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6th International conference on Computing and Informatics, ICCI 2024

作者： Alabyad, Nesma Hany, Ziad Mostafa, Abdelrahman Eldaby, Reem Tagen, Ibrahim Ayman Mehanna, Amal Future University In Egypt Cairo Egypt

ISBN: (纸本)9798350373875

This paper explores the evolution of self-driving cars, from early radio-controlled prototypes to today's advanced autonomous vehicles, highlighting key milestones such as Houdina Radio Control's 1920s efforts and Carnegie Mellon University's Navlab project in the 1980s. Recent advancements driven by industry leaders like Google, Tesla, and Uber incorporate advanced technologies, including sensors, cameras, radar, and lidar, empowering self-driving cars for autonomous navigation. The literature review in Frontiers in Future Transportation focuses on performance metrics for automated driving systems, discussing methodologies for quantifying obstacle threats and enhancing human-like perception and response mechanisms, with a significant emphasis on deep learning methods such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). Object detection algorithms' dynamic evolution, influenced by CNNs, is explored, and the integration of hardware accelerators like GPUs, FPGAs, and specialized AI accelerators is highlighted for real-time responsiveness. Deep learning applications in self-driving cars, including obstacle detection, lane recognition, and traffic sign and light recognition, are outlined. Vision sensor-based obstacle detection using monocular and binocular approaches is discussed, emphasizing the importance of binocular vision technology. Lane recognition's significance for deviation warning, collision prevention, and path planning is highlighted, along with deep learning approaches such as John et al.'s lane detection algorithm. Traffic sign and light recognition are explored for safety and regulatory compliance, utilizing CNNs and Deep Neural Networks (DNNs). The discussion on sensors covers simultaneous localization and mapping (SLAM) using both passive (digital cameras) and active sensors (LIDAR, RADAR), emphasizing the integration of sensors and pre-existing maps to enhance the SLAM process and contribute to the overall perception of a

关键词： Autonomous vehicles

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Bridging Hardware and Software: A Holistic Approach to Home Automation via IOT

Bridging Hardware and Software: A Holistic Approach to Home ...

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2024 International conference on Computer, Electronics, Electrical Engineering and their applications, IC2E3 2024

作者： Manoj, P. Karthik Reddy, K.V. Raghu, Kavya Rudresh, M.D. M S Ramaiah Institute of Technology Dept. of ECE Bangalore India M S Ramaiah Institute of Technology Dept. of TCE Bangalore India Kalpataru Institute of Technology Dept. of ECE Tiptur India

ISBN: (纸本)9798350388534

The Internet of Things (IoT) has emerged as a transformative paradigm, revolutionizing various aspects of modern life, including residential living. As the world becomes increasingly interconnected, the integration of IoT technologies into home automation systems holds immense relevance in optimizing comfort, efficiency, and security within households. This research paper explores the significance of IoT in the context of a home automation project leveraging a Node MCU-Flask-React architecture. In today's fast-paced world, the demand for smart solutions that streamline daily tasks and enhance quality of life is ever-growing. IoT-based home automation offers a compelling solution by enabling remote control and monitoring of household devices through interconnected systems. The project described herein exemplifies the practical application of IoT principles, demonstrating how hardware and software can seamlessly collaborate to create intelligent environments tailored to individual preferences. The relevance of IoT in home automation extends beyond mere convenience;it encompasses broader implications for energy conservation, safety, and resource optimization. By integrating sensors, actuators, and data analytics capabilities, IoT-enabled systems can intelligently adapt to user behavior, optimize energy consumption, and enhance home security protocols. Such advancements are crucial in addressing contemporary challenges related to energy sustainability and urban living. Moreover, the proposed project underscores the utilization of smart technologies, making advanced automation capabilities accessible to a broader audience. By leveraging open-source frameworks like Node MCU, Flask, and React, the barriers to entry for developing and deploying IoT solutions are significantly reduced, fostering innovation and collaboration in the field. This research paper highlights the profound relevance of IoT in reshaping residential living experiences. it elucidates how IoT technologie

关键词： sensor nodes

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Fine-grained Spatiotemporal Features-Based for Anomaly Detection in Microservice systems 24

Fine-grained Spatiotemporal Features-Based for Anomaly Detec...

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24th IEEE International conference on High Performance Computing and Communications, 8th IEEE International conference on Data Science and systems, 20th IEEE International conference on Smart City and 8th IEEE International conference on Dependability in sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Yang, Xikang Wang, Juan Zhou, Biyu Wang, Wang Liu, Wantao Dong, Yangchen Institute of Information Engineering Chinese Academy of Sciences China School of Cyber Security University of Chinese Academy of Sciences China China Academy of Information and Communications Technology Beijing China

ISBN: (纸本)9798350319934

More and more applications use microservice architecture. Protecting the reliability of the microservice system is very important for the stable operation of applications. However, the complexity of microservice systems poses a great challenge to operation and maintenance. Researchers have proposed a series of anomaly detection algorithms, which can automatically detect the anomalies of cloud systems in time. However, for the microservice system with a complex spatial structure, there is no effective method to represent the fine-grained features of the internal metric level of the microservice. To solve this problem, we propose a fine-grained metric-level spatial feature graph TopoMetrics and use a spatiotemporal neural network STAD to obtain the spatiotemporal features of microservices, which can accurately detect the anomalies of complex microservices. We compare STAD with the most advanced algorithms in three open microservice workloads. The experimental results show that the average precision of STAD is significantly higher than that of the most advanced baseline method. © 2022 IEEE.

关键词： Anomaly detection

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Design and Optimization of High-Performance Health Monitoring systems Using advanced sensor Networks

Design and Optimization of High-Performance Health Monitorin...

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advanced Computing & Communication Technologies (ICACCTech), International conference on

作者： Heena Mehta Mukesh Singla Dept. of Computer Science and Engineering Baba Mastnath University Rohtak Haryana India

ISBN: (数字)9798331519056

ISBN: (纸本)9798331519063

This research elucidates the development and optimization of advanced sensor network-based health monitoring systems. In response to the increasing need for accurate health data in real-time, advanced gadgets capable of continuously monitoring essential indicators have been created. Contemporary sensor technologies, such as biosensors, IoT devices, and WSN s, enable these systems to facilitate data collection and processing with little disturbance. Optimization techniques like PSO, including machine learning algorithms and energy conservation procedures, are used to enhance the system's performance, reliability, and battery longevity. The study focuses on developing robust and scalable systems suitable for various healthcare applications, while also investigating data processing, communication protocols, network architecture, and sensor selection. advanced sensor networks will be crucial for future health monitoring, as research indicates substantial improvements in monitoring accuracy, system efficiency, and patient outcomes. Present approach is supposed to provide scalable and efficient solution. Moreover, it would support privacy in order to provide secure solution.

关键词： Wireless sensor networks Accuracy Protocols System performance Medical services Network architecture Real-time systems Biosensors Monitoring Optimization

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Edge Computing in Wireless Sensing applications 11

Edge Computing in Wireless Sensing Applications

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11th Mediterranean conference on Embedded Computing (MECO) / 3rd Summer School on Cyber-Physical + systems and Internet of Things (CPS and IoT)

作者： Santejudean, Tudor Voicu Mois, George Dan Sanislav, Teodora Folea, Silviu Corneliu Tech Univ Cluj Napoca Dept Automat Cluj Napoca Romania

ISBN: (纸本)9781665468282

Edge computing has emerged as the solution to the continuously increasing numbers of Internet-connected devices and to the ever increasing amounts of data transmitted by them. Through the use of advanced algorithms and hardware components it allows sensor data processing at the source and reduces the volumes of data transmitted within the network. This paper focuses on the idea of edge computing, looks at some of the most important achievements in the field, and presents a use case system that shows how edge intelligence is becoming more common. The developed use case system is an environmental wireless sensor that is able to run for long periods of time on a single coin-cell battery while measuring parameters like equivalent CO2 (carbon dioxide) and VOC (Volatile Organic Compounds). This was made possible through the device's design, components, and advanced firmware, that uses high-level signal processing and fusion algorithms.

关键词： Edge computing Internet-of-Things wireless sensor

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3-Axis Force Estimation of a Soft Skin sensor using Permanent Magnetic Elastomer (PME) Sheet with Strong Remanence

3-Axis Force Estimation of a Soft Skin Sensor using Permanen...

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IEEE/ASME International conference on advanced Intelligent Mechatronics (AIM)

作者： Wang, Yushi Kamezaki, Mitsuhiro Wang, Qichen Sakamoto, Hiroyuki Sugano, Shigeki Waseda Univ 1 Chome 104 Totsukamachi Shinjuku City Tokyo 1698050 Japan Nippon Paint Holdings Corp Ltd Tokyo Japan

ISBN: (数字)9781665413084

ISBN: (纸本)9781665413084

This paper describes a prototype of a novel Permanent Magnetic Elastomer (PME) sheet based skin sensor for robotic applications. Its working principle is to use a Hall effect transducer to measure the change of magnetic field. PME is a polymer that has Neodymium particles distributed inside it, after strong magnetization for anisotropy, the PME acquires strong remanent magnetization that can be comparable to that of a permanent magnet, in this work, we made improvement of the strength of the magnetic field of PME, so it achieved magnetic strength as high as 25 mT when there is no deformation. When external forces apply on the sensor, the deformation of PME causes a change in the magnetic field due to the change in the alignment of the magnetic particles. Compared with other soft magnetic sensors that employ similar technology, we implemented linear regression method to simplify the calibration, so we focus on the point right above the magnetometer. An MLX90393 chip is installed at the bottom of the PME as the magnetometer. Experimental results show that it can measure forces from 0.01-10 N. Calibration is confirmed effective even for shear directions when the surface of PME is less than 15 x 15 mm.

关键词： Magnetic field measurement Magnetometers Magnetization Robot sensing systems Particle measurements Skin Soft magnetic materials

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The Green Revolution from Space: A Survey of Satellite-Based Agricultural Monitoring systems 17

The Green Revolution from Space: A Survey of Satellite-Based...

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17th IEEE International conference on advanced Networks and Telecommunications systems, ANTS 2023

作者： Ghosh, Debjani Swarnkar, Jatin Gupta, Gunesh Rawat, Priyanka Bennett University School of Computer Science Engineering and Technology Greater Noida India

ISBN: (纸本)9798350307672

The utilization of satellite technology has brought forth a new era of possibilities in the field of agriculture, facilitating data-driven decisions that cater to the global need for improved agricultural productivity. This research paper extensively examines the crucial role played by satellite imagery in revolutionizing agricultural practices. We delve into the technical foundations of satellite sensors, which include optical, thermal infrared, radar, hyperspectral, and lidar sensors, establishing a comprehensive understanding of the diverse data sources. Moving into the realm of satellite image processing, we provide explanations of radiometric calibration, geometric correction, atmospheric correction, noise reduction, and image enhancement techniques, ensuring the accuracy and reliability of the data. Additionally, we shed light on the multifaceted applications of satellite imagery in agriculture, encompassing crop health monitoring, precision agriculture, crop growth monitoring, irrigation management, soil mapping, and pest management. While acknowledging the challenges and limitations, we address the technical complexities, economic considerations, social implications, and environmental impacts crucial for developing sustainable satellite-based agricultural solutions. Finally, we explore the promising trends and research directions, ranging from advanced sensor technologies to climate-resilient strategies, with the aim of advancing efficient and sustainable agricultural systems. This paper offers a comprehensive understanding of the mutually beneficial relationship between satellite technology and agriculture, contributing to the creation of resilient and sustainable agricultural systems for the future. © 2023 IEEE.

关键词： Image enhancement

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Edge Intelligence-Based E-Health Wireless sensor Network systems 23

Edge Intelligence-Based E-Health Wireless Sensor Network Sys...

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23rd IEEE/ACIS International conference on Computer and Information Science, ICIS 2023

作者： Hu, Bintao Isaac, Matilda Abdul Majeed, Anwar P.P. Liu, Hengyan School of Internet of Things Xi'an Jiaotong-Liverpool University Suzhou China School of Robotics Xi'an Jiaotong-Liverpool University Suzhou China School of Ai and Advanced Computing Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798350345841

In order to support delay-sensitive applications of healthcare internet of things (HIoT) network systems, it is necessary to allow e-health wearable devices to process their computational applications at an artificial intelligence (AI) based mobile edge computing (MEC) server. Existing works mainly focused on optimising the offloading decisions of all users while minimising their corresponding energy consumption and/or transmission/processing delays. However, the huge data volumes offloading and/or privacy-preserving data processing have been largely ignored. In this paper, we consider an edge intelligence-based e-health wireless sensor network system, where the queues at the MEC server follow M/M/1 queueing model. To minimise energy consumption among all e-health wearable devices, we propose to jointly optimise the FL model task offloading decisions of all e-health wearable devices while guaranteeing delay constraints (which include the transmission delay, queueing delay and processing delay) and global/local FL training accuracy. This is achieved by devising an FL-based edge intelligence queueing offloading decision optimisation algorithm. Simulation results demonstrate that our proposed algorithm achieves a much lower maximum service delay than the benchmarks. © 2023 IEEE.

关键词： Energy utilization

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Curving Motion Control of a Traction Rail Mover Using a Dual BLAC Motor Drive

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IEEE TRANSACTIONS ON INDUSTRY applications 2023年第1期59卷 1175-1183页

作者： Ok, Sangjae Bae, Jongnam Lee, Dong-Hee Kyungsung Univ Dept Mechatron Engn Busan 48434 South Korea

This article presents an improved position control method of an overhang-type rail system considering a curved path. The designed system is driven by two BLAC (brushless ac) motors, and the moving position is controlled based on the signal from a simple Hall position sensor mounted on the motor without any absolute position sensors. The rail is composed of both linear and curved paths. For the linear rail, the two motors are controlled to rotate in the same speed. However, in a curved path, the two motors must have different moving distance according to the curvature. Generally, in order to determine the proper motion commands for both traction motors, the actual curvature state and position have to be detected by a potentiometer or an encoder equipped with linear position sensor, but this method significantly increases complexity and cost of the system. This article aims to solve this problem by using a low-cost semiconductor IMU (inertia measurement unit) to estimate the actual rail condition. The IMU will then estimate the heading angle variation to compensate the motion commands for the two BLAC motors without any additional external absolute sensors. As a result, a balanced and improved motion can be achieved for an arbitrary rail path. Practical experiments using an overhang-type rail traction system were performed to verify the effectiveness of the proposed control scheme. The results show the advanced control performance in both linear and curved path, and also a smooth transition between them both.

关键词： Rails Traction motors Brushless motors AC motors Rotors Permanent magnet motors Synchronous motors Curving motion dual BLAC (brushless ac) motor Hall sensor heading angle estimation turning

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Real-time Heart Rate Estimation Using PVDF Flexible Piezoelectric sensor Based on Machine Learning 2

Real-time Heart Rate Estimation Using PVDF Flexible Piezoele...

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2nd International conference on advanced Manufacturing Technology and Manufacturing systems, ICAMTMS 2023

作者： Luo, Shijian Fang, Ting Dong, Chong Han, Jiaming School of Electrical and Information Engineering Anhui University of Technology Anhui Ma’anshan243032 China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Anhui University of Technology Anhui Ma’anshan243032 China

ISBN: (纸本)9781510667327

To achieve non-invasive, non-contact, and real-time heart rate monitoring, proposed a pulse signal acquisition system using PVDF (Polyvinylidene Fluoride) piezoelectric film. In order to address the issue of errors in heart rate extraction caused by differences in the morphology of pulse signals across individuals or in different states, the K-means clustering algorithm was innovatively used to locate the peak of pulse waveforms in different states and constructed a heart rate data set. Real-time heart rate monitoring by training a large number of pulse signal samples with the proposed CNN-LSTM network model. Experimental results demonstrated that the performance metrics of this model, including the MAE (Mean Absolute Error), RMSE (Root Mean Square Error), and R2(Coefficient of Determination), are 0.2517, 0.3395, and 0.9863, respectively. the maximum error between the proposed system and the standard instrument within 3 minutes was only 1.55 beats/minute, indicating that the system exhibits high accuracy and reliability, and holds great potential for applications in heart rate detection. © 2023 SPIE.

关键词： Mean square error

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