

2nd international conference on Recent Trends in Microelectronics, Automation, Computing, and Communications systems, ICMACC 2024

作者： Neels Ponkumar, D. David Ramesh, S. Ahamed, A. Niyas Baskar, S. Ashok, Chitrada Charan, M. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India School of Computing College of Engineering and Technology SRMIST Department of Computing Technologies Kattankulathur Campus Tamil Nadu Chengalpattu India Thamirabharani Engineering College Department of Electronics and Communication Engineering Tamil Nadu Tirunelveli India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Civil Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350366570

Using CNN and GAN improves road safety, says study. Modern machine learning techniques for mobile crowdsourcing may identify driver fatigue early. Our convolutional neural network (CNN) model detects drivers' fatigue using facial expressions, head movements, and other visual clues. Mobile devices and high-resolution cameras make the system straightforward to install in automobiles. GAN (Generative Advisal Network) handles unequal and limited training data. Creating realistic, synthetic weary driver photos improves the dataset and helps CNN learn from different driving scenarios and face features. Our edge-based computing distinguishes it. In mobile crowdsourcing with unpredictable internet connections, processing data locally on users' smartphones minimizes latency and bandwidth. The edge-based solution processes sensitive data locally on the device rather than sending it to servers, increasing user privacy. Extensive testing showed our system diagnosed driver weariness better than others. GAN-generated data increased model performance in under-represented training datasets. The study shows how to merge CNN and GAN in edge computing with 98.4% accuracy and driver fatigue monitoring. We found important implications for mobile crowdsourcing and intelligent transportation system development. © 2024 IEEE.

关键词： Convolutional neural networks

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Revolutionizing Travel Planning: An image based Destination Recognition and Recommendation System 1

Revolutionizing Travel Planning: An Image Based Destination ...

引用

1st international conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Gupta, Megha Goyal, Vanshika Rathi, Vanshika Jss Academy of Technical Education Computer Science and Engineering Uttar Pradesh Noida India

ISBN: (纸本)9798350367720

Due to the abundance of information available online and the wide range of possibilities available, our preparation has become more difficult and time-consuming. This is especially true given that every visitor has different interests and preferred destinations in addition to tour-specific limitations like vaccination records and travel restrictions due to pandemics. A number of travel agencies and organizations have sprung up with more advanced internet services in an attempt to take advantage of the growing global travel market by employing technology to provide travelers with relevant recommendations. However, these systems often use a destination-based recommendation strategy and are sold in packages with little room for modification to account for the tastes of individual travelers. In order to overcome these restrictions. With the use of artificial intelligence-powered picture recognition, our TravelGaze system can now identify destinations from user-uploadedimages, marking a significant advancement in travel technology. In addition to recognition, the system offers customized trip suggestions that include neighboring lodging options, eateries, art galleries, and current weather information. The solution improves destination recognition accuracy and revolutionizes travel planning by utilizing cutting-edge AI algorithms. This paper offers insights for developers and stakeholders looking to reinvent how consumers explore and plan their travels, adding to the ongoing conversation on intelligent travel solutions. © 2024 IEEE.

关键词： Tourism

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Research on Acquisition Method of DSSS System based on PMF-FFT 8

Research on Acquisition Method of DSSS System Based on PMF-F...

引用

8th international conference on Communication, image and signal Processing, CCISP 2023

作者： Wang, Xinyu Jiang, Kun Chu, Ran Zhang, Haozhe Wang, Changheng School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China Shanghai Aerospace Electronic Technology Institute Shanghai Academy of Spaceflight Technology Shanghai China Jiangsu YEE-Space Aerospace Technology Co. LTD Starboard Electronics Department Nanjing China

ISBN: (纸本)9798350305838

Spread spectrum communication, as an essential communication technique, has a wide range of applications in the real world. This article focuses on the acquisition methods in DSSS (direct sequence spread spectrum) systems. The PMF-FFT (Partial Match Filtering Fast Fourier Transform) algorithm, recognized as an excellent acquisition algorithm, combines timedomain and frequency-domain acquisition algorithms, exhibiting characteristics such as high dynamic range and fast acquisition speed. Firstly, the basic principles of the PMF - FFT algorithm are introduced, and a corresponding mathematical model is established to analyze the characteristics of this algorithm. Secondly, improvements are made in response to the practical design requirements and issues in multi-rate, multi-user communication systems. These improvements mainly include the selection of spread spectrum sequences, frame composition, and acquisition architecture. Through these improvements, the algorithm's performance is enhanced. Finally, through simulation verification at rates of 16Kbps and 128Kbps, the improved algorithm successfully achieved acquisition of eight different time slots under a significant Doppler frequency. © 2023 IEEE.

关键词： Fast Fourier transforms

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18th international KES conference on Agents and Multi-Agent systems: Technologies and Applications, KES-AMSTA 2024

18th International KES Conference on Agents and Multi-Agent ...

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18th international KES conference on Agents and Multi-Agent systems: Technologies and Applications, KES-AMSTA 2024

ISBN: (纸本)9789819764686

The proceedings contain 34 papers. The special focus in this conference is on Agents and Multi-Agent systems: Technologies and Applications. The topics include: Fair Path Generation for Formation Control Combining Ant Colony and Particle Swarm Optimizations;preference Definition in a Multi-agent System Approach for User-Centric internet of Things Smart Environments;AI-Driven Nitrogen Stress Management in Cereal Crops via Drone technology;agent-based Simulation for Withdrawal of Energy-Inefficient Housing;resource Limitations of Business Process Simulations: Literature Study;data Augmentation for Business Process Alignment: Proof of Concept and Experimental Design;smart Scheduling in Urban Traffic: A Multi-Agent System for Dynamic Vanpooling;analysis of the Impact on Area Prices Using Propensity Score Matching, Considering the Proportions of Photovoltaic and Thermal Power Generation Simultaneously;consideration of Building a Simulator to Evaluate Methods to Maximize the Effectiveness of Advertising to Households;Human-AI-Collaboration SECI Model: The Knowledge Management Model of the Experts’ Tacit Knowledges with Augmented LLM-based AI;modeling Agent Awareness After Hierarchical Managerial Training;development of An Application for Extracting Needs Related to Actual Gas Use Using Text Mining;Impact of Intelligent systems in the Home Office on Employee Satisfaction—Lessons Learned from the COVID-19 Pandemic;agile Methodologies in Software Development: A Study of Effective Management Strategies for Companies in the Digital Era;predictive Analysis of Cyclical Sales Data;EMG signal Classification Using Machine Learning for Augmentative Assistance in Cerebral Palsy;wellnessWave—Platform for the Digitization of the Romanian Public Medical System;TRIAGE Predictive Model based on Artificial Neural Networks and Deep Learning;platform for Automated Assessment of Obstetric Ultrasounds, Using Machine Learning;identification of Fonts in Unstructured Environments Through Deep Lea

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Insulator Location and Segmentation Method based on Improved S2ANet 8

Insulator Location and Segmentation Method Based on Improved...

引用

8th international conference on Intelligent Computing and signal Processing, ICSP 2023

作者： Deng, Zhixiang Zhu, Aili Cai, Changchun Hohai University Key Laboratory of Power Transmission & Distribution Equipment Technology Changzhou China Hohai University College of Internet of Things Engineering Changzhou China

ISBN: (纸本)9798350302455

Insulator is one of the important components of power system, which greatly affects the safe operation of transmission line. Aiming at the problem that insulator in aerial images has arbitrary rotation angle which leads to inaccurate location of insulator region and contains redundant background information, S2ANet model based on PAN is proposed to locate insulator region in aerial images. Firstly, rotation, cutting and noise were used to enhance the insulator data set and expand the number of samples. Secondly, S2ANet model based on PAN is used to locate the insulator and enhance the feature extraction ability of insulator edge. Finally, the insulator region is segmented accurately based on the image outspread clipping method. Experiments show that AP of improved S2ANEet model on the test data set is 92.6%, and outspread clipping method can completely segment the insulator region. The method proposed for insulator location and segmentation has good engineering application value. © 2023 IEEE.

关键词： Location

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Knowledge graph construction for power grid systems based on fuzzy matching algorithm 3

Knowledge graph construction for power grid systems based on...

引用

3rd international conference on Advanced Algorithms and signal image Processing, AASIP 2023

作者： Haitao, Gui Junyang, Tian Heming, Hou Renming, Li Guilin Power Supply Bureau Guangxi Power Grid Co Ltd Guilin Guangxi541002 China Guangxi Power Grid Power Dispatching and Control Center Nanning Guangxi530023 China

ISBN: (纸本)9781510668522

To facilitate the processing of data pertaining to defects and faults in the power grid regulation system, as well as knowledge graph-based support to help regulators in their decision-making, a knowledge graph construction method employing a fuzzy matching algorithm has been devised, the outcomes are presented in the form of a visual knowledge graph. Initially, a fuzzy matching algorithm is devised to to match the defect with the defect-fault database. Subsequently, the Neo4j database is utilized to construct a knowledge graph that provides guidance on fault locations. Lastly, by conducting a case analysis of the data extracted from a specific region's distribution network, experimental results demonstrate the method's capability to accurately match target data. Moreover, the visual knowledge graph constructed has proven effective in enhancing regulators' decision-making efficiency. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Defects

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Joint Beam-Time Allocation of Phased Array Radar based on Variable False Alarm Rate Detection 8

Joint Beam-Time Allocation of Phased Array Radar Based on Va...

引用

8th international conference on signal and image Processing, ICSIP 2023

作者： Liao, Maosen Tan, Rui Xiong, Kui Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China

ISBN: (纸本)9798350397932

Conventional searching methods with only one constant false alarm rate can no longer provide effective detection performance for different remote targets associated with distinct signal-to-noise ratios in radar systems. To overcome this problem, this paper presents a dynamic joint beam and time resource allocation strategy based on variable false alarm rate detection framework for phased array radar for remote target searching. Specifically, a multi-stage searching framework of the phased array radar is first developed, where the false alarm probability for detection increases adaptively with the stage evolving. Then, a constrained allocation model of the beam and time is formulated. Simulation results demonstrate the effectiveness and superiority of the proposed algorithm against some counterparts in terms of detection performance and efficiency of resource utilization. © 2023 IEEE.

关键词： Errors

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Retrievable image Encryption based on Adaptive Block Compressed Sensing

Retrievable Image Encryption Based on Adaptive Block Compres...

引用

international conference on image, Vision and Intelligent systems, ICIVIS 2023

作者： Fang, Jiuchuan Zhao, Hui Zheng, Mingwen Wang, Zijian Niu, Sijie Gao, Xizhan Shandong Provincial Key Laboratory of Network Based Intelligent Computing School of Information Science and Engineering University of Jinan Jinan250022 China School of Mathematics and Statistics Shandong University of Technology Zibo255000 China

ISBN: (纸本)9789819708543

The increasing popularity of the internet and mobile devices, cloud storage has emerged as a popular storage method. However, because data carries a lot of information, untrustworthy servers can access users’ private information. This paper introduces an approach based on adaptive block compressed sensing and hash retrieval. The objective of this paper is to reduce the storage space required by encryption algorithms while simultaneously improving interaction efficiency. Firstly, compress images using block compressed sensing, and use BCS-SPL algorithm to reconstruct. And curves are fitted based on the gradient features and root mean square values of the blocks. Then, the sub-rates are allocated based on the gradient characteristics of the image using a fitting curve, and then the image is compressed. Next, encrypt the image and save it. The features of the queried image are used for retrieval, the results are decrypted, and then reconstructed. Finally, through a series of security analyses, the method is effective. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cloud storage

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On-line Monitoring System For Water Content based On The Principle of Calculable Cross Capacitor 26

On-line Monitoring System For Water Content Based On The Pri...

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26th international conference on Electrical Machines and systems, ICEMS 2023

作者： Pan, Ming Wenze Gao, Hao Chen, Bitong Shanghai Zhixin Electric Co. Ltd. Shanghai China Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing China

ISBN: (纸本)9798350317589

The presence of water in transformer oil will reduce its insulation performance, resulting in significant accidents such as insulation breakdown of the transformer. The traditional method of measuring the water content in transformer oil has shortcomings such as poor real-time performance and low accuracy. This paper proposes for the first time to apply the principle of the calculable cross capacitor to the field of water measurement in transformer oil. A new sensor structure based on the principle of the calculable cross capacitor is designed. It uses the finite element software Comsol Multiphysics to simulate and analyze the influence of structural parameters on the sensor's sensitivity and obtain the optimal design of the sensor. The capacitance measurement chip CAV444 is used to convert the capacitance signal into a differential voltage signal, and then the data is uploaded to the cloud platform through the microprocessor and internet of Things technology, realizing the function of online measurement. The characteristic experiment shows that the water content in the oil has an excellent linear relationship with the output voltage. In the range of 0-100 ppm, the accuracy reaches ±3.0% FS, which meets the needs of the actual site. © 2023 IEEE.

关键词： Capacitance

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Enhancing Transportation Safety with YOLO-based CNN Autonomous Vehicles 1

Enhancing Transportation Safety with YOLO-Based CNN Autonomo...

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1st IEEE international conference on Electronics, Computing, Communication and Control technology, ICECCC 2024

作者： Sarumathi, S. Sabir, Mohammed Suhail, Mohammed Umarulla, Mohammed Yousuf, Mohammed HKBK College Of Engineering Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350371802

Our project, titled Enhancing Transportation Safety with YOLO-based CNN Autonomous Vehicles', pioneers a transformative approach to autonomous driving. Through the fusion of advanced machine learning techniques, specifically the YOLO-based Convolutional Neural Network (CNN) algorithm, with meticulously selected hardware components, including Raspberry Pi 4B and IR sensors, our system addresses critical objectives such as object recognition, lane detection, and traffic signal and signboard detection, pothole detection. By leveraging diverse image datasets and optimizing the YOLO-based CNN algorithm, our system achieves exceptional accuracy and efficiency in environmental perception and navigation. Key features such as real-time object detection and precise lane detection contribute to safe navigation through complex traffic scenarios. With potential applications across automotive, logistics, and transportation industries, our project represents a significant advancement in autonomous driving technology. By prioritizing safety and efficiency, our YOLO-based CNN autonomous vehicle system holds promise for revolutionizing transportation systems and enhancing road safety worldwide. © 2024 IEEE.

关键词： Autonomous vehicles

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