2022 IEEE Sensors Applications Symposium (SAS)最新文献_第4页

A parking spot occupancy sensor based on commodity wireless chipsets 一种基于商用无线芯片组的车位占用传感器

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881350

Gerrit Maus, Wiebke Gerth, D. Brückmann

{"title":"A parking spot occupancy sensor based on commodity wireless chipsets","authors":"Gerrit Maus, Wiebke Gerth, D. Brückmann","doi":"10.1109/SAS54819.2022.9881350","DOIUrl":"https://doi.org/10.1109/SAS54819.2022.9881350","url":null,"abstract":"An important prerequisite for smart parking management systems are accurate and reliable occupancy sensors for individual parking spots. Since those systems are often equipped with a wireless interface for data exchange, it is reasonable to re-use the involved wireless chipsets for sensing purposes. In this contribution, a parking spot sensor approach is discussed that solely features low-cost wireless communication devices. For this, a 2.45 GHz transmitter receiver pair is installed on the floor in the center of a parking spot. It is shown that the frequency derivative, i. e. the channel dependency, of the Received Signal Strength strongly correlates with the presence of a car on a parking spot. Based on this observation, a linear classifier approach is suggested to predict the state of an observed parking spot. An experimental evaluation of the proposed sensing approach was carried out in both a parking garage and on an open-air parking place. The achieved occupancy detection accuracy of up to 99.0 % is competitive with existing, e. g. radar based, sensing approaches, while featuring a significant cost reduction at the same time.","PeriodicalId":129732,"journal":{"name":"2022 IEEE Sensors Applications Symposium (SAS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122240023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensor Data Communication via Light Guide Body for Monitoring Vehicle Batteries 基于光导体的传感器数据通信用于车辆电池监测

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881250

F. Rittweger, P. Schiepel, Jonas Ernsting, K. Riemschneider

引用次数: 0

In-Process Tool Deflection Measurement in Incremental Sheet Metal Forming 渐进式钣金成形过程中刀具挠度测量

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881345

M. Terlau, A. Freyberg, D. Stöbener, A. Fischer

{"title":"In-Process Tool Deflection Measurement in Incremental Sheet Metal Forming","authors":"M. Terlau, A. Freyberg, D. Stöbener, A. Fischer","doi":"10.1109/SAS54819.2022.9881345","DOIUrl":"https://doi.org/10.1109/SAS54819.2022.9881345","url":null,"abstract":"Incremental sheet forming is an economical alternative to deep drawing for forming large sheets in small quantities. However, the shape deviations resulting from a process-force-caused tool deflection limits the measuring accuracy. Therefore, an optical multi-sensor system is proposed to enable the contactless in-process measurement of the tool deflection independent of the machine kinematics for the first time. The presented design study of the sensor system aims to meet the requirement of a maximal measurement uncertainty of 15 µm at a measuring distance of up to 2 m. The multi-sensor system consists of a large number of inexpensive angulation sensors, each of which measures an angle to a light source on the tool. Based on the measured angles of all sensors calibrated to each other, the position of the tool in the three-dimensional manufacturing volume can be calculated by multi-angulation. Via experimental characterization of a realized angulation sensor as well as an uncertainty propagation, the measurement uncertainty achievable with the overall system is estimated. As a result, the multi-sensor concept fulfills all requirements for the measurement of the tool deflection in incremental sheet metal forming.","PeriodicalId":129732,"journal":{"name":"2022 IEEE Sensors Applications Symposium (SAS)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134300415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Particle doped fiber based sensors for the monitoring of structures 基于粒子掺杂光纤的结构监测传感器

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881247

J. Ortega, T. Gries

引用次数: 0

Method to Improve Gait Speed Assessment for Low Frame Rate AI Enabled Visual Sensor 基于低帧率AI的视觉传感器步态速度评估改进方法

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881252

Ashi Agarwal, Bruce Wallace, R. Goubran, F. Knoefel, N. Thomas

{"title":"Method to Improve Gait Speed Assessment for Low Frame Rate AI Enabled Visual Sensor","authors":"Ashi Agarwal, Bruce Wallace, R. Goubran, F. Knoefel, N. Thomas","doi":"10.1109/SAS54819.2022.9881252","DOIUrl":"https://doi.org/10.1109/SAS54819.2022.9881252","url":null,"abstract":"The research potential of home-based autonomous health assessment has grown in recent times with the decline in caregivers for the aging population. There are several verified methods for automatic gait assessment using various kinds of sensors and cameras, however each of them comes with their own limitations. Previous gait speed assessments using an innovative privacy respecting visual sensor showed potential but were limited by the camera’s asynchronous and low frame rate. This paper extends this work with methods focused on reducing these limitations. This paper proposes a method to estimate the lost or dropped frames originally captured by the visual sensor through linear, quadratic, and cubic regression. Bisection methods are used on these regression polynomials to calculate the time taken for walking a predetermined distance, thence estimating the walking speed. The proposed method successfully regenerates the lost data back to the frame rate of 30 frames/sec whilst reducing the mean percentage error to ~6% and ~11% from ~13% for quadratic and cubic polynomials respectively indicating the quadratic provides better performance. The proposed algorithm also establishes the constancy in gait speed estimation which can be observed as a decrease in standard deviation of absolute error from 0.15 m/sec to 0.04 m/sec.","PeriodicalId":129732,"journal":{"name":"2022 IEEE Sensors Applications Symposium (SAS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124091118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Plasmonic Sensors based on 3D-printed polymer waveguides covered by a metals bilayer 基于3d打印聚合物波导的等离子体传感器，该波导被金属双层覆盖

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881343

G. Cicala, F. Arcadio, L. Zeni, L. Saitta, C. Tosto, M. Fragalá, D. D. Prete, N. Cennamo

引用次数: 1

A Lightweight Convolutional Neural Network Model for Concrete Damage Classification using Acoustic Emissions 基于声发射的混凝土损伤分类轻量级卷积神经网络模型

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881386

Yuxuan Zhang, S. Bader, B. Oelmann

引用次数: 2

Measurement setup for industrial communication techniques under electromagnetic interference 电磁干扰下工业通信技术的测量装置

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881364

Sebastian Schaffenroth, Hans-Peter Schmidt, A. Kölpin

引用次数: 0

Impact of face covering models on respiratory sound classification applications 人脸覆盖模型对呼吸声分类应用的影响

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881371

Madison Cohen-McFarlane, Fatima Hassan, Pengcheng Xi, Bruce Wallace, R. Goubran, F. Knoefel

{"title":"Impact of face covering models on respiratory sound classification applications","authors":"Madison Cohen-McFarlane, Fatima Hassan, Pengcheng Xi, Bruce Wallace, R. Goubran, F. Knoefel","doi":"10.1109/SAS54819.2022.9881371","DOIUrl":"https://doi.org/10.1109/SAS54819.2022.9881371","url":null,"abstract":"Respiratory sound evaluation and classification has the potential to provide healthcare professionals with information that would otherwise be unavailable, especially in light of the COVID-19 pandemic. With the adoption of face masks and cough covering best practices, understanding the impact of face coverings on recorded audio measurements is essential. In this paper, system identification has been applied to four face covering states (disposable mask, N95 mask, fabric mask, and elbow covering) leading to four transfer functions that can be applied pre-recorded vocal sounds. As covering a cough with a bent elbow led to the highest level of frequency attenuation, it was used to evaluate three classifiers created using the original uncovered data, the elbow covered modeled data, and a combination of both. Each classifier used YAMNet embeddings to classify between four respiratory sounds. The classifier built using the original uncovered and modeled elbow covered data led to the highest performance when evaluated on either the uncovered or modeled data, with accuracies of 0.72. The application of these models can not only evaluate the robustness of preexisting respiratory classifiers in the presence of face coverings but may also be used as a data augmentation tool for human vocal sounds.","PeriodicalId":129732,"journal":{"name":"2022 IEEE Sensors Applications Symposium (SAS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123356868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A low-cost, open-source, and distributed ocean profiling sensor node 一个低成本、开源、分布式的海洋剖面传感器节点

2022 IEEE Sensors Applications Symposium (SAS) Pub Date : 2022-08-01 DOI: 10.1109/SAS54819.2022.9881243

Andrés Rico, Suparnamaaya Prasad, Kent Larson

{"title":"A low-cost, open-source, and distributed ocean profiling sensor node","authors":"Andrés Rico, Suparnamaaya Prasad, Kent Larson","doi":"10.1109/SAS54819.2022.9881243","DOIUrl":"https://doi.org/10.1109/SAS54819.2022.9881243","url":null,"abstract":"Ocean exploration is emerging as a critical field of research for understanding and combating climate change. While coastal waters house vital marine ecosystems, such as coral reefs, they are still vastly unexplored. Sensor nodes in coastal waters can give local communities and researchers relevant data for understanding the relationship between climate change, blue-economy activities, and ecosystem degradation. We present and validate a sensor node that can be opportunistically used by non-industrial fishing boats in order to collectively source ocean profiles containing temperature, light, and acidity levels at multiple depths. We describe the complete system architecture and validate our design with deployments in three different types of water bodies. First, we validate the device’s temperature, light, and depth sensors in a submersion within a controlled pool environment. We then evaluate the software-based power cycling for intermittent data acquisition algorithms through a river deployment. Finally, we demonstrate the complete system’s functionality and possible ways to incorporate acidity sensing with an open ocean deployment. In addition to field testing, we describe and test possible architectures for adding networking capabilities through a WiFi-based system. We conclude that the device’s electrical and mechanical characteristics significantly contribute towards enabling low-cost, community-sourced data acquisition for ocean coastal water profiling.","PeriodicalId":129732,"journal":{"name":"2022 IEEE Sensors Applications Symposium (SAS)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122777006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0