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检索条件"任意字段=18th Conference on Embedded Networked Sensor Systems"

共 216 条记录，以下是1-10 订阅

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SenSys 2020 - Proceedings of the 2020 18th ACM conference on embedded networked sensor systems

SenSys 2020 - Proceedings of the 2020 18th ACM Conference on...

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18th ACM conference on embedded networked sensor systems, SenSys 2020

ISBN: (纸本)9781450375900

the proceedings contain 162 papers. the topics discussed include: UWHear: through-wall extraction and separation of audio vibrations using wireless signals;exploring commodity RFID for contactless sub-millimeter vibration sensing;AcuTe: acoustic thermometer empowered by a single smartphone;LeakyTrack: non-coherent single-antenna nodal and environmental mobility tracking with a leaky-wave antenna;combating interference for long range LoRa sensing;symphony: localizing multiple acoustic sources with a single microphone array;EarphoneTrack: involving earphones into the ecosystem of acoustic motion tracking;milliEgo: single-chip mmWave radar aided egomotion estimation via deep sensor fusion;FM-track: pushing the limits of contactless multi-target tracking using acoustic signals;and zero-wire: a deterministic and low-latency wireless bus through symbol-synchronous transmission of optical signals.

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NanoCoCoA 2020 - Proceedings of the 1st ACM International Workshop on Nanoscale Computing, Communication, and Applications, Part of the 18th ACM conference on embedded networked sensor systems, SenSys 2020

NanoCoCoA 2020 - Proceedings of the 1st ACM International Wo...

引用

1st ACM International Workshop on Nanoscale Computing, Communication, and Applications, NanoCoCoA 2020, held in conjunction with the 18th ACM conference on embedded networked sensor systems, SenSys 2020

ISBN: (纸本)9781450381161

the proceedings contain 8 papers. the topics discussed include: on the feasibility of flow-guided nanocommunication networks for some medical applications;a molecular communication scheme to estimate the state of biochemical processes on a lab-on-a-chip;hydrogel-based bio-nanomachine transmitters for bacterial molecular communications;toward dynamically adapting wireless intra-chip channels to traffic needs with a programmable metasurface;a cube-tree hybrid NoC topology with 3D mirroring technique for load balancing;secrecy capacity of diffusive molecular communication under biological spherical environment;metasurface sensing platforms for medical diagnostics;and work in progress: intelligent metasurface holograms.

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Distributed Resilient Estimator for networked systems under Deception Attacks 18

Distributed Resilient Estimator for Networked Systems under ...

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18th International conference on Control Automation Robotics and Vision

作者： Zhan, Weiwei Miao, Zhiqiang Hu, Yang Chen, Yizong Chen, Yanjie Wang, Yaonan Hunan Univ Coll Elect & Informat Engn Changsha 410082 Peoples R China Natl Engn Res Ctr Robot Visual Percept & Control Changsha 410082 Peoples R China Fuzhou Univ Sch Mech Engn & Automat Changsha 410082 Peoples R China

ISBN: (纸本)9798331518509;9798331518493

Deception attacks are employed to compromise cyber-physical systems through fake data injection. this paper concentrates on the distributed resilient estimation issue of multi-sensor networked systems under deception attacks. In order to detect deception attacks, we utilize Kullback-Leibler(K-L) divergence as a criterion to distinguish the discrepancy between the deceived information and the estimated information. When the attack does not exist, the transmitted information can be restored to ensure the resilient estimation performance. Based on the extended Kalman filter design method, a distributed resilient estimation with a dual-gain mechanism is developed. this advanced approach dynamically adjusts the weighting balance between the predictive model and sensor data inputs, achieving the optimal estimation during the shutdown and activation of spoofing attacks. Finally, numerical simulations are provided to further illustrate the results.

关键词： Extended Kalman filters

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Anomaly Detection and Functional Testing for Automotive CAN Communication 18

Anomaly Detection and Functional Testing for Automotive CAN ...

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18th Annual IEEE International systems conference (SysCon)

作者： Al Maruf, Md Azim, Akramul Ontario Tech Univ Dept Elect Comp & Software Engn Oshawa ON Canada

ISBN: (纸本)9798350358810;9798350358803

Integrated vehicle dynamics control systems require real-time communication among their components to improve performance and process efficiency. this communication relies on the use of sensor data, hardware interfaces, transmission protocols, and control strategies, which all have an impact on the system's reliability. However, as the number of functionalized electronic control units (ECUs) and wiring systems increases, advanced control systems encounter complex functional and cybersecurity issues. To mitigate this complexity, the automotive industry widely employs the Controller Area Network (CAN) communication bus. Nevertheless, the inherent vulnerabilities of CAN and the rich interfaces with external environments increase the systems' susceptibility to soft errors caused by uncertainty factors such as process changes. therefore, detecting abnormalities in automotive CAN communication is crucial. this paper introduces a machine learning (ML)-based anomaly detection framework to identify anomalies through CAN messages, extracting key features and employing ML models for predictive analysis. It also uses Triple Modular Redundancy (TMR) for trusted ML computation in anomaly detection. the study provides a comparative analysis of various ML algorithms, highlighting the effectiveness of Deep Neural Networks in identifying anomalies within both synthetic and real Hyundai CAN data for a wheel speed control system, showcasing the framework's capability to enhance system reliability and security.

关键词： CAN Communication Anomaly Detection embedded systems

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Adaptive Multi-Core Real-Time Scheduling Based on Reinforcement Learning 18

Adaptive Multi-Core Real-Time Scheduling Based on Reinforcem...

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IEEE 18th International conference on Control and Automation (ICCA)

作者： Liang, Yonghui Li, Hui Shen, Fei Xu, Qimin Hua, Shuna Zhu, Shanying Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Engn Res Ctr Intelligent Control & Manag Shanghai 200240 Peoples R China Chinese Acad Sci Shanghai Inst Microsyst & Informat Technol Key Lab Wireless Sensor Network & Commun Shanghai 200050 Peoples R China North Informat Control Res Acad Grp Co Ltd Nanjing 211153 Peoples R China

ISBN: (纸本)9798350354416;9798350354409

With the transformation towards industrial intelligence, multi-core processors are increasingly being applied in real-time networked control systems to ensure secure execution of sensing, computing and actuating tasks under time constraints. However, existing scheduling methods result in either low CPU utilization or many missed task deadlines in dynamic systems. In this paper, we propose a two-layer scheduling architecture to address this issue by fully exploring the complex dependency between real-time tasks. To be specific, the local layer determines task execution priorities considering both dependency between tasks and deadline constraints by utilizing a reinforcement learning approach. Moreover, to better utilize the parallel capabilities of multi-core processors and reduce temporal collisions, this paper minimizes the requested core count for the task set based on a greedy strategy. the global layer designs a scheduling algorithm based on the preempt method and provides schedulability analysis of multiple task sets. Experimental results validate the correctness of the proposed scheduling approach, and efficiency is demonstrated through comparisons with baseline method.

关键词： networked control systems

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Mobile robot perception system in ROS 2 on embedded computing platforms 18

Mobile robot perception system in ROS 2 on embedded computin...

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18th IFAC conference on Programmable Devices and embedded systems (PDES)

作者： Zemcik, Tomas Kratochvila, Lukas Brno Univ Technol Brno Czech Republic

In this paper a perception system of a mobile robot is proposed and implemented combining a LiDAR sensor with a colour camera. Localisation of unknown objects in an a priori known environment and their classification is required in order for the robot to safely and reliably navigate the working area. To this end, a pipeline is proposed to process and fuse the LiDAR 3D point-cloud data with a monocular colour camera image classifications yielding precisely localised 3D detections with class designations. the proposed pipeline is designed to run on limited computational power embedded platforms in the ROS 2 environment, and has been tested on a robotic testbench. Copyright (c) 2024 the Authors. this is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Mobile robot known environment ROS 2 sensor fusion object detection 3D object localisation

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An Amalgamation of Machine Learning and embedded systems for Smart Street Lightning systems 18

An Amalgamation of Machine Learning and Embedded Systems for...

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18th INDIAcom;11th International conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Gupta, Sakshi Singh, Rishit Parikh, Jolly Puri, Yugnanda Vashisht, Ridham Bharati Vidyapeeth's College of Engineering Department of Electronics and Communication Engineering New Delhi110063 India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering New Delhi110063 India

ISBN: (纸本)9789380544519

this research paper introduces an innovative Smart Street Light System that optimizes street lighting operations by harnessing ambient light levels to govern the activation and deactivation of streetlights. Lux value thresholds are employed to distinguish between various lighting scenarios, ranging from bright sunlight to subdued sunlight and complete darkness. Moreover, the paper explores the potential integration of an ultrasonic sensor (US 100) for detecting approaching vehicles and pedestrians, by using advanced machine learning algorithms, thereby enhancing system capabilities. the novel use of Machine Learning algorithms, extensive training of the model, on dataset built using real world conditions, enhances the output accuracy of the model, which gives the model the capabilities to take decisions on its own and thus create a self-sustainable ecosystem, harnessing advanced technologies, without any human involvement. the model was created and implemented with an accuracy of 97.35 percent. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Ambient Light Sensing BH1750 Energy Efficiency Lux Machine Learning Nucleo-F401 RE Smart Street Light System Ultrasonic sensor Urban Sustainability US -100

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18th IFAC conference on Programmable Devices and embedded systems, PDES 2024 - Proceedings

18th IFAC Conference on Programmable Devices and Embedded Sy...

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18th IFAC conference on Programmable Devices and embedded systems, PDES 2024

the proceedings contain 54 papers. the topics discussed include: fault detection algorithm for pneumatic measuring and sorting station;design and analyses of tendon-driven continuum robots for minimally invasive surgery;a method of tactile resistive sensor array calibration;computer vision approaches for automated bee counting application;open source embedded system approach for decreasing carbon footprint of Oldtimers;practice-oriented controller design of a simple nonlinear system;laboratory tester for relay contacts lifespan;a data-driven approach to reliability and fault analysis in industrial maintenance;comparison of split computing scenarios for object detection;the influence of recursive filtering methods on Bluetooth-based localization;event driven phase-locked loop with application to atomic force microscopy oscillation non-resonant modes;road pavement monitoring and analysis approaches using gyroscope and accelerometer data;a comparison of methods recovering signals from non-uniform samples;and experimental kit and digital model to support an agile design process of an industrial multihead weigher.

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A Novel Force Sensing Biopsy Needle for MR-Compatible Robotic Biopsy System: Performance Evaluation 1

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18th International conference on Intelligent Autonomous systems (IAS)

作者： Liu, Rongrong Ko, Seong Young Chonnam Natl Univ Mech Engn Gwangju South Korea

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

A force-sensing biopsy needle embedded with Fiber Bragg Grating (FBG) sensors is proposed to be used in cancer diagnosis. the FBG sensor is a fiber optic sensor, and the biopsy needle is made of nitinol, both of which can be used in MRI-guided biopsy to provide force feedback to surgeons. the axial force resolution of the biopsy needle is as high as 8.4 mN/pm, and its repeatability was measured to be 19 mN. the dynamic force measurement performance of the needle was verified by animal meat insertion experiment.

关键词： Force measurement FBG sensor MRI guidance Biopsy needle

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Aggressive Trajectory Tracking for Nano Quadrotors Using embedded Nonlinear Model Predictive Control 1

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18th International conference on Intelligent Autonomous systems (IAS)

作者： Kazim, Muhammad Sim, Hyunjae Shin, Gihun Hwang, Hwancheol Kim, Kwang-Ki K. Inha Univ Dept Elect & Comp Engn Incheon South Korea

ISBN: (数字)9783031448515

ISBN: (纸本)9783031448508;9783031448515

this paper presents an aggressive trajectory tracking method for a small lightweight nano-quadrotor using nonlinear model predictive control (NMPC) based on acados. Controlling a nano quadrotor for accurate trajectory tracking at high speed in dynamic environments is challenging due to complex aerodynamic forces that introduce significant disturbances and large positional tracking errors. these aerodynamic effects are difficult to be identified and require feedback control that compensates for them in real time. NMPC allows the nano-quadrotor to control its motion in real time based on onboard sensor measurements, making it well-suited for tasks such as aggressive maneuvers and navigation in complex and dynamic environments. the software package acadosenables the implementation of the NMPC algorithm on embedded systems, which is particularly important for nano-quadrotor due to its limited computational resources. Our autonomous navigation system is developed based on an AI-deck that is a GAP8-based parallel ultra-low power computing platform with onboard sensors of a multi-ranger deck and a flow deck. the proposed method of NMPC-based trajectory tracking control is tested in simulation and the results demonstrate its effectiveness in trajectory tracking while considering the dynamic environments. It is also tested on a real nano quadrotor hardware, 27-g Crazyflie 2.1, with a customized MCU running embedded NMPC, in which accurate trajectory tracking results are achieved in dynamic real-world environments.

关键词： Optimal tracking control Nonlinear model predictive control acados Crazyflie2.1 AI-deck

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