Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530192
G. Gruber, M. Neumayer, T. Bretterklieber, H. Wegleiter
For small engines in non-automotive powertrains the emissions share is already limited. The introduction and integration of ECU -systems for engine control and dedicated sensors in small engines are required. The ion current sensing technology could be a key enabler for next generation combustion diagnoses and maintenance of small engines. It is an add-on sensing system and aims on gaining knowledge about the combustion process from the ion current signal. In this paper we present an analysis of an ion current sensing system from a metrological point of view. We investigate the impact of the ignition system and the ion current sensing system on the ion current signal and calculate a measurement error. We present a potential parameter to characterize the combustion process independently of the instrumentation. The analysis represents a first approach on how to design robust ion current based ECU control systems.
{"title":"Metrological Analysis of an Ion Current Measurement System","authors":"G. Gruber, M. Neumayer, T. Bretterklieber, H. Wegleiter","doi":"10.1109/SAS51076.2021.9530192","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530192","url":null,"abstract":"For small engines in non-automotive powertrains the emissions share is already limited. The introduction and integration of ECU -systems for engine control and dedicated sensors in small engines are required. The ion current sensing technology could be a key enabler for next generation combustion diagnoses and maintenance of small engines. It is an add-on sensing system and aims on gaining knowledge about the combustion process from the ion current signal. In this paper we present an analysis of an ion current sensing system from a metrological point of view. We investigate the impact of the ignition system and the ion current sensing system on the ion current signal and calculate a measurement error. We present a potential parameter to characterize the combustion process independently of the instrumentation. The analysis represents a first approach on how to design robust ion current based ECU control systems.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"2 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":"132920040","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530040
Chih-Chung Yang, Yu-Ting Li, D. Chiang, P. Chiu, Yi-Cheng Lin, W. Hsiao
The oil quality after the long heating time is required to be examined frequently because the degradation of oils can be detrimental to human health. Several sensing methods have addressed oil degradation problems but currently there is no known techniques to solve the problem in both efficient and economical ways. Three sensing methods, i.e. an interdigital planar sensor integrated with a LCR meter, spectrophotometer method and tested sensing paper, are proposed to characterize the quality of two kinds of edible oils. It is found that the logarithm of impedance of oils is linearly related to the logarithm of measured frequency, implying that the oils are dielectric materials. The impedances of oils decrease linearly with the increase of heated duration and the capacitance ratio of oils is weakly dependent on the heating duration. The wavelengths of starting transmittance are significantly red-shifted as observed by a spectrophotometer when the oils are heated for a long time. The absorbance of the oils increases exponentially with the heating time. The tested paper indicates that the color change can exhibit a quick oil qualitative measurement within a few minutes, but lacks quantitative information. Each sensing method has different sampling time, precision and accuracy for measuring the oil degradation, and the sensing methods should be chosen according to the required needs.
{"title":"Comparison of Sensing Methods for Characterization of Heated Oils Degradation","authors":"Chih-Chung Yang, Yu-Ting Li, D. Chiang, P. Chiu, Yi-Cheng Lin, W. Hsiao","doi":"10.1109/SAS51076.2021.9530040","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530040","url":null,"abstract":"The oil quality after the long heating time is required to be examined frequently because the degradation of oils can be detrimental to human health. Several sensing methods have addressed oil degradation problems but currently there is no known techniques to solve the problem in both efficient and economical ways. Three sensing methods, i.e. an interdigital planar sensor integrated with a LCR meter, spectrophotometer method and tested sensing paper, are proposed to characterize the quality of two kinds of edible oils. It is found that the logarithm of impedance of oils is linearly related to the logarithm of measured frequency, implying that the oils are dielectric materials. The impedances of oils decrease linearly with the increase of heated duration and the capacitance ratio of oils is weakly dependent on the heating duration. The wavelengths of starting transmittance are significantly red-shifted as observed by a spectrophotometer when the oils are heated for a long time. The absorbance of the oils increases exponentially with the heating time. The tested paper indicates that the color change can exhibit a quick oil qualitative measurement within a few minutes, but lacks quantitative information. Each sensing method has different sampling time, precision and accuracy for measuring the oil degradation, and the sensing methods should be chosen according to the required needs.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"46 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":"115581415","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530113
Bruce Wallace, S. Gagnon, A. Stinchcombe, Stephanie Yamin, R. Goubran, F. Knoefel
Aging related changes and pathology affecting cognition and the ability to drive are significant issues for individuals, their families and the general population. Ensuring that unsafe drivers have their license suspended or get the additional training they need is important for the safety of the general population. On the other hand, allowing a person to continue to drive as long as they are safe is important for the social, emotional and cognitive wellbeing of the individual. This paper presents results of a preliminary study to see if an automated assessment based on trained machine learning models can correctly classify simulator drives as safe or unsafe in comparison to expert driver assessment opinion. The results show that the machine learning is able to achieve 85% accuracy in comparison to the experts for a combined group of 47 drivers that included 20 Healthy Controls, 9 diagnosed with Lewy Body Dementia and 18 diagnosed with mild Dementia of Alzheimer's Type. This work shows the potential for automated driver simulation assessment, which could reduce the burden on clinicians regarding driver safety evaluation.
{"title":"Preliminary Results for the Automated Assessment of Driving Simulation Results for Drivers with Cognitive Decline","authors":"Bruce Wallace, S. Gagnon, A. Stinchcombe, Stephanie Yamin, R. Goubran, F. Knoefel","doi":"10.1109/SAS51076.2021.9530113","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530113","url":null,"abstract":"Aging related changes and pathology affecting cognition and the ability to drive are significant issues for individuals, their families and the general population. Ensuring that unsafe drivers have their license suspended or get the additional training they need is important for the safety of the general population. On the other hand, allowing a person to continue to drive as long as they are safe is important for the social, emotional and cognitive wellbeing of the individual. This paper presents results of a preliminary study to see if an automated assessment based on trained machine learning models can correctly classify simulator drives as safe or unsafe in comparison to expert driver assessment opinion. The results show that the machine learning is able to achieve 85% accuracy in comparison to the experts for a combined group of 47 drivers that included 20 Healthy Controls, 9 diagnosed with Lewy Body Dementia and 18 diagnosed with mild Dementia of Alzheimer's Type. This work shows the potential for automated driver simulation assessment, which could reduce the burden on clinicians regarding driver safety evaluation.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"74 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":"129476874","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530132
C. Liu, Jiang Liu, S. Shimamoto
The sign language recognition system plays an important role in the field of human-computer interaction. In the daily life of hearing-impaired people, sign language is used as the main tool to communicate with the world. Although sign language can satisfy simple conversation, it is difficult to deal with in some situations where a lot of conversation is required such as medical emergencies or educational consultation. This paper proposes a sign language recognition system based on Wi-Fi to improve the life of the disabled. The proposed system collects the Channel State Information (CSI) due to the change of hand movement. Through the analysis of all subcarriers, the amplitude of CSI is determined to reflect the characteristics of different sign languages, some high-frequency noise is removed in the amplitude of CSI to obtain a smoother signal Gesture feature. We propose a gesture feature extraction method based on the variance of time series and DTW algorithm is used to recognize nine common Japanese sign language gestures. We set two daily conditions to test the system, and the experimental results show that the system performs well in different conditions.
{"title":"Sign Language Estimation Scheme Employing Wi-Fi Signal","authors":"C. Liu, Jiang Liu, S. Shimamoto","doi":"10.1109/SAS51076.2021.9530132","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530132","url":null,"abstract":"The sign language recognition system plays an important role in the field of human-computer interaction. In the daily life of hearing-impaired people, sign language is used as the main tool to communicate with the world. Although sign language can satisfy simple conversation, it is difficult to deal with in some situations where a lot of conversation is required such as medical emergencies or educational consultation. This paper proposes a sign language recognition system based on Wi-Fi to improve the life of the disabled. The proposed system collects the Channel State Information (CSI) due to the change of hand movement. Through the analysis of all subcarriers, the amplitude of CSI is determined to reflect the characteristics of different sign languages, some high-frequency noise is removed in the amplitude of CSI to obtain a smoother signal Gesture feature. We propose a gesture feature extraction method based on the variance of time series and DTW algorithm is used to recognize nine common Japanese sign language gestures. We set two daily conditions to test the system, and the experimental results show that the system performs well in different conditions.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"3 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":"128660666","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530158
Hari Krishna Salila Vijayalal Mohan, A. Malcolm
In a high-volume food and beverage production environment, non-destructive and real-time inspection of various stages of food production from raw content processing to product packaging at high speed is a challenge. Specifically, filling and dispensing, packaging, and sealing lines encounter issues such as powder caking, non-homogenous powder composition, misaligned caps, and leaks during package sealing, which are currently addressed using human inspection and/or destructive, expensive and offline screening methodologies. In this work, a non-destructive evaluation platform using a capacitive proximity sensor was proposed and demonstrated to showcase novel applications such as monitoring powder caking, non-invasive powder composition analysis, contactless capping closure integrity testing and non-contact leak detection in sachet seals with high throughput, in-line integration capability and a small system footprint.
{"title":"Non-Destructive Evaluation of Food and Beverage (F&B) Fast Moving Consumer Goods (FMCG) Using Capacitive Proximity Sensor","authors":"Hari Krishna Salila Vijayalal Mohan, A. Malcolm","doi":"10.1109/SAS51076.2021.9530158","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530158","url":null,"abstract":"In a high-volume food and beverage production environment, non-destructive and real-time inspection of various stages of food production from raw content processing to product packaging at high speed is a challenge. Specifically, filling and dispensing, packaging, and sealing lines encounter issues such as powder caking, non-homogenous powder composition, misaligned caps, and leaks during package sealing, which are currently addressed using human inspection and/or destructive, expensive and offline screening methodologies. In this work, a non-destructive evaluation platform using a capacitive proximity sensor was proposed and demonstrated to showcase novel applications such as monitoring powder caking, non-invasive powder composition analysis, contactless capping closure integrity testing and non-contact leak detection in sachet seals with high throughput, in-line integration capability and a small system footprint.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"63 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":"122306709","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530102
Vivek Bharati
Autonomy of the blind and visually impaired can be achieved through technological means and thereby empowering them with a sense of independence. Mobile phones are ubiquitous and can access artificial intelligence capabilities locally and in the Cloud. Navigational sensors, such as Light Detection and Ranging (LiDAR), and wide angle cameras, typically found in self-driving cars, are beginning to be incorporated into mobile phones. In this paper, we propose techniques for using mobile phone LiDAR + camera sensor data fusion along with edge + Cloud split AI to create an indoor situational awareness and navigational aid for the visually impaired. In addition to physical sensors, the system uses AI models as virtual sensors to provide the required functionality. The system enhances the image of a scene captured by a camera using distance information from the LiDAR and directional information computed by the device to provide a rich 3-D description of the space in front of the user. The system also uses a combination of sensor data fusion and geometric formulas to provide step-by-step walking instructions for the user in order to reach destinations. The user-centric system proposed here can be a valuable assistive technology for the blind and visually imnpired.
{"title":"LiDAR + Camera Sensor Data Fusion On Mobiles With AI-based Virtual Sensors To Provide Situational Awareness For The Visually Impaired","authors":"Vivek Bharati","doi":"10.1109/SAS51076.2021.9530102","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530102","url":null,"abstract":"Autonomy of the blind and visually impaired can be achieved through technological means and thereby empowering them with a sense of independence. Mobile phones are ubiquitous and can access artificial intelligence capabilities locally and in the Cloud. Navigational sensors, such as Light Detection and Ranging (LiDAR), and wide angle cameras, typically found in self-driving cars, are beginning to be incorporated into mobile phones. In this paper, we propose techniques for using mobile phone LiDAR + camera sensor data fusion along with edge + Cloud split AI to create an indoor situational awareness and navigational aid for the visually impaired. In addition to physical sensors, the system uses AI models as virtual sensors to provide the required functionality. The system enhances the image of a scene captured by a camera using distance information from the LiDAR and directional information computed by the device to provide a rich 3-D description of the space in front of the user. The system also uses a combination of sensor data fusion and geometric formulas to provide step-by-step walking instructions for the user in order to reach destinations. The user-centric system proposed here can be a valuable assistive technology for the blind and visually imnpired.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"26 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":"122479360","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530079
D. Spirjakin, A. Baranov, S. Akbari, C. T. Phong, N. N. Tuan
Catalytic gas sensors are among the most widespread gas sensors for combustible gas concentration measurements. However, their selectivity is low. In this research, the results of machine learning techniques application to enhance catalytic gas sensor selectivity are presented. The measurements of sensor signal are performed using the multistage heat pulse method described in our previous works. Contrary to the previous works, the number of heating stages was increased from 2 to 55, which corresponds to the heating voltage range of 125 m V to 1.5 V with a 25 m V step. This change enriches sensor signal with information about gas compositions. Methane and vapors of acetone, ethanol and gasoline are used as target gases. A support vector machine method is used to train two models. The first one was trained based on the plain normalized data. It was used for a microcontroller implementation of the method. The second model used the data transformed by principal component analysis technique. This model was used to visualize the method proposed. The results show that the application of proposed method allows to identify gases by single catalytic sensor. These principles can be used to design selective gas detectors which will react only to target gases.
催化气体传感器是可燃气体浓度测量中应用最广泛的气体传感器之一。然而，它们的选择性很低。在本研究中，介绍了机器学习技术在提高催化气体传感器选择性方面的应用结果。传感器信号的测量使用了我们之前工作中描述的多级热脉冲法。与之前的工作相反，加热阶段的数量从2个增加到55个，对应于加热电压范围为125 m V至1.5 V，步长为25 m V。这种变化丰富了传感器信号中的气体成分信息。甲烷和丙酮、乙醇和汽油的蒸气被用作目标气体。采用支持向量机方法对两个模型进行训练。第一个是基于普通归一化数据进行训练的。它是用单片机实现的一种方法。第二个模型使用主成分分析技术转换后的数据。该模型用于可视化所提出的方法。结果表明，该方法的应用可以实现单催化传感器对气体的识别。这些原理可用于设计只对目标气体起反应的选择性气体探测器。
{"title":"Novel Method of Temperature Modulation for Enhancing Catalytic Gas Sensor Selectivity","authors":"D. Spirjakin, A. Baranov, S. Akbari, C. T. Phong, N. N. Tuan","doi":"10.1109/SAS51076.2021.9530079","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530079","url":null,"abstract":"Catalytic gas sensors are among the most widespread gas sensors for combustible gas concentration measurements. However, their selectivity is low. In this research, the results of machine learning techniques application to enhance catalytic gas sensor selectivity are presented. The measurements of sensor signal are performed using the multistage heat pulse method described in our previous works. Contrary to the previous works, the number of heating stages was increased from 2 to 55, which corresponds to the heating voltage range of 125 m V to 1.5 V with a 25 m V step. This change enriches sensor signal with information about gas compositions. Methane and vapors of acetone, ethanol and gasoline are used as target gases. A support vector machine method is used to train two models. The first one was trained based on the plain normalized data. It was used for a microcontroller implementation of the method. The second model used the data transformed by principal component analysis technique. This model was used to visualize the method proposed. The results show that the application of proposed method allows to identify gases by single catalytic sensor. These principles can be used to design selective gas detectors which will react only to target gases.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"10 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":"133265702","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530087
M. Diehl, T. Teichmann, J. Zeilfelder, W. Stork
In this paper, a concept for automated anomaly detection for a new method of blood pressure measurement in the ear is presented. When the external auditory canal is closed off airtight, the enlargement of the arteries during the heartbeat causes a volume change of the closed air chamber and thus a pressure fluctuation. Pressure measurement in the ear results in a signal waveform of very small amplitude with respect to the pulse wave and in relation to the sensor noise of currently available absolute pressure sensors. Under real conditions, the useful signals are always exposed to interfering influences such as superimposed motion and environmental artifacts. This results in the necessity of an automatic artifact detection as an important requirement for the analysis of the biosignals in a non-laboratory environment. Different concepts for automated anomaly detection were investigated using a standardized test protocol with test subjects and evaluated regarding their suitability. Context signals were included in the analysis as well as statistical methods were applied to the signal itself. The approach using a one-dimensional convolutional neural network (1DCNN) achieved the best results with an average recognition rate of 79 %. However, the inclusion of acceleration data was identified as a promising addition in specific motion scenarios.
{"title":"Anomaly detection concept for a non-invasive blood pressure measurement method in the ear","authors":"M. Diehl, T. Teichmann, J. Zeilfelder, W. Stork","doi":"10.1109/SAS51076.2021.9530087","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530087","url":null,"abstract":"In this paper, a concept for automated anomaly detection for a new method of blood pressure measurement in the ear is presented. When the external auditory canal is closed off airtight, the enlargement of the arteries during the heartbeat causes a volume change of the closed air chamber and thus a pressure fluctuation. Pressure measurement in the ear results in a signal waveform of very small amplitude with respect to the pulse wave and in relation to the sensor noise of currently available absolute pressure sensors. Under real conditions, the useful signals are always exposed to interfering influences such as superimposed motion and environmental artifacts. This results in the necessity of an automatic artifact detection as an important requirement for the analysis of the biosignals in a non-laboratory environment. Different concepts for automated anomaly detection were investigated using a standardized test protocol with test subjects and evaluated regarding their suitability. Context signals were included in the analysis as well as statistical methods were applied to the signal itself. The approach using a one-dimensional convolutional neural network (1DCNN) achieved the best results with an average recognition rate of 79 %. However, the inclusion of acceleration data was identified as a promising addition in specific motion scenarios.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"9 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":"134433154","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530151
Víctor Asanza, Rebeca Estrada Pico, Danny Torres, S. Santillan, J. Cadena
In this paper, we propose to implement a meteorological monitoring station using embedded systems. This model is possible thanks to different sensors that enable us to measure several environmental parameters, such as i) relative humidity, ii) average ambient temperature, iii) soil humidity, iv) rain occurrence, and v) light intensity. The proposed system is based on a field-programmable gate array device (FPGA). The proposed design aims at ensuring high-resolution data acquisition and at predicting samples with precision and accuracy in real-time. To present the collected data, we develop also a web application with a simple and friendly user interface.
{"title":"FPGA Based Meteorological Monitoring Station","authors":"Víctor Asanza, Rebeca Estrada Pico, Danny Torres, S. Santillan, J. Cadena","doi":"10.1109/SAS51076.2021.9530151","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530151","url":null,"abstract":"In this paper, we propose to implement a meteorological monitoring station using embedded systems. This model is possible thanks to different sensors that enable us to measure several environmental parameters, such as i) relative humidity, ii) average ambient temperature, iii) soil humidity, iv) rain occurrence, and v) light intensity. The proposed system is based on a field-programmable gate array device (FPGA). The proposed design aims at ensuring high-resolution data acquisition and at predicting samples with precision and accuracy in real-time. To present the collected data, we develop also a web application with a simple and friendly user interface.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"69 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":"134424166","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}
Pub Date : 2021-08-23DOI: 10.1109/SAS51076.2021.9530044
Yasmina Souley Dosso, R. Selzler, K. Greenwood, J. Harrold, J. Green
RGB-D cameras have shown promise in noncontact monitoring of patients in the neonatal intensive care unit (NICU). This work conducts essential experiments to assess the suitability and safe use of the Intel RealSense SR300 camera for non-contact neonatal monitoring. Since a pulse oximeter monitoring the patient's oxygen saturation levels (SpO2) senses infrared light, and the RGB-D sensor has an infrared projector, this work investigates a safe camera distance to ensure that the projected infrared light from the camera does not interfere with the SpO2 signal. RGB-D data reflection artifacts from the Plexiglass surface are also explored for single- and double-walled incubators. To prevent from infrared interference and RGB-D data artifacts, we recommend placing the camera at a minimum distance of 40 cm for open beds, and 25 cm for closed incubators. The camera should also be mounted directly on the Plexiglass surface in closed incubators, especially for double-wall designs. We have developed a custom latex apparatus to adhere an SR300 camera to the outer surface of an incubator to avoid reflections while securely mounting the camera without requiring any modification to the incubator itself. This work provides critical information for safe and practical RGB-D camera application in non-contact neonatal monitoring.
{"title":"RGB-D Sensor Application for Non-Contact Neonatal Monitoring","authors":"Yasmina Souley Dosso, R. Selzler, K. Greenwood, J. Harrold, J. Green","doi":"10.1109/SAS51076.2021.9530044","DOIUrl":"https://doi.org/10.1109/SAS51076.2021.9530044","url":null,"abstract":"RGB-D cameras have shown promise in noncontact monitoring of patients in the neonatal intensive care unit (NICU). This work conducts essential experiments to assess the suitability and safe use of the Intel RealSense SR300 camera for non-contact neonatal monitoring. Since a pulse oximeter monitoring the patient's oxygen saturation levels (SpO2) senses infrared light, and the RGB-D sensor has an infrared projector, this work investigates a safe camera distance to ensure that the projected infrared light from the camera does not interfere with the SpO2 signal. RGB-D data reflection artifacts from the Plexiglass surface are also explored for single- and double-walled incubators. To prevent from infrared interference and RGB-D data artifacts, we recommend placing the camera at a minimum distance of 40 cm for open beds, and 25 cm for closed incubators. The camera should also be mounted directly on the Plexiglass surface in closed incubators, especially for double-wall designs. We have developed a custom latex apparatus to adhere an SR300 camera to the outer surface of an incubator to avoid reflections while securely mounting the camera without requiring any modification to the incubator itself. This work provides critical information for safe and practical RGB-D camera application in non-contact neonatal monitoring.","PeriodicalId":224327,"journal":{"name":"2021 IEEE Sensors Applications Symposium (SAS)","volume":"395 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":"133513830","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}
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