2021 IEEE Sensors Applications Symposium (SAS)最新文献_第3页

Gunshot Sound Measurement and Analysis 射击声音测量与分析

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530145

Bruno Tardif, D. Lo, R. Goubran

{"title":"Gunshot Sound Measurement and Analysis","authors":"Bruno Tardif, D. Lo, R. Goubran","doi":"10.1109/SAS51076.2021.9530145","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530145","url":null,"abstract":"Exposure to gunshot sounds can cause hearing impairments. Measuring and analyzing these sounds can improve the design of hearing protectors and can help in enacting safety regulations. Furthermore, analyzing gunshot sounds can help identify the type of gun used. This is important for determining the appropriate public safety actions when a gunshot sound is detected in a public space. In this paper, we collected acoustic data from four different guns. To capture their sound including any non-symmetric sound propagation, 27 high dynamic range pressure microphones were placed around the guns forming a polar grid pattern. Audio signals were captured at 204.8 kHz sampling rate synchronously to preserve the fidelity of the impulse nature of the gunshots. In this study, an image-based analysis method was developed to take advantage of the recent advancement of image recognition techniques. Two spectral analysis methods: Short Time Fourier Transform (STFT) or Continuous Wavelet Transform (CWT), were then applied to get the spectrogram of the gunshot audio signal. Machine learning using the k-nearest neighbor and random subspaces was used to classify these spectrograms and identify which gun did the particular gunshot originated from. Under reverberant conditions, the STFT maintained a better identification accuracy than the CWT.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122007627","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

A low-power embedded system for fire monitoring and detection using a multilayer perceptron 一种使用多层感知器的低功耗嵌入式火灾监测和探测系统

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530090

Alexios Papaioannou, Panagiotis Verikios, C. Kouzinopoulos, D. Ioannidis, D. Tzovaras

引用次数: 1

A Fusion Model for Cross-Subject Stress Level Detection Based on Transfer Learning 基于迁移学习的跨学科应力水平检测融合模型

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530085

M. Mozafari, R. Goubran, J. Green

{"title":"A Fusion Model for Cross-Subject Stress Level Detection Based on Transfer Learning","authors":"M. Mozafari, R. Goubran, J. Green","doi":"10.1109/SAS51076.2021.9530085","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530085","url":null,"abstract":"Stress is a psychological condition that affects daily life, and chronic stress can result in cardiovascular disease and reduced productivity. Mental stress can be induced when difficult and time-limited tasks are assigned. Several groups have studied the relationship between physiologic signals and a subject's stress level. Through machine learning and signal processing, stress level can be automatically inferred from raw physiologic signals. As each person can have a specific physiologic reaction pattern to stress, it becomes problematic for a classifier to work well on a new subject. In this study, transfer learning is used to solve the problem of inter-subject variability. Methods are developed here to classify five levels of stress based on physiologic signals comprising photoplethysmogram (PPG), galvanic skin response (GSR), abdominal respiration, and thoracic respiration. Domain adaptation methods based on information-theoretical learning and transfer component analysis (TCA) are shown to reduce inter-subject variability of both GSR and respiratory signals. A fusion model was also designed to combine classification scores from each signal to reduce the effect of low-quality recording. The proposed method is shown to increase accuracy from 68.79% to 76.70% and Intraclass Correlation Coefficient (ICC) from 83.82% to 96.55%.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128015361","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: 2

A Non-Intrusive Ultrasonic Sensor System for Water Flow Rate Measurement 一种非侵入式超声波流量测量系统

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530165

S. Mileiko, Oktay Cetinkaya, A. Yakovlev, Domenico Balsamo

{"title":"A Non-Intrusive Ultrasonic Sensor System for Water Flow Rate Measurement","authors":"S. Mileiko, Oktay Cetinkaya, A. Yakovlev, Domenico Balsamo","doi":"10.1109/SAS51076.2021.9530165","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530165","url":null,"abstract":"Ultrasonic technologies have established themselves as optimal solutions for water flow rate measurement thanks to the high reliability and efficiency they offer. However, the existing applications often require ultrasonic sensors to be embedded in pipes, i.e., intrusive, which significantly increases initial deployment and maintenance costs. Considering the volume of employment, one to each house, the water meters have to be designed in a way that the consumers can deploy and maintain them without any skilled labourer. Hence, this paper proposes a delta time-of-flight $(Delta ToF)$ -based non-intrusive sensor system for plug-and-play ultrasonic water flow rate metering. After introducing the measurement theory and our proposed design, we experimentally evaluated the performance of three different ΔToF calculation methods in terms of memory and computation requirements through a dedicated testbed consisting of a closed-loop multi-pipe layout. The results helped us to determine the optimal $Delta ToF$ method for the employed platform, which is then used to select the best sensor and housing setting that is operable even under the worst deployment conditions (pipe material, diameter). Compared to its intrusive counterparts, the proposed system achieved a sufficient level of precision $(pm 5.7%)$ and hence provided the possibility of replacing the conventional methods of intrusive water metering at the household level.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128105638","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: 2

Method to determine the suitability of non-dispersive infrared carbon dioxide sensor models in Heating, Ventilation and Air Conditioning systems 确定非色散红外二氧化碳传感器模型在采暖、通风和空调系统中的适用性的方法

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530046

Simon Nutsch, M. Sauer

引用次数: 1

Next Generation Geophysical Assessment System 下一代地球物理评估系统

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530095

Gray D. Thurston, J. Schmalzel, B. Barrowes

引用次数: 0

A Semi-Analytical Method for Modelling of EC Probes for Detection of Thin Defects in Metals 金属薄型缺陷检测EC探针的半解析建模方法

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530168

Shourya Mukherjee, Tapabrata Sen, C. Anoop, S. Sen

引用次数: 0

Broadband Ultra-Sensitive Adiabatic Magnetometer 宽带超灵敏绝热磁强计

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530142

I. Savukov, Young Jin Kim

引用次数: 0

Quantifying the glucose concentration in urine test strip with a color-calibrated imaging system 用彩色校准成像系统定量测定尿试纸中的葡萄糖浓度

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530141

Cheng-Ru Li, Chih-Chung Yang, H. Tsai, Chun-Han Chou, Kuo-Cheng Huang, Yu-Hsuan Lin

{"title":"Quantifying the glucose concentration in urine test strip with a color-calibrated imaging system","authors":"Cheng-Ru Li, Chih-Chung Yang, H. Tsai, Chun-Han Chou, Kuo-Cheng Huang, Yu-Hsuan Lin","doi":"10.1109/SAS51076.2021.9530141","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530141","url":null,"abstract":"Urine test paper is often used to roughly judge the course of certain diseases, such as diabetes. Excessive glucose in the urine will react with the chemicals in the test strip, and then show an appropriate color to provide human observation and judgment. Generally speaking, the color of the test strip can only tell the approximate glucose concentration in urine through visual observation. Accurate quantification must rely on professional electrochemical analysis equipment. In this study, an imaging system with color correction was developed to quantify the color of urine glucose test paper. Through the composition of high color rendering lighting, darkroom barrel and color algorithm, the measurement results successfully achieved color accuracy with a color deviation of less than 3. A color distribution display method that is more suitable for human observation has been successfully established. The method of swatch contribution analysis has also been developed to numerically quantify the glucose concentration in urine. The results show that the developed system can greatly improve the resolution of urine glucose test strip. This research provides a low-cost, high-quality detection concept that can be used for home medical diagnosis and related chronic disease applications.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115867497","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

Polycrystalline silicon photovoltaic harvesting for indoor IoT systems under red- far red artificial light 用于室内物联网系统的多晶硅光伏采集，在红-远红色人造光下

2021 IEEE Sensors Applications Symposium (SAS) Pub Date : 2021-08-23 DOI: 10.1109/SAS51076.2021.9530063

M. Bruzzi, I. Cappelli, A. Fort, A. Pozzebon, M. Tani, V. Vignoli

{"title":"Polycrystalline silicon photovoltaic harvesting for indoor IoT systems under red- far red artificial light","authors":"M. Bruzzi, I. Cappelli, A. Fort, A. Pozzebon, M. Tani, V. Vignoli","doi":"10.1109/SAS51076.2021.9530063","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530063","url":null,"abstract":"This paper aims at demonstrating the feasibility of a LoRaWAN-based sensor node for temperature monitoring, autonomously powered by a polycrystalline silicon photovoltaic module with possible applications within the Internet of Things (loT) domain in the horticulture field. The commercial solar cell was characterized under two light sources: a conventional white 4000 K Light Emitting Diode (LED) and a red and far red (R:FR) lamp peaked at 655 nm and 730 nm. The sensor node is equipped with a RFM95x LoRa transceiver which proved to be a valid technology in those application scenarios where robustness and low power consumption are required. The energy harvesting features are performed by a nano-power boost charger buck converter which deals with the power extraction from the photovoltaic module, the LiPo battery charging/discharging management and the supply of the sensor node. Field tests demonstrate that under R:fr light source, the energy self-sufficiency of the system is achieved: a positive balance between the battery charge and discharge is measured, sufficient both for the node working operation and for the battery charging.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115141914","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: 6