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检索条件"任意字段=International Conference on Sensor Technologies and Applications, SensorComm"

共 9418 条记录，以下是441-450 订阅

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Research on the Design of sensor Intelligent Defense System

Research on the Design of Sensor Intelligent Defense System

引用

2023 international conference on Advances in Artificial Intelligence and applications, AAIA 2023

作者： Tang, Zhu Cui, Yichuan Peng, Siyong Dai, Guanghua Yang, Jianjun Duan, Yanhong Air Force Early Warning Academy Hubei Wuhan430019 China

ISBN: (纸本)9798400708268

This paper analyzes the necessity of building an intelligent defense system for sensors, systematically designs the intelligent defense system from three aspects: hardware composition, Software architecture and information flow interaction, and puts forward six key support technologies for system design, namely, integrated management and control technology, Internet of Things technology, Big data and cloud computing technology, artificial intelligence technology, intelligent planning technology, and auxiliary decision-making technology, which have important application value. © 2023 Copyright held by the owner/author(s).

关键词： Systems analysis

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Opportunistic RL-based WiFi Access for Aerial sensor Nodes in Smart City applications

Opportunistic RL-based WiFi Access for Aerial Sensor Nodes i...

引用

2023 international conference on Smart applications, Communications and Networking, SmartNets 2023

作者： Ariman, Mehmet Cakir, Lal Verda Ozdem, Mehmet Canberk, Berk Istanbul Technical University Department of Computer Engineering Istanbul Turkey Türk Telekom Turkey Edinburgh Napier University School of Computing Engineering and the Build Environment United Kingdom

ISBN: (纸本)9798350302523

Unmanned air vehicles are becoming widespread, driven by improved wireless technologies. However, the WiFi technology used for communication has a highly crowded and unevenly distributed channel occupancy in its spectrum. To overcome this, WiFi resources need to be utilized efficiently. Therefore, this paper proposes the Opportunistic Reinforcement Learning-based WiFi Access scheme, which exploits intermittent channel occupancy to solve the NP-hard channel assignment problem. As a result, the proposed model has improved the accurate channel selection on the UAVs by 9%, performing 91% accuracy, compared to the trivial channel scoring-based selection algorithms. © 2023 IEEE.

关键词： Deep learning

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Blind Spot Detection on Vehicles Using a Distance sensor with Fuzzy Logic Sugeno Method

Blind Spot Detection on Vehicles Using a Distance Sensor wit...

引用

2023 international conference on Data Science and Its applications, ICoDSA 2023

作者： Saputra, Ardiansa Pahlevi, Rizka Reza Nuha, Hilal H. Telkom University Department of Information Technology Bandung Indonesia Telkom University School of Computing Bandung Indonesia

ISBN: (纸本)9798350305197

Blind spots are a significant contributor to car accidents, prompting continuous efforts by automakers to develop technologies aimed at mitigating this issue. In this context, the use of object detection sensors that facilitate communication between drivers in blind spots has gained traction. This study addresses the pressing concern of road accidents in Indonesia, where statistics reveal a rising trend. By employing fuzzy logic with the Sugeno method, this research proposes a blind spot object detection system for trucks. The system integrates five ultrasonic sensors strategically positioned at the front, left, right, and rear sides of the truck, coupled with fuzzy logic algorithms to process the sensor data. Visual and auditory warning signals, such as buzzers and LEDs, are utilized to alert drivers of potential hazards. The device incorporates input values derived from observation results, utilizing the coefficient value of the sensor distance data. The validity test, employing R2 (R Square), reveals a remarkably strong correlation. This conclusion is supported by the author's meticulous observation of distance data from each sensor, performed 30 times, which yielded an average correlation value of 0.99. The proposed system showcases its efficacy in addressing blind spot-related risks and promises improved road safety through intuitive decision-making mechanisms that are easily comprehensible to drivers. © 2023 IEEE.

关键词： Object detection

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Efficient and Non-Invasive Rice Moisture Quantification Using Coupled Lines Microwave sensor Design 8

Efficient and Non-Invasive Rice Moisture Quantification Usin...

引用

8th international conference on Information Technology, InCIT 2024

作者： Phanomupatum, Pratya Phromloungsri, Ravee Wongpatsa, Decha Pongthavornkamol, Tiwat Saeng-On, Phatcharanat Sonasang, Somchat Nakhon Phanom University Faculty of Industrial Technology Nakhon Phanom Thailand Udon Thani Rajabhat University Faculty of Technology Udon Thani Thailand Nakhon Phanom University Faculty of Agriculture and Technology Nakhon Phanom Thailand National Science and Technology Development Agency Location and Automatic Identification System Research Team Nectec Pathum Thani Thailand Faculty of Industrial Technology Nakhon Phanom Thailand

ISBN: (纸本)9798350366303

This research presents the design, simulation, and experimental validation of a novel microwave sensor for noninvasive moisture measurement in rice. The sensor employs coupled microstrip lines fabricated on an FR4 substrate, designed to operate at a center frequency of 900 MHz with a quarter-wavelength configuration. The Advanced Design System software was utilized for the simulation, where key parameters such as S21 and phase response were analyzed across a frequency range of 0.1 to 3 GHz. The sensor was fabricated and tested using a Vector Network Analyzer, where the moisture content in rice samples was varied incrementally, and the sensor's performance was evaluated based on the changes in transmission characteristics. The results demonstrated the sensor's potential for accurate moisture detection in rice, showcasing its feasibility as a noninvasive measurement technique in agricultural applications. This study contributes to the development of efficient, real-time moisture measurement technologies in the food processing industry. © 2024 IEEE.

关键词： Microwave sensors

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Data Privacy and Confidentiality in Healthcare applications of IoT-Enabled Wireless sensor Networks 2

Data Privacy and Confidentiality in Healthcare Applications ...

引用

2nd international conference on Smart technologies for Smart Nation, SmartTechCon 2023

作者： Vinola, C. Solainayagi, P. Kuppusamy, P.G. Premi, Godwin Srinivasan, C. Department of Computer Science and Engineering Sri Sairam College of Engineering Anekal Karnataka Bengaluru India Department of Computer Science and Engineering Aarupadai Veedu Institute of Technology Tamil Nadu Paiyanoor India Andhra Pradesh Puttur India Department of Electronics and Communication Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350305418

In this paper, a comprehensive framework for protecting sensitive healthcare information in Internet of Things (IoT)-enabled Wireless sensor Network (WSN) is presented. Sensitive medical data is protected by the proposed architecture's usage of secure data transmission protocols, encryption, access control, and authentication. It also looks at how the General Data Protection Regulation (GDPR) and other data privacy regulations might affect IoT-enabled healthcare infrastructure. The study results indicate a need for more privacy and security education and implementation throughout the healthcare, technology, government, and user communities. The need of teaching healthcare professionals and patients about the dangers of sharing personal information online and the importance of managing data ethically is discussed. New loopholes and dangers can only be patched if security is regularly assessed, audited, and improved. This research paper sheds light on the problems of privacy and confidentiality in WSN healthcare applications enabled by the Internet of Things. The effort aims to safeguard and defend healthcare IoT adoption and enhance patient care by offering a complete framework that emphasizes regulatory compliance and appropriate data management. © 2023 IEEE.

关键词： Data Privacy Data Security Encryption Secure Communication Protocols Wireless sensor Networks

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Fuzzy-Based Routing Scheme with Reliable Transmission Enhanced by Deep Learning for Wireless sensor Networks

Fuzzy-Based Routing Scheme with Reliable Transmission Enhanc...

引用

2024 international conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Titus, T. Joby Aakash Raja, K.M. Bharathevaasan, G. Abishek, V.S. Sri Krishna College of Engineering and Technology Department of Ece Coimbatore India

ISBN: (纸本)9798331510022

The advent of fifth-generation (5G) communication technologies is set to transform the global Internet of Everything (IoE) by linking numerous physical devices to the Internet. This extensive connectivity plays a vital role in IoT applications such as smart homes, city management, transportation, surveillance and the Internet of Medical Things (IoMT). Although wireless communication seeks to achieve broader coverage, lower latency, higher throughput, and increased reliability, challenges remain in optimizing limited communication resources and enhancing coding, modulation, and channel estimation methods. Managing transmission power is essential for mitigating interference and conserving energy. Our study introduces a fuzzy logic optimization routing (FLOR) method designed to extend the lifespan of Wireless sensor Networks (WSNs) by making routing decisions based on nodes' energy levels and network distances. We evaluate FLOR's performance against current methods, showing the significant improvements in throughput, packet delivery ratio, average end-to-end delay and normalized routing overhead. In addition a deep learning-based strategy is proposed for sub-band assignment and power control in IoT cellular networks. Utilizing the convolutional neural networks (CNNs), we enhance the resource allocation, decrease latency, and improve energy efficiency. Our results demonstrate that deep learning methods outperform traditional techniques, offering faster speeds, reduced latency, and better energy efficiency. The integration of deep learning with edge computing and network slicing further benefits various IoT applications, boosting network performance, reliability, and energy efficiency. © 2024 IEEE.

关键词： Channel estimation

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AUTOMATED PREFORMING WITH A SMART MOULD APPROACH FOR EFFICIENT LIQUID RESIN INFUSION IN AEROSPACE applications 23

AUTOMATED PREFORMING WITH A SMART MOULD APPROACH FOR EFFICIE...

引用

23rd international conference on Composite Materials, ICCM 2023

作者： Helber, F. Deutsch, Z. Linne, H. Sonnemann, T. Dungern, F. Middendorf, P. Pfaffenwaldring 31 Stuttgart70569 Germany Israel Aerospace Industries ltd. Ben-Gurion International Airport Lod70100 Israel INVENT GmbH Christian-Pommer-Str. 47 Braunschweig38112 Germany

This paper presents the assessment of non-conventional materials and consumables as well as the development of novel technologies and processing strategies for the manufacturing of thermoset composite materials in order to reduce the ecological footprint of structural components in the aerospace industry. The particular technologies, which are being addressed, involve, novel automated preforming concepts with dry unidirectional fabrics, optimized infusion processes with a sustainable polymer resin and corresponding infusion strategies, a novel smart mould with micro-vibrations for improved fiber wetting and integrated sensor technologies, resulting in a significant reduction of energy consumption during composite manufacture and consequently a minimization of production costs and the environmental footprint of composite manufacturing technologies. Lastly, a stabilizer panel, with slight curvature and integrated stiffener elements was realized using the aforementioned technologies in order to demonstrate the feasibility and ecological benefits. This paper presents the results of the Clean Sky 2 ecoTECH project and highlights its potential and ecological benefits. © 2023 international Committee on Composite Materials. All rights reserved.

关键词： Aerospace applications

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5G-Based Body sensor Network for Real-Time Feedback in Running 12

5G-Based Body Sensor Network for Real-Time Feedback in Runni...

引用

Proceedings of the 12th international conference on Sport Sciences Research and Technology Support, icSPORTS 2024

作者： Mayr, Sebastian Rieser, Harald Human Motion Analytics Salzburg Research Forschungsgesellschaft MbH Salzburg Austria

ISBN: (纸本)9789897587191

Immediate feedback is vital in sports and motor learning. Traditionally, coaches provide this feedback. However, recent developments in wearable sensing and feedback devices, state-of-the-art processing algorithms and sensor data integration allow for new applications and insights. While this allows for more direct feedback, it also introduces new demands on feedback systems in terms of network transmission speed, energy consumption and needed calculation power. The 5G networking standard is a promising technology to address these issues. It promises reduced energy usage, high availability, latency in the low millisecond range and high data rates up to 10 Gbps. Despite these characteristics, there has not been much research on the use of 5G in sports biofeedback systems. Therefore, this work aims to assess the usability of 5G for a real-time feedback system in the sports context. We did this by developing a distributed feedback system for the assessment of running gait symmetry. The system utilizes internal smartphone IMU as sensors and employs a 5G infrastructure for data transmission to an offsite server for the calculation of running metrics and generation of the feedback signal. Pilot tests, using the feedback system, showed mean roundtrip times of 140.14ms (sd = 14.47ms) for outdoor use and 128.92ms (sd = 25.83ms) for indoor use. These results indicate that promised low latencies by the 5G standard are currently not reachable outside of controlled testing environments. Nonetheless, as these times are below average reaction times in recreational athletes (150ms) it is still promising for real-time feedback applications in running. Copyright © 2024 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Body sensor networks

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Application of Artificial Intelligence Techniques to Detect Water Stress 21

Application of Artificial Intelligence Techniques to Detect ...

引用

2024 IEEE/ACS 21st international conference on Computer Systems and applications, AICCSA 2024

作者： Dorai, Marwa Abdellaoui, Mehrez Douh, Bouthaina Douik, Ali National Engineering School of Sousse University of Sousse NOCCS Laboratory Tunisia Higher Institute of Computer Science and Communication Technologies University of Sousse Tunisia Higher Institute of Agronomic Sciences of Chott Mariem University of Sousse Tunisia

ISBN: (纸本)9798331518240

Water stress is a critical issue that significantly affects agricultural productivity worldwide, particularly in the context of climate change and diminishing water resources. Conventional methods for detecting water stress, such as visual inspections and ground sensors, often lack the precision, costeffectiveness, and scalability needed for modern agricultural demands. Recent advances in artificial intelligence (AI) offer innovative solutions by leveraging complex data from multiple sources. This research aims to develop a multimodal AI model that integrates satellite imagery, drone data, and ground IoT sensors to improve the accuracy and timeliness of water stress detection. By combining Convolutional Neural Networks (CNNs) for image analysis, machine learning algorithms for sensor data interpretation, and advanced data fusion techniques, the proposed model captures water stress indicators from various perspectives, enhancing sensitivity and specificity. The expected outcomes include significant improvements in precision and responsiveness compared to traditional single-source methods. This approach aims to optimize irrigation, minimize crop losses, and support sustainable water management, providing a valuable tool for precision agriculture. © 2024 IEEE.

关键词： Convolutional neural networks

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Dynamic Real-Time Spatio-Temporal Acquisition and Rendering in Adverse Environments 1

引用

9th international conference on Geographical Information Systems Theory, applications and Management (GISTAM)

作者： Dutta, Somnath Ganovelli, Fabio Cignoni, Paolo Italian Natl Res Council CNR Inst Informat Sci & Technol Alessandro Faedo ISTI Via Giuseppe Moruzzi 1 I-56124 Pisa Italy

ISBN: (数字)9783031602771

ISBN: (纸本)9783031602764;9783031602771

This paper introduces NausicaaVR, a novel hardware/software system designed to acquire and render intricate 3D environments, with a particular emphasis on challenging and adverse contexts. In doing so, we navigate the complex landscape of system calibration and rendering, while seamlessly integrating data from multiple sensors. We explore the distinctive challenges inherent in adverse environments, juxtaposing them against conventional automotive scenarios. Through a comprehensive exposition of all constituent elements of the NausicaaVR system, we offer transparent insights into the encountered obstacles and the intricate decisions that were instrumental in surmounting them. This study seeks to illuminate the developmental trajectory of NausicaaVR and analogous systems, thereby furnishing a repository of knowledge and understanding poised to benefit future research and the pragmatic implementation of such cutting-edge technologies.

关键词： Multi-sensor calibration Real-time rendering Virtual reality

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