Pub Date : 2021-04-27DOI: 10.1109/SSI52265.2021.9466995
N. Fusté, O. Aviñó, X. Perpiñà, D. Sánchez, M. Vellvehí, X. Jordà
A determination of the Anand viscoplastic model parameters for 88Au12Ge solder alloy is presented in this work. Using experimental data from temperature and rate dependent shear stress tests, the nine characteristic parameters for the aforementioned model were obtained through non-linear fitting using a Least Squared Residual approach. The calculated estimated parameters were used to replicate the conditions of the experimental shear test using Finite Element Simulations in order to validate the final model obtained. Results show a fitting temperature dependency with understress at lower temperatures and a tendency to overstress at higher temperatures. The obtained model response shows no rate dependent behaviour (probably as a result of the small dataset used) and the non-ideal Anand distribution of saturation stresses of the experimental data. Nervetheless, the proposed approach provides a parameter dataset useful for FEA thermos-mechanical simulation of die-attach layers in power modules.
{"title":"Determination of Anand viscoplastic constitutive parameters for the AuGe solder alloy from experimental stress-strain curves for power systems integration FEA simulations","authors":"N. Fusté, O. Aviñó, X. Perpiñà, D. Sánchez, M. Vellvehí, X. Jordà","doi":"10.1109/SSI52265.2021.9466995","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9466995","url":null,"abstract":"A determination of the Anand viscoplastic model parameters for 88Au12Ge solder alloy is presented in this work. Using experimental data from temperature and rate dependent shear stress tests, the nine characteristic parameters for the aforementioned model were obtained through non-linear fitting using a Least Squared Residual approach. The calculated estimated parameters were used to replicate the conditions of the experimental shear test using Finite Element Simulations in order to validate the final model obtained. Results show a fitting temperature dependency with understress at lower temperatures and a tendency to overstress at higher temperatures. The obtained model response shows no rate dependent behaviour (probably as a result of the small dataset used) and the non-ideal Anand distribution of saturation stresses of the experimental data. Nervetheless, the proposed approach provides a parameter dataset useful for FEA thermos-mechanical simulation of die-attach layers in power modules.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122931608","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9467012
Christian Möller, Heike Wünscher, T. Frank, T. Ortlepp
We introduce the development of an electrical and an optical ammonia sensor. The electrical sensor enables a continuous monitoring of ammonia by electrical impedance measurement of condensate gases. The optical sensor is based on the principle of non-dispersive ultra violet spectroscopy (NDUV) and should enable the measurement of the ammonia content in the exhaust tract.
{"title":"Ammonia Sensors – Different Measurement Principles","authors":"Christian Möller, Heike Wünscher, T. Frank, T. Ortlepp","doi":"10.1109/SSI52265.2021.9467012","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9467012","url":null,"abstract":"We introduce the development of an electrical and an optical ammonia sensor. The electrical sensor enables a continuous monitoring of ammonia by electrical impedance measurement of condensate gases. The optical sensor is based on the principle of non-dispersive ultra violet spectroscopy (NDUV) and should enable the measurement of the ammonia content in the exhaust tract.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128182834","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9466970
S. Voigt, Chun-Kwon Lee, J. Joung, S. Kurth, F. Roscher
Degrading cable connections are a major problem in the medium-voltage grid. Early failure detection is therefore very important. In this paper, a flexible, small-sized, self-sufficient wireless monitoring system for medium voltage cable joints is presented. The system can be fitted easily around all common power cables with shielding and cable joints. Even the current induction energy harvester has a flexible design. From a current flow of around 15 amperes, the radio electronics and sensor technology are supplied with sufficient energy. With the help of the integrated sensors, partial discharge (PD), fault current, over-temperature and external impacts like vibrations or shocks can be measured. The whole sensor node including radio, sensors and energy harvester is designed for and practically tested in a wide operating temperature range from − 40 °C to + 110 °C. The system is currently undergoing extensive field tests.
{"title":"Flexible Multi Sensor Monitoring System for Medium Voltage Cable Joints","authors":"S. Voigt, Chun-Kwon Lee, J. Joung, S. Kurth, F. Roscher","doi":"10.1109/SSI52265.2021.9466970","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9466970","url":null,"abstract":"Degrading cable connections are a major problem in the medium-voltage grid. Early failure detection is therefore very important. In this paper, a flexible, small-sized, self-sufficient wireless monitoring system for medium voltage cable joints is presented. The system can be fitted easily around all common power cables with shielding and cable joints. Even the current induction energy harvester has a flexible design. From a current flow of around 15 amperes, the radio electronics and sensor technology are supplied with sufficient energy. With the help of the integrated sensors, partial discharge (PD), fault current, over-temperature and external impacts like vibrations or shocks can be measured. The whole sensor node including radio, sensors and energy harvester is designed for and practically tested in a wide operating temperature range from − 40 °C to + 110 °C. The system is currently undergoing extensive field tests.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131656005","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9467029
Claudia Bruno, Antonella Licciardello, G.A.M. Nastasi, F. Passaniti, C. Brigante, Francesco Sudano, Alessandro Faulisi, E. Alessi
Smart agriculture represents one of the greatest potential scenarios in the field of the Internet of Things (IoT). Sensory and connectivity technologies together with big data analysis make the farming more accurate and controlled, overcoming the current model of intensive production. It allows farmers to accurately assess the amounts of water, fertilizers, and pesticides needed. Consequently, it guarantees better and healthier crops as well as costs reduction. The adoption of low cost and low power smart air probes based on gas, humidity, pressure and temperature sensors for monitoring air quality and environment conditions and crop emissions, is arising to become a fundamental instrument to be used to provide decision support to the farmers. Moreover, to embed edge computing in the probe for pre-process measurements enhance the potentiality of sensors increasing efficiency and reducing the amount of information traveling in the cloud. By focusing on the sensory features of the platform, the paper aims to exploit the developing a gas recognition algorithm which embeds a neural network and that is able to recognize different types of gas such as NH3, CH4, N20 on the basis of data coming from a gas sensor. Metal-oxide-semiconductor (MOX) gas sensors are generally low-cost sensors made of a single sensing material and are not characterized by an excellent selectivity with respect to different gases; for this reason, an embedded algorithm able to identify the gas type is the key feature to enable the adoption of the MOX technology in smart agriculture applications. This paper presents an AI method to enhance the selectivity feature of a MOX gas sensor. An artificial neural network (ANN) has been implemented and trained in Python environment, using different machine learning tools, such as Keras and scikit-learn. The trained ANN was able to recognize four types of gas detected by the embedded MOX gas sensor in lab conditions. By using X-CUBE-AI tool, the C-model implementation of the pre-trained ANN was generated and embedded in a low power STM32 microcontroller used in the smart air probe.
{"title":"Embedded Artificial Intelligence Approach for Gas Recognition in Smart Agriculture Applications Using Low Cost MOX Gas Sensors","authors":"Claudia Bruno, Antonella Licciardello, G.A.M. Nastasi, F. Passaniti, C. Brigante, Francesco Sudano, Alessandro Faulisi, E. Alessi","doi":"10.1109/SSI52265.2021.9467029","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9467029","url":null,"abstract":"Smart agriculture represents one of the greatest potential scenarios in the field of the Internet of Things (IoT). Sensory and connectivity technologies together with big data analysis make the farming more accurate and controlled, overcoming the current model of intensive production. It allows farmers to accurately assess the amounts of water, fertilizers, and pesticides needed. Consequently, it guarantees better and healthier crops as well as costs reduction. The adoption of low cost and low power smart air probes based on gas, humidity, pressure and temperature sensors for monitoring air quality and environment conditions and crop emissions, is arising to become a fundamental instrument to be used to provide decision support to the farmers. Moreover, to embed edge computing in the probe for pre-process measurements enhance the potentiality of sensors increasing efficiency and reducing the amount of information traveling in the cloud. By focusing on the sensory features of the platform, the paper aims to exploit the developing a gas recognition algorithm which embeds a neural network and that is able to recognize different types of gas such as NH3, CH4, N20 on the basis of data coming from a gas sensor. Metal-oxide-semiconductor (MOX) gas sensors are generally low-cost sensors made of a single sensing material and are not characterized by an excellent selectivity with respect to different gases; for this reason, an embedded algorithm able to identify the gas type is the key feature to enable the adoption of the MOX technology in smart agriculture applications. This paper presents an AI method to enhance the selectivity feature of a MOX gas sensor. An artificial neural network (ANN) has been implemented and trained in Python environment, using different machine learning tools, such as Keras and scikit-learn. The trained ANN was able to recognize four types of gas detected by the embedded MOX gas sensor in lab conditions. By using X-CUBE-AI tool, the C-model implementation of the pre-trained ANN was generated and embedded in a low power STM32 microcontroller used in the smart air probe.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133420389","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9466987
Guido Colombo
Today INDUSTRY4.0 looks at Edge Computing [1] as the technology able to transform raw data from machineries and sensors directly into valuable information made available for proximity services in order to actively support machine operators and maintenance teams acting in the shopfloor.
{"title":"Cloud Driven Edge Computing on Smart Systems Integration","authors":"Guido Colombo","doi":"10.1109/SSI52265.2021.9466987","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9466987","url":null,"abstract":"Today INDUSTRY4.0 looks at Edge Computing [1] as the technology able to transform raw data from machineries and sensors directly into valuable information made available for proximity services in order to actively support machine operators and maintenance teams acting in the shopfloor.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123993353","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9467021
D. Bulz, S. Weidlich, S. Konietzka, T. Motl, A. Shaporin, R. Forke, K. Hiller, H. Kuhn
North-finders based on gyroscopes are commonly used because of their robustness against local Earth magnetic field distortion and independence of electromagnetic transmission. In this paper, we present an easy to use, compact, transportable, standalone, north-finder based on one MEMS gyroscope. The Maytagging algorithm allows the use of an inexpensive stepper motor. The integrated in-house developed tuning fork MEMS gyroscopes offer low enough noise and drift to determine north heading down to 1 degree of deviation in less than 10 minutes at a latitude of 50.8 degrees without additional signal conversion electronics.
{"title":"Compact Standalone North-finding Device based on MEMS Gyroscope and Maytagging","authors":"D. Bulz, S. Weidlich, S. Konietzka, T. Motl, A. Shaporin, R. Forke, K. Hiller, H. Kuhn","doi":"10.1109/SSI52265.2021.9467021","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9467021","url":null,"abstract":"North-finders based on gyroscopes are commonly used because of their robustness against local Earth magnetic field distortion and independence of electromagnetic transmission. In this paper, we present an easy to use, compact, transportable, standalone, north-finder based on one MEMS gyroscope. The Maytagging algorithm allows the use of an inexpensive stepper motor. The integrated in-house developed tuning fork MEMS gyroscopes offer low enough noise and drift to determine north heading down to 1 degree of deviation in less than 10 minutes at a latitude of 50.8 degrees without additional signal conversion electronics.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127166261","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9466996
F. Selbmann, F. Roscher, Felipe de Souza Tortato, M. Wiemer, T. Otto, Yvonne Joseph
Following the current trends towards Industry 4.0 and the Internet of Things, flexible electronics and sensors are a key enabling technology for the realization of wearables and geometry adaptive devices. Within this study, we present a new approach for the fabrication of an ultra-thin and highly flexible printed circuit board (PCB), featuring multiple metallization layers and a thickness of < 20 μm only. Doing so, the polymer Parylene served as substrate material, as dielectric between the metallization layers as well as for the encapsulation and protection. Within this paper, the concept of this new approach as well as different options for the fabrication technologies and possible applications are presented in detail. Finally, the fabricated Parylene based ultra-thin flexible PCB was characterized mechanically and electrically.
{"title":"An ultra-thin and highly flexible multilayer Printed Circuit Board based on Parylene","authors":"F. Selbmann, F. Roscher, Felipe de Souza Tortato, M. Wiemer, T. Otto, Yvonne Joseph","doi":"10.1109/SSI52265.2021.9466996","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9466996","url":null,"abstract":"Following the current trends towards Industry 4.0 and the Internet of Things, flexible electronics and sensors are a key enabling technology for the realization of wearables and geometry adaptive devices. Within this study, we present a new approach for the fabrication of an ultra-thin and highly flexible printed circuit board (PCB), featuring multiple metallization layers and a thickness of < 20 μm only. Doing so, the polymer Parylene served as substrate material, as dielectric between the metallization layers as well as for the encapsulation and protection. Within this paper, the concept of this new approach as well as different options for the fabrication technologies and possible applications are presented in detail. Finally, the fabricated Parylene based ultra-thin flexible PCB was characterized mechanically and electrically.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131037546","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9466961
Souvik Kundu, B. O’flynn, Javier Torres Sanchez, M. Walsh
The Tactile Internet, which is considered by many to be the next generation of Internet of Things (IoT), will enable real time Human Computer Interaction (HCI) systems capable of delivering tactile experiences remotely from the machine to the operator. Tactile Internet application fields include the tactile robot teleoperation, which constitutes the next generation of collaborative robots, equipped with sensing capabilities to process humanlike tactile sensation in Augmented/Virtual Reality (AR/VR) applications, i.e. advanced AR/VR training or education environments, Automotive and other application domains where Human Machine Interfaces (HMI) are required [1]. Tactile Enabled battery powered HCI devices must satisfy ultra-low latency haptic media constraints which are an order of magnitude more sensitive to delays when compared to audio and visual media [2] as well as low power consumption constrains required by battery powered portable or wearable technology. This paper describes the design considerations for power efficient low latency tactile feedback technology and the modelling and characterization of the system level latency associated with a tactile piezoelectric actuator driver. Such a driver architecture is envisaged to be used to implement haptic feedback in HMI scenarios, with a focus on reducing the latency of, battery powered, piezoelectric based tactile enabled HCI devices.
{"title":"Low Latency Haptic Feedback for Battery Powered HCI for the Tactile Internet","authors":"Souvik Kundu, B. O’flynn, Javier Torres Sanchez, M. Walsh","doi":"10.1109/SSI52265.2021.9466961","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9466961","url":null,"abstract":"The Tactile Internet, which is considered by many to be the next generation of Internet of Things (IoT), will enable real time Human Computer Interaction (HCI) systems capable of delivering tactile experiences remotely from the machine to the operator. Tactile Internet application fields include the tactile robot teleoperation, which constitutes the next generation of collaborative robots, equipped with sensing capabilities to process humanlike tactile sensation in Augmented/Virtual Reality (AR/VR) applications, i.e. advanced AR/VR training or education environments, Automotive and other application domains where Human Machine Interfaces (HMI) are required [1]. Tactile Enabled battery powered HCI devices must satisfy ultra-low latency haptic media constraints which are an order of magnitude more sensitive to delays when compared to audio and visual media [2] as well as low power consumption constrains required by battery powered portable or wearable technology. This paper describes the design considerations for power efficient low latency tactile feedback technology and the modelling and characterization of the system level latency associated with a tactile piezoelectric actuator driver. Such a driver architecture is envisaged to be used to implement haptic feedback in HMI scenarios, with a focus on reducing the latency of, battery powered, piezoelectric based tactile enabled HCI devices.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122515855","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9466993
G. Lammel, R. Dorsch, Timo Giesselmann, Jens Goldeck, Jochen Hahn, Nouman Naim Hasan, Juergen Meier, Kaustubh Gandhi
Mobile devices like smartphones, smartwatches, hearables and others rely more and more on MEMS sensors as user interface and as a link to the physical world. Powerful algorithms can detect meaningful features and classify sensor data, like counting steps from motion sensors, classifying different sport activities, detecting gestures for device control or dead reckoning for pedestrian navigation. In order to achieve ultra-low power consumption in execution of high performance algorithms, while staying flexible in programming, we developed over the last years specialized architectures for smart sensor systems, focusing on close hardware/software co-design.
{"title":"Smart System Architecture for Sensors with Integrated Signal Processing and AI","authors":"G. Lammel, R. Dorsch, Timo Giesselmann, Jens Goldeck, Jochen Hahn, Nouman Naim Hasan, Juergen Meier, Kaustubh Gandhi","doi":"10.1109/SSI52265.2021.9466993","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9466993","url":null,"abstract":"Mobile devices like smartphones, smartwatches, hearables and others rely more and more on MEMS sensors as user interface and as a link to the physical world. Powerful algorithms can detect meaningful features and classify sensor data, like counting steps from motion sensors, classifying different sport activities, detecting gestures for device control or dead reckoning for pedestrian navigation. In order to achieve ultra-low power consumption in execution of high performance algorithms, while staying flexible in programming, we developed over the last years specialized architectures for smart sensor systems, focusing on close hardware/software co-design.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115668508","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 : 2021-04-27DOI: 10.1109/SSI52265.2021.9467024
Kianoush Rassels, Paddy J. French
One of the important measured vital signs in neonates is the body temperature. The traditional measurement uses adhesive pads, but medical staff are hindered by connectors attached to the infant. Remote infrared thermal imaging techniques provide a non-intrusive and safe method to measure body temperature. By means of the thermography technology, it is possible to monitor the variations and trends in the body temperature, which is more reliable, faster, less stressful than traditional methods. Measuring body temperature of a moving neonate remains a challenge. Moreover, factors like humidity, thermal lens forming through the incubator portholes, thermal noise from inside and outside the incubator, camera position and limited Field of View through the incubator portholes, etc. could disrupt a reliable measurement. This study will focus on developing a technique that measures neonates’ body temperature accurately in an incubator. By eliminating unwanted external factors, continual measurement of a Region of Interest (ROI) become more feasible from which trends become available for the techniques like Artificial Intelligence, Machine Learning or Deep Learning. Moreover, this method reduces stress and discomfort for the infant. The outcome of this study is more accurate and the temperature profile of a geometric shapes or ROI over time provides a valuable input to the physicians or nurses to provide higher quality care.
{"title":"Accurate Body Temperature Measurement of a Neonate Uusing Thermography Technology","authors":"Kianoush Rassels, Paddy J. French","doi":"10.1109/SSI52265.2021.9467024","DOIUrl":"https://doi.org/10.1109/SSI52265.2021.9467024","url":null,"abstract":"One of the important measured vital signs in neonates is the body temperature. The traditional measurement uses adhesive pads, but medical staff are hindered by connectors attached to the infant. Remote infrared thermal imaging techniques provide a non-intrusive and safe method to measure body temperature. By means of the thermography technology, it is possible to monitor the variations and trends in the body temperature, which is more reliable, faster, less stressful than traditional methods. Measuring body temperature of a moving neonate remains a challenge. Moreover, factors like humidity, thermal lens forming through the incubator portholes, thermal noise from inside and outside the incubator, camera position and limited Field of View through the incubator portholes, etc. could disrupt a reliable measurement. This study will focus on developing a technique that measures neonates’ body temperature accurately in an incubator. By eliminating unwanted external factors, continual measurement of a Region of Interest (ROI) become more feasible from which trends become available for the techniques like Artificial Intelligence, Machine Learning or Deep Learning. Moreover, this method reduces stress and discomfort for the infant. The outcome of this study is more accurate and the temperature profile of a geometric shapes or ROI over time provides a valuable input to the physicians or nurses to provide higher quality care.","PeriodicalId":382081,"journal":{"name":"2021 Smart Systems Integration (SSI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127108812","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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