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Joint Beamforming Design Based on Graph Neural Convection Diffusion Network

Joint Beamforming Design Based on Graph Neural Convection Di...

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intelligent Communication, Sensing and Electromagnetics (ICSE), International conference on

作者： Wenqing Li Kai Lin Hanjie Yang Xuening Wang School of computer science and technology Dalian University of Technology Dalian China

ISBN: (数字)9798350354935

ISBN: (纸本)9798350354942

intelligent Reflecting Surface (IRS), as an emerging green communication technology, improves the communication quality of wireless communication networks by reconfiguring the wireless propagation environment. This paper focuses on IRS-assisted multiple input single output wireless communication systems, considering the j oint optimization of transmission beamforming at the Access Point (AP) and reflection beamforming of passive phase shifters at the IRS under the constraint of total transmission power at the AP to maximize the sum rate of the users. To solve the nonconvex optimization problem of multivariable coupling, this paper develops a graph neural convection diffusion model based on the convection diffusion equation to solve the joint beamforming design. The experimental results show that under the same conditions, the proposed algorithm achieves a larger sum rate of users compared to other algorithms, demonstrating its effectiveness.

关键词： Wireless sensor networks Array signal processing Neural networks Diffusion models Mathematical models Regulation Reflection sensors Convection Optimization

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intelligent Safety Helmet For Miners Using Arduino Leveraging Support Vector Machines

Intelligent Safety Helmet For Miners Using Arduino Leveragin...

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Network, Multimedia and information Technology (NMITCON) International conference on

作者： S. Thangam Aryan Kothari V. R. N. S. Nikhil Namana Rohit J. Jesy Janet Kumari Amrita School of Computing Bangalore Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350372892

ISBN: (纸本)9798350372908

In the fast-evolving era of mining and development, ensuring the safety and well-being of miners remains paramount. Recent advancements in the Internet of Things (IoT) have paved the way for innovative solutions in mining techniques. This paper introduces an intelligent mining helmet equipped with Arduino UNO, ESP8266 wireless connectivity, and an array of sensors (gas, temperature, humidity, and ultrasonic). These sensors monitor environmental conditions in real-time, coupled with an alarm system to enhance miner safety and operational efficiency. This implementation of the safety helmet employs a multi-approach methodology, integrating support vector machines (SVMs) for predictive analysis of hazardous conditions. The SVM model is trained on historical data to predict potential risks based on current sensor readings and Our Model got a very good accuracy. The intelligent helmet continuously checks environmental conditions, and in the event of potential hazards, such as high gas levels or elevated temperatures, it alerts miners with a buzzer, prompting immediate evacuation to prevent accidents. The results demonstrate that the intelligent helmet significantly improves safety by reducing the response time to hazardous conditions. Additionally, it optimizes working conditions through real-time monitoring and predictive maintenance by analyzing environmental trends. Such an SVM-based predictive model is very important in minimizing false alarms and enhancing the reliability of the system.

关键词： Support vector machines Temperature sensors Head Predictive models Real-time systems Hazards Data models Safety intelligent sensors sensor arrays

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Research on Fault Prediction and Maintenance of RGL System Combining Electrical and Electronic Technology and Artificial Intelligence 2

Research on Fault Prediction and Maintenance of RGL System C...

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2nd IEEE International conference on Image processing and Computer Applications, ICIPCA 2024

作者： Liu, Jianjun Gao, Chao He, Kaibing Liu, Yi Zhao, Xiaolei Liu, Jiancheng Chang, Xincai Taishan Nuclear Power Joint Venture Co. Ltd Taishan China Cgn Digital Technology Co. Ltd Cgnpc Beijing China

ISBN: (纸本)9798350360240

The uninterrupted functioning of modern society heavily relies on the reliability and stability of power equipment. The integration of electrical and electronic technologies with artificial intelligence in the form of the RGL system introduces innovative concepts and methodologies for managing power infrastructure efficiently. This paper aims to study an RGL (power equipment operation management) system that combines electrical and electronic technology and artificial intelligence, focusing on its fault prediction and maintenance. First, this article provides an in-depth analysis of the structure and principles of the RGL system, focusing on its advantages in power equipment monitoring and control. By introducing advanced sensor technology and data collection methods, the RGL system can obtain the operating status data of power equipment in real time, and use artificial intelligence algorithms to perform real-time analysis to achieve early identification of potential faults. Secondly, the paper studies the application of RGL system in fault prediction in detail. By establishing a fault prediction model based on big data and machine learning, the RGL system can comprehensively monitor and analyze power equipment and discover factors that may cause equipment failure in advance. This not only helps improve equipment reliability, but also reduces the impact of sudden failures on the power system. Finally, this article explores the practical application of RGL systems in fault maintenance. By introducing intelligent maintenance strategies, the RGL system can formulate accurate maintenance plans based on the actual operating status of the equipment and predicted fault information, improve maintenance efficiency, and reduce maintenance costs. © 2024 IEEE.

关键词： Deep neural networks

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IoT-based virtual sensing application for Bridge Static Deflection estimation via Data-Driven approaches at the Edge

IoT-based virtual sensing application for Bridge Static Defl...

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Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), IEEE International conference on

作者： Leonardo Iacussi Paolo Chiariotti Diego Melpignano Alfredo Cicada Dept. of Mechanical Engineering Politecnico di Milano Milan Italy STMicroelectronics Agrate Brianza Italy

ISBN: (数字)9798350378009

ISBN: (纸本)9798350378016

This research investigates the enhancement of low-cost sensor performances using data-driven approaches by deploying models directly at the edge. An experimental setup, consisting of a bridge model and a vehicle equipped with a smart sensor, was used to scan the bridge deflection and reconstruct the mid-span displacement caused by the vehicle passage. Two data driven models have been compared to find the best performing to be deployed at the edge. The findings demonstrate that incorporating physics-related features into the training process improves both model accuracy and computational efficiency on microcontrollers, significantly reducing the required computational effort and processing time. Moreover deploying algorithms at the edge offers greater flexibility within an IoT infrastructure, facilitating efficient information exchange between smart sensor nodes, gateways, and the cloud through wireless technologies.

关键词： Bridges Wireless communication Training Wireless sensor networks Cloud computing Microcontrollers Computational modeling Logic gates Computational efficiency intelligent sensors

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Analysis of sensor Technologies for Structural Health Monitoring in Civil Engineering Applications

Analysis of Sensor Technologies for Structural Health Monito...

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Automation and Computation (AUTOCOM), International conference on

作者： Trapty Agarwal Ayush Gandhi Yogomaya Mohapatra Jagtej Singh Dimple Bahri V. Venkata Ramesh Reddy Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India Department of Civil Engineering School of Engineering and Technology JAIN (Deemed to be University) Bangalore Karnataka India Sponsored Research Presidency University Bangalore Karnataka India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Civil engineering is considered complete with structural health monitoring SHM, a continuous process in which structures are tested for their health and integrity, ensuring they remain safe and reliable. Recent advancements in sensor technologies for SHM have improved the empirical side of structural performance. The advancement of sensor technologies for SHM is largely related to implementing wireless and smart sensors. It is easily fixable and provides real-time information on the strain, temperature, vibration, etc. Wireless and smart sensors can also be deployed in difficult-to-access or non-safe areas, allowing for an increased size of monitored structures. In addition, the emergence of sensor technologies has resulted in smart algorithms and data analytics methods suitable for SHM. Such algorithms process huge amounts of data and detect potential structural problems or anomalies before any expected maintenance intervention.

关键词： Temperature sensors Wireless communication Temperature measurement Vibrations Wireless sensor networks Real-time systems Maintenance Monitoring Civil engineering intelligent sensors

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Development and Deployment of an Internet of Things (IoT) Enabled intelligent Medication Dispensing Solution 9

Development and Deployment of an Internet of Things (IoT) En...

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9th IEEE International conference on Smart Structures and Systems, ICSSS 2023

作者： Harshini, D.A. Amiritavarshini, S. Sudha, V. Raja, R. Sona College of Technology Department of Ece Salem636005 India Muthyammal Engineering College Department of Eee Rasipuram637408 India

ISBN: (纸本)9798350384208

This paper presents the design of a smart dispenser system that utilizes Internet of Things (IoT) technology and integrates with a mobile application developed using the Blynk IoT platform. The system aimed to enhance medication adherence and patient safety by providing automated pill dispensing, medication reminders, and real-time monitoring capabilities. The IoT-based pill dispenser consists of a physical device equipped with compartments for storing pills, sensors to detect whether pills are taken or not, and a microcontroller for data processing and communication. The device is connected to the internet, allowing seamless interaction with the Blynk app via Wi-Fi or cellular connectivity. By integrating components like Arduino UNO, nodeMCU, a servomotor, an RTC, an IR sensor, a power supply, and a buzzer, we've designed a robust hardware system for precise medication dispensing. Our system has been rigorously tested and has demonstrated exceptional efficiency, significantly improving medication adherence rates. © 2023 IEEE.

关键词： Internet of things

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Performance Evaluation of Depth Completion Neural networks for Various RGB-D Camera Technologies in Indoor Scenarios 22nd

Performance Evaluation of Depth Completion Neural Networks ...

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22nd International conference of the Italian Association for Artificial Intelligence, AIxIA 2023

作者： Castellano, Rino Terreran, Matteo Ghidoni, Stefano Intelligent and Autonomous Systems Laboratory University of Padova Padova Italy

ISBN: (纸本)9783031475450

RGB-D cameras have become essential in robotics for accurate perception and object recognition, enabling robots to navigate environments, avoid obstacles, and manipulate objects precisely. Such cameras, besides RGB information, allow the capture of an additional image that encodes the distance of each point in the scene from the camera. Popular depth acquisition techniques include active stereoscopic, which triangulates two camera views, and Time-of-Flight (T-o-F), based on infrared laser patterns. Despite different technologies, none of them is yet able to provide accurate depth information on the entire image due to various factors such as sunlight, reflective surfaces or high distances from the camera. This leads to noisy or incomplete depth images. Neural network-based solutions have been researched for depth completion, aiming to create dense depth maps using RGB images and sparse depth. This paper presents a comparison of the data provided by different depth-sensing technologies, highlighting their pros and cons in two main benchmark setups. After an analysis of the sensors’ accuracy under different conditions, several state-of-the-art neural networks have been evaluated in an indoor scenario to assess if it is possible to improve the quality of the raw depth images provided by each sensor. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cameras

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Performance Comparison of Radar and Video for American Sign Language Recognition

Performance Comparison of Radar and Video for American Sign ...

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IEEE Radar conference (RadarConf)

作者： Rahman, M. Mahbubur Kurtoglu, Emre Taskin, Muhammet Esme, Kudret Gurbuz, Ali C. Malaia, Evie Gurbuz, Sevgi Z. Univ Alabama Dept Elect & Comp Engn Tuscaloosa AL 35401 USA Mississippi State Univ Dept Elect & Comp Engn Starkville MS USA Univ Alabama Dept Commun Disorders Tuscaloosa AL USA

ISBN: (纸本)9781728153681

In the past decade, there has been a great research in the developments of American Sign Language (ASL) enabled user interfaces and smart environments, especially using wearables, RGB and RGB-D video cameras, and radio frequency (RF) sensors. Each sensor modality provides distinct advantages and suffer from various problems. Although each sensor modality is studied for ASL recognition a comparison of video and RF based sensing performance in terms of ASL recognition is not available. This study aims to compare word level ASL recognition performance over the same 100 ASL glosses data from both RF and video sensors. A top-5 accuracy of 93% was achieved while using the RF micro-Doppler spectrogram representation in a convolutional neural network (CNN) classifier, whereas with video ASL data for the same 100 words, a top-5 accuracy of 90% was achieved. This shows that radar has comparable recognition performance to video for ASL recognition.

关键词： American Sign Language video radar RF sensors deep neural networks

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FPGA Design for Multimodal sensor Data Fusion in Autonomous Robots

FPGA Design for Multimodal Sensor Data Fusion in Autonomous ...

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Sustainable Communication networks and Application (ICSCNA), International conference on

作者： Muthukumaran Vaithianathan Shivakumar Udkar Deepanjan Roy Manjunath Reddy Senkadir Rajasekaran Samsung Semiconductor Inc. San Diego USA AMD Inc. Colorado USA NVIDIA Corporation Inc. Texas USA Qualcomm Inc. San Diego USA

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

This research study introduces a novel Field Programmable Gate Array (FPGA) design for autonomous robotics that integrates data from multiple sensors to improve their operational efficiency and decision-making. The proposed technique accomplishes real-time performance by integrating information from multiple sensors, such as LiDAR, cameras, and inertial measurement units (IMUs), using the parallel processing capabilities of FPGAs. sensor interfaces, control logic, and complex data integration algorithms are integrated into the design. Additionally, the design is adaptable and can be implemented with FPGAs. By employing Kalman filters for state prediction and decision trees for contextual classification, the design enhances accuracy and significantly reduces latency. According to the testing results, the FPGA-based system outperforms earlier existing systems in terms of processing speed and accuracy, capable of processing up to 2000 data points per second with a latency of 10ms. This research enhances autonomous robotics by delineating a comprehensive approach to the efficient integration of sensors and the processing of data in dynamic environments.

关键词： Accuracy Laser radar Multimodal sensors Robot vision systems Data integration Parallel processing Cameras Real-time systems Field programmable gate arrays Autonomous robots

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A Performance Cost/Benefit Analysis of Adaptive Computing in the Tactical Edge

A Performance Cost/Benefit Analysis of Adaptive Computing in...

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International conference on Military Communications and information Systems (ICMCIS)

作者： Alessandro Amato Harrie Bastiaansen Willem Datema Mattia Fogli Roberto Fronteddu Raffaele Galliera Johan van der Geest Thomas Kudla Pablo Sanchez Niranjan Suri Susan Watson Florida Institute for Human and Machine Cognition (IHMC) Pensacola FL USA The Netherlands Organisation for Applied Scientific Research (TNO) The Hague The Netherlands University of Ferrara Ferrara Italy Fraunhofer Institute for Communication Information Processing and Ergonomics Wachtberg Germany University of Cantabria Santander Spain US Army DEVCOM Army Research Laboratory (ARL) Adelphi MD USA Defence Research and Development Canada Ottawa Canada

ISBN: (数字)9798350373196

ISBN: (纸本)9798350373202

Tactical Edge Computing is a promising solution to address the challenges of processing and managing large volumes of data collected by sensors deployed at the tactical edge. Tactical edge networks often lack sufficient bandwidth to transfer data at high rates. Much of the sensor raw data might be uninteresting and would waste networking resources to transmit. Edge computing solves these problems by staging the processing capabilities for sensor data at the edge, close to the data source. Local data processing reduces bandwidth needs in disadvantaged tactical networks. Furthermore, it could reduce the latency of data processing and avoid congestion in the tactical network. However, static solutions that deploy edge services could also be problematic because of the unpredictability of the tactical edge - the source / location of the data may not be known a priori, and there could be significant changes, such as sensors and nodes going offline. Therefore, tactical edge computing solution must be adaptive, where services are deployed on demand based on the sensors tasked and the mission requirements. This paper presents the work of the NATO IST-193 work on adaptive tactical edge computing and its analysis on the adaptivity benefits and overhead costs involved.

关键词： Military communication Cloud computing Costs Adaptive systems Soft sensors Bandwidth Data processing

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