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检索条件"任意字段=Conference on Advanced Sensor Systems and Applications VII"

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Mechanical Modelling and Analysis of CMOS Image sensor Package 25

Mechanical Modelling and Analysis of CMOS Image Sensor Packa...

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25th Electronics Packaging Technology conference (EPTC)

作者： Lim, T. S. Sukiman, Muhamad Shafiq Jasmee, S. Masdzarif, N. D. I. ON Semicond M Sdn Bhd Lot 122Senawang Ind Estate Seremban Malaysia Univ Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Melaka Malaysia

ISBN: (纸本)9798350329575

The growth of automotive industry not only focus on power efficiency and carbon emission reduction, it also has makes further progress in the areas of advanced driver assistance systems (ADAS) and autonomous driving (AD) technologies. With the progressive technology breakthrough and heavily studies in these two areas, the demand for imaging cameras is steadily increasing to support applications such as lane detection, traffic sign detection, pedestrian/vehicle recognition and driver monitoring. Consequently, this drives higher demand for image sensor packages to meet stringent automotive reliability requirements. In the past, high reliability image sensor packages are typically with ceramic based packages, these tend to have considerably higher costs and longer development cycles than laminate-based packages which are normally used in high speed, RF or MEMS market segment. Therefore, it is important to ensure a high reliability for the laminate-based packages by studying the package design. This can be done by finite element analysis (FEA) which is a fast and cost-efficient method in analyzing the stress experienced by the package. This paper discusses the effects of different package designs on the package stress using the FEA simulation method.

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Cognitive Congestion Alleviation Framework in IoT-Enabled WSN for Next-Gen Intelligent Transport systems via Optimized Capsule Attention Network 3

Cognitive Congestion Alleviation Framework in IoT-Enabled WS...

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3rd International conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Mohandas, R. Sudha, Y. Narmatha, P. Venkata Prasad, P. Manikandan, N. Department of Electronics & Communication Engineering Chennai Institute of Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Presidency University Karnataka Bangalore India Department of Computer Science and Engineering Sri Sairam College of Engineering Karnataka Bangalore India Department of Electrical and Electronics Engineering Chaitanya Bharathi Institute of Technology Telangana Hyderabad India Department of Business Administration Kalasalingam Business School Kalasalingam Academy of Research and Education Viruthunagar Krishnankoil India

ISBN: (纸本)9798331527549

The rapid advancement of Intelligent Transportation systems (ITS) has heightened the importance of reliable, real-time data transmission in Wireless sensor Networks (WSNs). However, congestion in data-heavy Internet of Things (IoT)-enabled networks remains a critical challenge, impacting communication efficiency and decision-making in ITS. In high-density IoT-ITS applications, traditional congestion control methods are insufficient to address the complexity and dynamics of data flows. Existing solutions often fail to adapt in real time to varying traffic loads, leading to delays and data loss. There is a strong need for a congestion alleviation framework capable of intelligently prioritizing data while dynamically managing network resources to ensure seamless information exchange in large-scale deployments. This study presents a Cognitive Congestion Alleviation Framework in IoT-Enabled WSN for Next-Gen Intelligent Transport systems via Optimized Capsule Attention Network (V-CapMiAN-Parr), which combines the Vectorized Adaptive Capsule Neural Network (V-AdCapNet) and Multi-instance Attention Network (MAN), fine-tuned by the Parrot Optimizer (ParrOpt). This integration aims to effectively detect, mitigate, and prevent congestion through an advanced capsule-based attention mechanism with adaptive optimization. The suggested V-CapMiAN-Parr framework demonstrated significant improvements in congestion control, achieving data throughput efficiencies above 99.7%, packet delivery rates above 99.5%, and network reliability reaching 99.2% under high traffic loads. The model’s adaptive weighting mechanism ensures real-time responsiveness and reliability, crucial for next-gen ITS applications. The V-CapMiAN-Parr framework effectively addresses congestion issues in IoT-enabled WSNs, providing a robust, scalable solution for ITS applications. This cognitive framework’s advanced data prioritization and adaptive optimization capabilities are well-suited for enhancing the performanc

关键词： Traffic congestion

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Interferometric Fiber-Optic sensor for Electrical Partial Discharge Detection 28

Interferometric Fiber-Optic Sensor for Electrical Partial Di...

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28th International conference on Optical Fiber sensors, OFS 2023

作者： Yan, Gaocheng Chen, Jiageng Niu, Heng Qiao, Feng He, Zuyuan State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China Shangwei Technology Co. Ltd. 23 Wanghai Road Fujian Xiamen361008 China

We propose an interferometric fiber-optic sensor and investigate its ability to measure the partial discharge in electrical applications. Preferable performance can be achieved under system self-noise level of 10−6 ra... 详细信息

ISBN: (纸本)9781957171302

关键词： Partial discharges

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Distributed Algorithm for Localization of Localizable Wireless sensor Networks 1

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37th International conference on advanced Information Networking and applications, AINA 2023

作者： Kanchi, Saroja Department of Computer Science Kettering University FlintMI48504 United States

ISBN: (数字)9783031290565

ISBN: (纸本)9783031290558

In this paper, a distributed algorithm is presented that localizes large number of sensors in localizable wireless sensor networks. It is well known that a network is localizable if and only if the underlying graph is globally rigid, however, even for globally rigid graphs, localization problem is proven to be NP-Hard. We develop a polynomial time distributed algorithm for localization on localizable networks based on annexation of localizable nodes using trilateration, bilateration and edge reconciliation. We study the performance of the algorithm for networks that have varying node densities, sensor radii and connectivity of the underlying graph. We assume that there are three anchor nodes available for localization. Even for networks that whose underlying globally rigid graph is sparse, we demonstrate that the algorithm performs exceptionally well by localizing large percentage of nodes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Polynomial approximation

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GIIDS: Generalized Intelligent Intrusion Detection System for Heterogeneous UAVs in UAM 27

GIIDS: Generalized Intelligent Intrusion Detection System fo...

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27th International conference on advanced Communications Technology, ICACT 2025

作者： Kabir, Fahmina Mowla, Nishat I. Doh, Inshil Division of Artificial Intelligence and Software Ewha Womans University Seoul Korea Republic of Department of Industrial Systems RISE Research Institutes of Sweden Sundsvall Sweden Department of Cyber Security Ewha Womans University Seoul Korea Republic of

ISBN: (纸本)9791188428137

Unmanned Aerial Vehicles (UAVs) are increasingly integral in various sectors, simultaneously encountering rising security threats as UAV and Urban Air Mobility (UAM) networks continue to expand. This paper addresses the challenge of securing UAM networks while also emphasizing generalizability of the security solution to protect heterogeneous UAVs against threats that compromise their stability, reliability and can cause catastrophic failures such as a crash landing. The deployment of traditional machine learning (ML) based intrusion detection systems (IDSs) is often hampered in real-world applications due to a lack of generalizability of the security solution. As a result, the system fails to provide adequate security across the varying models and platforms of UAVs, each with its unique statistical properties and data distributions. To address these challenges, we focus on employing a comprehensive set of UAV sensor parameters, tailored feature engineering and selection to develop multi-stage cross-validated ensemble learning systems to facilitate generalized detection of attack and non-attack cases. For additional analysis, we cross-validate the models using two different cross-validation techniques. The proposed stacking ensemble systems provide the overall best performance, with AUC within the range of 92% to 100% across different crossvalidations. Copyright 2025 Global IT Research Institute (GIRI). All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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ChromaSense-Empowering Health, Empowering You

ChromaSense-Empowering Health, Empowering You

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2023 IEEE Biomedical Circuits and systems conference, BioCAS 2023

作者： Durbha, Ravi Koomson, Valencia Tufts University Advanced Integrated Circuits & Systems Lab Department of Electrical & Computer Engineering MedfordMA United States

ISBN: (纸本)9798350300260

Wearable devices have transformed from novelties into indispensable companions for millions, finding applications in health and wellness, empowering individuals to proactively manage their well-being. Among these, pulse oximeters play a vital role in detecting health issues like hypoxemia. Yet, traditional oximeters struggle with accuracy in individuals with darker skin tones and lack multi-vital sign monitoring using Photoplethysmogram (PPG) signals. Addressing these challenges, we introduce ChromaSense, a Skintone Compensated Pulse Oximeter (SCPO) equipped with advanced sensors and intelligent algorithms. It aims to provide precise oxygen saturation readings for all skin tones, ensuring equitable access to quality healthcare. By addressing pulse oximetry disparities, ChromaSense seeks to enhance patient outcomes, promote inclusivity in healthcare, revolutionize medical diagnostics and treatment, and drive a patient-centered healthcare transformation. © 2023 IEEE.

关键词： Accessible healthcare Business Canvas model Chronic health patient-centric diagnosis Photoplethysmogram Pulse Oximeter Purpose Launchpad radar Tele-medicine Value Preposition

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Preserving Data Integrity and Security in IoT-Enabled Wireless sensor Networks: Employing an Intrusion Detection System Strategy 1

Preserving Data Integrity and Security in IoT-Enabled Wirele...

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1st IEEE International conference on Smart Power Control and Renewable Energy, ICSPCRE 2024

作者： Vaithiyanathan, M. Jose, Naduvathezhath Nessariose Sasireka, C.S. Mishra, Pooja James, T. Prabahar Godwin Venu, Nookala Sri Sai Ram Engineering College Department: Information Technology India Regent Strategic Solutions Rochester United States Srm Institute of Science and Technology Department Of Computer Science and Engineering India Dy Patil Institute of Engineering Management and Research Pune India Sri Sairam Institute of Technolgoy Department Of Computer Science and Engineering India Centre for IoT Madhya Pradesh Gwalior474005 India

ISBN: (纸本)9798350377002

The proliferation of IoT-enabled wireless sensor networks (WSNs) has ushered in a multitude of applications but has also heightened concerns regarding data integrity and security. This underscores the critical necessity for robust Intrusion Detection systems (IDS) tailored explicitly for such environments. This study presents an innovative IDS framework designed to safeguard the integrity and security of data within -enabled. Our IDS framework introduces advanced machine learning techniques and anomaly detection algorithms to enable real-time monitoring and analysis, effectively identifying and mitigating potential threats. Through extensive experimentation and validation, we demonstrate the reliability and efficacy of our IDS in detecting various intrusion attempts while minimizing false alarms. Moreover, our framework incorporates adaptive mechanisms to address evolving threats and network dynamics, ensuring continuous protection against malicious activities. By enhancing the resilience of IoT-enabled WSNs against intrusions, our research contributes to bolstering trust and reliability in critical applications. © 2024 IEEE.

关键词： Network intrusion

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Wearable Smart Health Monitoring Transmitter and Portable Receiver systems for Enhanced Wellness Insights 2

Wearable Smart Health Monitoring Transmitter and Portable Re...

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2nd International conference on Automation, Computing and Renewable systems, ICACRS 2023

作者： Sivaprasad, T.C. Surendhar, R. Heiner, A.J. Electronics and Communication Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9798350340235

This study presents the development and evaluation of a smart wearable belt designed for comprehensive health monitoring and fall detection. The wearable integrates advanced sensors, including vibration and heartbeat, to give users real-time insights into their well-being. The vibration sensor, meticulously calibrated for precise fall detection, exhibited high sensitivity and responsiveness, distinguishing between daily activities and potential accidents. Simultaneously, the heartbeat sensor demonstrated accurate and consistent heart rate monitoring, contributing to proactive cardiovascular health management. The seamless integration of these sensors, supported by MQTT connectivity and secure data transmission, ensures a user-friendly experience. Cloud integration enhances data processing and analytics, empowering users with a comprehensive health dashboard. Results indicate the reliability of the fall detection system and the accuracy of heart rate monitoring. This intelligent wearable belt represents a promising advancement in health technology, offering a holistic solution for users seeking real-time health insights and proactive fall prevention. Ongoing research focuses on refining algorithms and incorporating user feedback for continuous improvement and broader applications in personalizedhealth care. © 2023 IEEE.

关键词： Data analytics Patient monitoring Smart belt Wearable sensor

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GNSS/IμUWB-Based Train Integrity Monitoring Using Fuzzy Reasoning 4

GNSS/IμUWB-Based Train Integrity Monitoring Using Fuzzy Rea...

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4th IEEE International conference on Power, Electronics and Computer applications, ICPECA 2024

作者： Zhong, Tianyu Liu, Jiang Cai, Baigen Wang, Jian School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Computer Science and Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350359589

Integrity of a train is a significant characteristic parameter towards a railway train control system in order to guarantee the railway operational safety. The decoupling event between a locomotive and a carriage or two adjacent carriages has become a serious threat for the following train operating along the same track. Conventional train integrity monitoring solutions based on state detection with specific sensors, like the Global Navigation Satellite System (GNSS) receiver and tail wind pressure unit, may not perform effectively and safely under constrained or difficult operation environments. This paper presents a Train Integrity Monitoring System (TIMS) architecture with integration of GNSS, Inertial Measurement Unit (IMU) and Ultra-wide Band (UWB) ranging technique. To realize the effective determination of the train integrity state with multiple detection channels, the fuzzy reasoning theory is adopted for decision-making. By using the simulated Head-of-Train (HoT) and End-of-Train (EoT) platforms, both the normal and decoupling scenarios are investigated through experiments. With the practically collected sensor datasets, the different single-sensor-based methods are compared with the presented fuzzy reasoning-based solution. The comparison results illustrate the advanced performance level under the given experimental conditions, which indicate great potentials of the presented solution in novel train control systems. © 2024 IEEE.

关键词： fuzzy reasoning Global Navigation Satellite System (GNSS) railway transportation sensor integration train integrity monitoring Ultra-wide Band

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Risk-aware Meta-level Decision Making for Exploration Under Uncertainty 10

Risk-aware Meta-level Decision Making for Exploration Under ...

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10th International conference on Control, Decision and Information Technologies (CoDIT)

作者： Ott, Joshua Kim, Sung-Kyun Bouman, Amanda Peltzer, Oriana Sobue, Mamoru Delecki, Harrison Kochenderfer, Mykel J. Burdick, Joel Agha-mohammadi, Ali-akbar

ISBN: (纸本)9798350373981;9798350373974

Autonomous exploration of unknown environments is fundamentally a problem of decision making under uncertainty where the agent must account for uncertainty in sensor measurements, localization, action execution, as well as many other factors. For large-scale exploration applications, autonomous systems must overcome the challenges of sequentially deciding which areas of the environment are valuable to explore while safely evaluating the risks associated with obstacles and hazardous terrain. In this work, we propose a risk-aware meta-level decision making framework to balance the tradeoffs associated with local and global exploration. Meta-level decision making builds upon classical hierarchical coverage planners by switching between local and global policies with the overall objective of selecting the policy that is most likely to maximize reward in a stochastic environment. We use information about the environment history, traversability risk, and kinodynamic constraints to reason about the probability of successful policy execution to switch between local and global policies. We have validated our solution in both simulation and on a variety of large-scale real world hardware tests. Our results show that by balancing local and global exploration we are able to significantly explore large-scale environments more efficiently.

关键词： Stochastic systems

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