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2D NIR-SPI spatial resolution evaluation under scattering condition 19

2D NIR-SPI spatial resolution evaluation under scattering co...

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19th international conference on electrical engineering, computing science and automatic control, CCE 2022

作者： Quero, Carlos Alexander Osorio Durini, Daniel Rangel-Magdaleno, Jose De Jesus Martinez-Carranza, Jose Ramos-Garcia, Ruben Electronics Department Puebla Mexico Computer Science Department Puebla Mexico Optical Department Puebla Mexico

ISBN: (数字)9781665455084

ISBN: (纸本)9781665455084

In recent years, it had been an evolution in the sensors used by vision systems. Different technologies from RGB camera, IR-camera, LIDAR, RADAR, or sensor combinations can work in different spectrum bands. A new alternative to the vision system is the single-pixel camera (SPC), an architecture based on the compressive sensing theory for 2D reconstruction images. SPC's feature is used as the single detector that measures the linear combinations of pixels through patterns projection of structured light over the object that would like to photograph instead of using an array of pixels as in RGB sensors or cameras. These architectures offer the advantage that they can be adapted to different spectrum bands as near-infrared (NIR), and could operate in scenarios with low visibility or under rain, mist, or fog conditions. Currently, there is little information that discusses the problem of spatial resolution in SPC in scattering conditions for which we defined a methodology to evaluate the spatial resolution SPC's in terms of point spread function (PSF), and we analyzed how it affected the spatial resolution with the distance and under foggy conditions, for an SPC with active illumination at the wavelength at 1550 nm. © 2022 IEEE.

关键词： Graphics processing unit

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An Intelligent Internet of Things (IoT) Powered Railway Track Crack Detection Scheme Based on Smart Sensors Association

An Intelligent Internet of Things (IoT) Powered Railway Trac...

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2024 international conference on Innovative computing, Intelligent Communication and Smart electrical Systems, ICSES 2024

作者： Prince, P. Seethalakshmi, P. Prasad, D. Kanchana, R. Bharathi, L. Vimalraj, S. Leones Sherwin Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Cse Chennai India Qis College of Engineering and Technology Department of Aimlds Pondur Road Vengamukkapalem Ongole Prakasam AndhraPradesh Prakasam District523272 India Sona College of Technology Department of Eee Salem636005 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Cse Chennai India Qis College of Engineering and Technology Department of It AndhraPradesh Ongole India Panimalar Engineering College Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331543617

This paper presents an IoT -powered railway track crack detection system that uses a combination of smart sensors and autonomous vehicles to detect cracks and obstacles in railway infrastructure. The system incorporates ultrasonic sensors, infrared (IR) sensors, and LED-LDR assemblies, enabling real-time monitoring and reporting of railway track conditions. Wireless communication protocols such as Wi- Fi, RF transmitters, and GPS are utilized to transmit data to central control systems. Through testing, the combined sensor setup demonstrated the highest crack detection accuracy of 98%, outperforming individual sensors with accuracies of 94 % for ultrasonic sensors, 90% for IR sensors, and 80% for LED-LDR. The system's response time averaged 460ms in the combined setup, with the LED-LDR setup being the slowest at 580ms. The system also showed resilience across varied environmental conditions, proving its robustness in both high and low temperature, humidity, and lighting scenarios. This efficient, solar-powered system reduces manual inspection efforts and ensures continuous, reliable operation. The proposed system offers an innovative, cost-effective solution to enhance railway safety and prevent potential accidents caused by track defects. © 2024 IEEE.

关键词： Ultrasonic sensors

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Improving Connectivity of IoT-Enabled Networks Through Big Data Analytics 15

Improving Connectivity of IoT-Enabled Networks Through Big D...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Kiran, K.S. Sen, Sumanta Sharma, Sunil School of Engineering and Technology Karnataka Bangalore India ARKA JAIN University Department of Pharmacy Jharkhand Jamshedpur India Vivekananda Global University Department of Computer Science & Application Jaipur India

ISBN: (纸本)9798350370249

The net of things (IoT) has quick grow to be the backbone of many corporations, taking into account real-time statistics collection and automatic tasks. However, the connectivity of these IoT-enabled networks can become without difficulty congested when huge amounts of data are generated in a brief time frame. To be able to hold a high stage of overall performance, big facts analytics can be used to research the massive volumes of generated statistics, provide insights and locate anomalies to improve community connectivity. Massive statistics analytics will permit higher records processing and evaluation competencies, become aware of regions of improvement and optimize network operations. Additionally, predictive analytics techniques can be used to forecast upcoming community congestion and take movement that could enhance network performance in real time. This, but, requires green facts collection, garage and control gear to ensure that the big records analytics answer is effective and efficient. This paper investigates how massive records analytics may be used to improve the connectivity of IoT-enabled networks through leveraging the energy of predictive analytics. © 2024 IEEE.

关键词： Predictive analytics

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Low-Level control of a Quadrotor using Twin Delayed Deep Deterministic Policy Gradient (TD3) 18

Low-Level Control of a Quadrotor using Twin Delayed Deep Det...

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18th international conference on electrical engineering, computing science and automatic control (CCE)

作者： Shehab, Mazen Zaghloul, Ahmed El-Badawy, Ayman German Univ Cairo Mechatron Engn Dept Cairo Egypt

ISBN: (纸本)9781665400299

Unmanned Aerial Vehicles (UAVs) like Quadrotors are inherently under-actuated and unstable systems. The mechanical complexity and non-linearity of such systems make it a difficult task to control the flight of the mentioned systems. However, due to recent advancements in the fields of data science and machine learning, new algorithms for flight stabilization and trajectory control were developed using Deep Reinforcement Learning. This paper presents two low-level Quadrotor controllers based on the same algorithm. The first designed controller aims to stabilize the Quadrotor at a certain preset point given any random initial position. The second is to track any target position given in the 3D space. Twin Delayed Deep Deterministic Policy Gradient (TD3) is used to train the agents to achieve the required tasks. This method is an off-policy Actor-Critic based method. It was used as it does not require a system model and works on environments with continuous action and state spaces. The superb performance of the trained policies is demonstrated in a simulation to illustrate the effectiveness of the proposed controllers.

关键词： Quadrotor Machine Learning Reinforcement Learning TD3

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Dossier Classification to Support Workflow Management Optimization 4th

Dossier Classification to Support Workflow Management Optim...

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4th international conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

作者： Fioretto, Simona Masciari, Elio Napolitano, Enea Vincenzo Department of Electrical and Information Technology Engineering University of Naples Federico II Naples Italy Arcavacata Italy

ISBN: (纸本)9783031812460

One of the main challenges in optimizing services in various fields, including the legal sector, is the lack of an automatic system that can efficiently assign tasks based on predefined rules. In many cases, documents are still processed manually by qualified staff, which can be time-consuming and prone to errors. To address this issue, there is a need to develop a system that can automate the classification process, thereby simplifying the allocation of tasks to the most competent professionals in a specific field. This can be achieved by using Natural Language Processing (NLP) algorithms. In our Case Study the problem is to classify legal documents and suggest the most suitable judiciary branch for each dossier. By implementing such a system, it is possible to reduce processing times and enhance the overall efficiency of judicial offices. The proposed method can be supported by using a legal distributed system, which can facilitate seamless communication and collaboration among different actors. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

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AI-Powered Automated Wheelchair with Lane Detection 6

AI-Powered Automated Wheelchair with Lane Detection

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6th IEEE international conference on Emerging Smart computing and Informatics, ESCI 2024

作者： Abiraj, B. Sethuraman, K. Bethanney Janney, J. Prince Grace Kanmani, P. Sudhakar, T. Ezekiel Jebaraj, S. Sathyabama Institute of Science and Technology Dept. of Biomedical Engineering Chennai India University of Madras M.Sc. Cyber Forensics and Information Security Chennai India

ISBN: (纸本)9798350306613

A wheelchair is a revolutionary assistive mobility aid that improves the flexibility and standard of life for those with mobility limitations. There are many guidance systems for impaired people to navigate against obstacles and other dangers that are confronted rapidly and safely. With the developments of modern techniques, there are many distinct kinds of devices available to help with mobility. The key objective of the proposed study is to create a technologically intelligent wheelchair that can recognize voice, gesture, facial, lane, and gaze in a natural setting for individuals who have mobility impairments. In this paper, an automatic wheelchair based on lane detection is shown, which is made in real-Time using hardware through the use of deep learning algorithms and image manipulation. The device also promotes overall well-being with health-Tracking capabilities. It also offers communication support for those unable to speak. Empower Wheel Chair redefines accessibility, providing users with newfound freedom, convenience, and connection in their daily lives. © 2024 IEEE.

关键词： Face Recognition and Computer vision Gesture control Lane Detection Voice Recognition Wheelchair

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A method of automatic mechanical control based on single chip microcomputer 3

A method of automatic mechanical control based on single chi...

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3rd international conference on Electronics, electrical and Information engineering, ICEEIE 2023

作者： Sun, Fengshen Ma, Weishun Wang, Songhong Wei, Yan Chen, Feng Laiwu Vocational and Technical College Laiwu271100 China

ISBN: (纸本)9781510671423

In this paper, a manual alignment device and control system mode of field self-propelled machinery are proposed, including flexible contact induction device, information acquisition module connected with whisker sensor, microcontroller controller connected with information acquisition block, steering device connected with a single chip microcomputer, motor, remote communication and remote control device, and grating, The front end of the flexible contact induction device also contains two cross direction contact sensors. The data acquisition device collects the resistance data of the crops touched by the contact sensors and transmits it to the microcontroller controller. The single chip microcomputer can use the received data to control the steering speed of the steering gear controller and the speed of the motor in the device, and finally complete the manual alignment with the operating vehicle, manual speed regulation, and the obstacles in the front can retreat automatically, And it can remotely control the field intelligent operation vehicle platform, as well as various other external equipment. © 2023 SPIE.

关键词： Microcomputers

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A Meta Distribution-Based Fine-Grained Analysis for Contention-based WiFi Backscatter Networks 21

A Meta Distribution-Based Fine-Grained Analysis for Contenti...

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21st international conference on Networking, Sensing and control, ICNSC 2024

作者： Wang, Yulei Zhao, Qinglin Feng, Li Zhou, MengChu Shen, Meng Luo, Yu Sun, Yi School of Computer Science and Engineering Macau University of Science and Technology 999078 China College of Electronics and Information Engineering South-Central Minzu University Wuhan430074 China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China School of Computer Science Guangdong University of Technology Guangzhou510006 China Institute of Computing Technology Chinese Academy of Sciences Beijing100045 China

ISBN: (纸本)9798350365221

WiFi backscatter communication has gained many applications, but its performance characteristics remain to be analyzed. While existing research has investigated the success probability of backscatter tags in contention-based WiFi backscatter networks (CWBNs), it has focused solely on the first-order statistic of the signal-to-interference-plus-noise ratio (SINR). In this paper, we present a meta distribution-based fine-grained analysis that provides high-order statistics of SINR and characterizes the disparity among backscatter transmission links in CWBNs. Leveraging stochastic geometry, we, for the first time, derive mathematical expressions for the b-th moments of conditional success probability and its meta distribution. The extensive Monte-Carlo simulation results validate the accuracy of our proposed theoretical model and demonstrate its outstanding value to help us understand the overall performance of CWBNs. © 2024 IEEE.

关键词： Wi-Fi

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Delivering Improved Care through Remote Health Monitoring Systems by Using Microservices. Case Study: Fall Detection Encompassed into Connected Care 24

Delivering Improved Care through Remote Health Monitoring Sy...

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24th international conference on control Systems and Computer science, CSCS 2023

作者： Ianculescu, Marilena Alexandru, Adriana Giura, Ionut-Emanuel Vasilevschi, Ana-Mihaela National Institute for Research and Development in Informatics Communication Digital Applications and Systems Department Bucharest Romania University Politehnica of Bucharest Doctoral School of Automatic Control and Computers Bucharest Romania Counselors Department National Institute for Research and Development in Informatics Târgovişte Romania Faculty of Electrical Engineering Electronics and Information Technology Târgovişte Romania Valahia University of Târgovişte Târgovişte Romania

ISBN: (纸本)9798350313390

Based on today's modern technologies, patient care can be provided remotely, in a connected way, being, at the same time, personalized, patient-centered and proactive. Such an approach can be achieved using Remote Health Monitoring Systems (RHMS). In case of elderly people, dramatic permanent deteriorations of their health status can be caused by falls. The seniors' health and life style monitoring and the detection and/or prevention of falls can be done by such RHMS, an example being the RO-SmartAgeing system developed inside 'Non-invasive Monitoring System and Health Assessment of the Elderly in a Smart Environment (RO-SmartAgeing)' research project. The paper presents the problem of using microservices for optimizing the architecture and functionalities of RO-SmartAgeing system, and the way in which the problems of ensuring the security of patient data can be solved. © 2023 IEEE.

关键词： Fall detection

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A Comparative Analysis of Object Detection Models for Drowsiness Detection: Evaluating Raw, Processed, and Hybrid Image Datasets with Faster R-CNN

A Comparative Analysis of Object Detection Models for Drowsi...

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international conference on electrical engineering, computing science and automatic control (CCE)

作者： Maria Laura Miranda-Leon Jesus Carlos Pedraza-Ortega Marco Antonio Aceves-Fernandez Juan Manuel Ramos-Arreguin Faculty of Engineering Autonomous University of Queretaro Santiago de Queretaro Queretaro

ISBN: (数字)9798350377545

ISBN: (纸本)9798350377552

In Mexico, last year, 5.10% of accidents attributed to human factors were related to drowsiness. Consequently, this study investigates the detection of objects to identify visible signs of drowsiness, such as the eyes and mouth, employing a Faster R-CNN model with ResNet50 and FPN. A comparative analysis uses three datasets: raw images, processed images, and a hybrid set comprising both. The results indicate that although the model trained on raw images exhibited the lowest loss and superior performance for certain classes, the model trained on processed images demonstrated the highest efficiency in training time. Meanwhile, the model trained on the hybrid set achieved a balanced performance, integrating the strengths of both preceding models.

关键词： Training Analytical models Process control Mouth Object detection Human factors Feature extraction Real-time systems Object recognition Residual neural networks

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