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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31-40 订阅

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An Effective Method for Data Processing of Inertial Measurement Units Applied to embedded systems 18

An Effective Method for Data Processing of Inertial Measurem...

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18th International conference on Informatics in Control, Automation and Robotics (ICINCO)

作者： Kolhoff, Christoph Kemper, Markus UAS Diepholz PHWT ZME Inst Thuringer Str 3a Diepholz Germany

ISBN: (纸本)9789897585227

Autonomous functions for navigation and localization have piqued the attention and interest in many fields of science and engineering as automotive, aviation and robotics. Desiring high quantity of autonomous products, the used components are requested to be cheap. this often lead engineers or developers to apply micro-electromechanical systems that exhibit large errors. To use these sensors anyway, the acquired data must be processed online for error reduction. Hence there is a need for an algorithm that is easy to compute. the aim of this research is to develop a generic algorithm based on a Gauss-Markov process representing the drifting bias that can be parametrized easily and performs well on real-time systems. therefore, the error model imitates the sensor's output and removing the errors afterwards. Finally, a validation of the suggested algorithm is performed by comparing processed data of the micro-controller to data processed a posteriori on a high-performance computer.

关键词： Bias Error Gauss-Markov Process MEMS Error Model

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Improving cyber-physical system performance through actuator-sensor interactions: PhD forum abstract 20

Improving cyber-physical system performance through actuator...

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

作者： Bannis, Adeola Carnegie Mellon University Moffett FieldCA United States

ISBN: (纸本)9781450375900

Cyber-physical systems are used both for sensing the environment around them as well as making changes to that environment (actuation). Interactions between actuators and sensors can create interference or uncertainty, but can also be leveraged to improve the sensing coverage, sensing resolution or capability of a cyber-physical system. the challenge in modifying actuator behavior in a system is to avoid degrading the actuation range or responsiveness. the acceptable range of actuator adaptation can be modelled and tested using physics-based, data-driven, or combination approaches. © 2020 Owner/Author.

关键词： Cyber Physical System

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CREAtIve: Reconfigurable embedded artificial intelligence 21

CREAtIve: Reconfigurable embedded artificial intelligence

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18th ACM International conference on Computing Frontiers 2021, CF 2021

作者： Bahrebar, Poona Denis, Leon Bonnaerens, Maxim Coddens, Kristof Dambre, Joni Favoreel, Wouter Khvastunov, Illia Munteanu, Adrian Nguyen-Duc, Hung Schulte, Stefan Stroobandt, Dirk Valvekens, Ramses Van Den Broeck, Nick Verbruggen, Geert Ghent University Ghent Belgium Etro Vrije Universiteit Brussel Brussels Belgium Ghent University Imec-IDLab Ghent Belgium Melexis Ieper Belgium Flir Systems Trading Meer Belgium XenomatiX Leuven Belgium Easics Leuven Belgium

ISBN: (纸本)9781450384049

cREAtIve targets the development of novel highly-adaptable embedded deep learning solutions for automotive and traffic monitoring applications, including position sensor processing, scene interpretation based on LiDAR, and object detection and classification in thermal images for traffic camera systems. these applications share the need for deep learning solutions tailored for deployment on embedded devices with limited resources and featuring high adaptability and robustness to changing environmental conditions. cREAtIve develops knowledge, tools and methods that enable hardware-efficient, adaptable, and robust deep learning. © 2021 ACM.

关键词： Object detection

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A toolkit for spatial interpolation and sensor placement: Poster abstract 20

A toolkit for spatial interpolation and sensor placement: Po...

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

作者： Narayanan, S Deepak Patel, Zeel B Agnihotri, Apoorv Batra, Nipun Iit Gandhinagar India

ISBN: (纸本)9781450375900

Sensing is central to the SenSys and related communities. However, fine-grained spatial sensing remains a challenge despite recent advancements, owing to cost, maintenance, among other factors. thus, estimating the sensed phenomenon at unmonitored locations and strategically installing sensors is of prime importance. In this work, we introduce Polire - an open-source tool that provides a suite of algorithms for spatial interpolation and near-field passive sensor placements. We replicate two existing papers on these two tasks to show the efficacy of Polire. We believe that Polire is an essential step towards lowering entry barriers towards sensing and scientific reproducibility. © 2020 ACM.

关键词： embedded systems

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Enhanced heart rate estimation based on face features 18

Enhanced heart rate estimation based on face features

引用

18th International Multi-conference on systems, Signals & Devices (SSD)

作者： Ben Ayed, Mossaad Alshaya, Shaya A. Alshammari, Adil Sfax Univ Embedded Syst Lab Sfax 3029 Tunisia Majmaah Univ Coll Sci & Humanities AlGhat Dept Comp Sci Majmaah 11952 Saudi Arabia

ISBN: (纸本)9781665414937

Health care systems have become essential parts of today's societies. However, the COVID-19 virus pandemic has highlighted the challenges that health care systems face. this need has encouraged scientists to improve these systems by supporting the Internet of things (IoT) architectures and providing more contactless sensors. Still, traditional equipment based on using a contact sensor to measure vital signs, such as the heart rate, faces problems with accuracy and can have psychological effects on patients. the proposed solution aims to monitor the heart rate through non-contact measurement using a smart camera. this objective was achieved by applying an intelligent algorithm to a facial video sequence. this paper attempts to estimate the heart rate based on the color variation of the forehead skin. Specifically, the proposed method aimed to accurately estimate the heart rate in the standard condition and in the case of darker skin where the variation of the skin color was only slightly changed. the results proved that the estimation's accuracy could reach 98%.

关键词： Heart rate Video processing Contactless Artificial intelligence facefeatures Raspberry

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Temperature prediction based on ANN linear regression with an LWIR sensor for the study of diabetic foot 18

Temperature prediction based on ANN linear regression with a...

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18th International conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

作者： Bayareh Mancilla, Rafael Daul, Christian Gutierrez Martinez, Josefina Leija Salas, Lorenzo Wolf, Didier Vera Hernandez, Arturo CINVESTAV IPN Dept Elect Engn Bioelect Mexico City DF Mexico Univ Lorraine CRAN BioSiS Nancy France Univ Lorraine CRAN BioSiS CNRS Nancy France INR LGII Direct Technol Res Med Engn Res Div Mexico City DF Mexico Univ Lorraine CNRS CRAN Nancy France

ISBN: (纸本)9781665400299

this work presents an improvement to a linear model obtained by Bayareh et al. in 2017, by training a single layer Perceptronand optimized by Gradient Descent. the objective of characterizing an IR radiometric sensor with a mathematical model is to predict the surface temperature of the body under study (e.g. diabetic foot) to perform quantitative thermography studies related to early detection through temperature difference. the data was obtained by measuring IR radiometric information on a phantom under a controlled environment. Subsequently, the predicted model was compared to the first characteristic equation. the model had an error of 0.14 degrees C while the original model had an error of 1.28 degrees C regard an industrial purpose camera, previously calibrated.. the updated model could support the study of quantitative thermography with embedded systems whose sensors are not able to interpret temperature from factory settings, especially in studies focused on the difference of temperatures that support the diagnosis from the quantitative point of view.

关键词： IR medical thermography Artificial Neural Network Diabetic foot

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Localization from activity sensor data: Poster abstract 20

Localization from activity sensor data: Poster abstract

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

作者： Papst, Franz Stricker, Naomi Saukh, Olga Institute of Technical Informatics Tu Graz Csh Vienna Austria Eth Zürich Switzerland

ISBN: (纸本)9781450375900

In this work, we show that sensor data may leak a sensor's location even if the latter is not explicitly included in the data set. the sensors are localized by linking sensor data, in particular activity data, with publicly available environmental data such as weather data. We show that using a linkage attack a cow can be localized within an entire country with an average accuracy of up to 32.6 km solely from activity traces recorded with a tracker in the cow's stomach. © 2020 ACM.

关键词： location privacy sensor data localization

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A sensor-based application for road conditions detection: Poster abstract 20

A sensor-based application for road conditions detection: Po...

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

作者： Sitanayah, Lanny Angdresey, Apriandy Kristalino, Evander Dept. of Informatics Engineering Universitas Katolik de la Salle Manado Indonesia

ISBN: (纸本)9781450375900

Road conditions affect the safety of road users as potholes may cause traffic accidents. We design and implement a sensor-based application for road conditions detection. the sensor device includes a GPS NEO-6M module to get the pothole locations and an MPU-92/65 module as accelerometer and gyroscope sensor, which are attached to a NodeMCU ESP8266. We use REST API as the web service to connect the sensor device and users, who will access the information using the Android application on their smartphones. To cluster the acquired data, we use the k-means clustering algorithm. the algorithm clusters data into deep, medium and shallow potholes. © 2020 ACM.

关键词： Roads and streets

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Real-time reassurance monitoring shopping basket in retail store: Poster abstract 20

Real-time reassurance monitoring shopping basket in retail s...

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

作者： Yamazaki, Azusa Akatsu, Ryo Okada, Yukihiko Zempo, Keiichi University of Tsukuba Tsukuba Japan

ISBN: (纸本)9781450375900

In this study, we propose a sensor network to estimate service reassurance in a store by estimating customer stress level based on a pulse wave. We developed a basket that can calculate an RR interval (RRI) with sufficient accuracy to estimate customer reassurance from the measured pulse wave under in-store conditions. Two processes were applied to the measurement values based on the assumption that certain circumstances may interfere with measuring pulse waves. Furthermore, the authors conducted pulse wave measurement experiments under simulated store conditions. the results showed RRIs' values with an error rate of 4.9% compared to the true value. © 2020 ACM.

关键词： sensor networks

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

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

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International conference on Control and Automation (ICCA)

作者： Yonghui Liang Hui Li Fei Shen Qimin Xu Shuna Hua Shanying Zhu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Re-search Center of Intelligent Control and Management Shanghai China Key Laboratory of Wireless Sensor Network and Communications Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China North Information Control Research Academy Group Company Ltd. Nanjing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

With the transformation towards industrial intel-ligence, multi-core processors are increasingly being applied in real-time networked control systems to ensure secure exe-cution 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 pre-empt 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： Job shop scheduling Multicore processing Scheduling algorithms networked control systems Reinforcement learning Real-time systems sensors

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