Pub Date : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910275
Sirinuch Sararuch, P. Wannapiroon, P. Nilsook
The Impact of Industry Revolution has been accelerated by global pandemic crisis recently. Disruptive technology is one of the key driving forces of transformation on the rapid change in business model and market demand. Traditional industries, including education, experience the challenge of maintaining business at lower cost while generating high performance (more revenue) and staying relevant in the market. Digital Transformation helps improve collaboration within and between organizations by creating immersive customer experience for better engagement. Enterprise organization wants to grow and give it a better chance of thriving post-pandemic by becoming more innovative and generating higher productivity and making better decisions with insights from data-driven platform. To achieve all the business requirements for transformation is not straightforward. By understanding the alignment of Business and Information Technology Architecture, Higher Education institutions can manage the challenges of the future trends. The success of Digital Transformation in enterprise organizations is determined by an agile implementation framework of Enterprise Architecture (EA). Enterprise Architecture is the critical intermediary between business and IT corporate wide strategy. Through understanding the current situation and performance of an enterprise, EA can help foresight future business challenges and deliver the information needed while simultaneously ensuring opportunities for business growth.
{"title":"Dimensions of Agile Enterprise Architecture","authors":"Sirinuch Sararuch, P. Wannapiroon, P. Nilsook","doi":"10.1109/RI2C56397.2022.9910275","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910275","url":null,"abstract":"The Impact of Industry Revolution has been accelerated by global pandemic crisis recently. Disruptive technology is one of the key driving forces of transformation on the rapid change in business model and market demand. Traditional industries, including education, experience the challenge of maintaining business at lower cost while generating high performance (more revenue) and staying relevant in the market. Digital Transformation helps improve collaboration within and between organizations by creating immersive customer experience for better engagement. Enterprise organization wants to grow and give it a better chance of thriving post-pandemic by becoming more innovative and generating higher productivity and making better decisions with insights from data-driven platform. To achieve all the business requirements for transformation is not straightforward. By understanding the alignment of Business and Information Technology Architecture, Higher Education institutions can manage the challenges of the future trends. The success of Digital Transformation in enterprise organizations is determined by an agile implementation framework of Enterprise Architecture (EA). Enterprise Architecture is the critical intermediary between business and IT corporate wide strategy. Through understanding the current situation and performance of an enterprise, EA can help foresight future business challenges and deliver the information needed while simultaneously ensuring opportunities for business growth.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125417805","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 : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910280
K. Ransikarbum, Sreenath Chalil Madathil
Biofuel energy has recently been used as a substitute for fossil fuels due to an increasing energy demand and a concern for environmental impact around the globe. Biomass, in particular, is a key type of biofuel source in Thailand that has been of interest as a national renewable energy plan. In this research, we use the integrated K-means and Rectilinear Minisum Location model to evaluate the wood collection site problem using an actual case study of the Northern part of Thailand. Initially, the K-means classification method is used to classify a group of farmers growing fast-growing trees for energy use in their regional area according to the national campaign. Then, the Rectilinear Minisum Location model is later used to evaluate a proper location for wood collection site to collect wood and produce wood chip for subsequent process of the biofuel supply chain. Our initial study provides promising result and is subject to the on-going development of the sustainable aiming biofuel supply chain model.
{"title":"Analysis of Wood Collection Site in the Biofuel Supply Chain using Integrated K-means and Rectilinear Minisum Location Model","authors":"K. Ransikarbum, Sreenath Chalil Madathil","doi":"10.1109/RI2C56397.2022.9910280","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910280","url":null,"abstract":"Biofuel energy has recently been used as a substitute for fossil fuels due to an increasing energy demand and a concern for environmental impact around the globe. Biomass, in particular, is a key type of biofuel source in Thailand that has been of interest as a national renewable energy plan. In this research, we use the integrated K-means and Rectilinear Minisum Location model to evaluate the wood collection site problem using an actual case study of the Northern part of Thailand. Initially, the K-means classification method is used to classify a group of farmers growing fast-growing trees for energy use in their regional area according to the national campaign. Then, the Rectilinear Minisum Location model is later used to evaluate a proper location for wood collection site to collect wood and produce wood chip for subsequent process of the biofuel supply chain. Our initial study provides promising result and is subject to the on-going development of the sustainable aiming biofuel supply chain model.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127316168","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 : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910272
Yanakorn Ruamsuk, A. Mingkhwan, H. Unger
Short abstracts and text summarisation are gaining increasing the importance of tools for filtering out the most relevant articles due to the increased documents and information. The following article uses TRCs to support text summaries’ generation and evaluation. A new method of document summarisation has been introduced based on text-representing centroids (TRC). TRC-based similarity measure delivers good similarity estimations for both methods, which are in the excellent range of 75 percent on average.
{"title":"Generating and Evaluating Text Summarisations using Text-representing Centroids(TRC)","authors":"Yanakorn Ruamsuk, A. Mingkhwan, H. Unger","doi":"10.1109/RI2C56397.2022.9910272","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910272","url":null,"abstract":"Short abstracts and text summarisation are gaining increasing the importance of tools for filtering out the most relevant articles due to the increased documents and information. The following article uses TRCs to support text summaries’ generation and evaluation. A new method of document summarisation has been introduced based on text-representing centroids (TRC). TRC-based similarity measure delivers good similarity estimations for both methods, which are in the excellent range of 75 percent on average.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133531292","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 : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910304
W. Thaiwirot, Dechawat Kamoldej, Phongsapuk Detchporn, P. Thongdit, Shalermchon Tangwachirapan
This paper presents the antipodal Vivaldi antenna (AVA) with dielectric lens. The AVA which efficiently focuses the energy toward the end-fire direction is required for biomedical applications. For this purpose, the various shapes of dielectric lens i.e., rectangular, triangular, trapezoid, sine, and elliptical-shaped dielectric lens as an extension of dielectric substrate are proposed. The effects of different dielectric lens shapes on enhancement of the gain and electric field in near field region are investigated. In order to confirm the validate in the designing, the AVA with elliptical dielectric lens is fabricated with the dimension of 45 mm × 90 mm. The measured results show that the proposed antenna can provide wide impedance bandwidth, covering the frequency range from 3.06 GHz to over 10 GHz. The proposed antenna has a maximum gain of 13.18 dBi at 10 GHz.
提出了一种带介质透镜的对映维瓦尔第天线(AVA)。AVA能有效地将能量聚焦到末射方向，是生物医学应用所需要的。为此，提出了作为介质衬底延伸的矩形、三角形、梯形、正弦形和椭圆形介质透镜的各种形状。研究了不同介质透镜形状对近场增益和电场增强的影响。为了验证设计上的正确性，制作了尺寸为45 mm × 90 mm的椭圆介质透镜AVA。测量结果表明，该天线具有较宽的阻抗带宽，覆盖了3.06 GHz到10 GHz以上的频率范围。该天线在10 GHz时的最大增益为13.18 dBi。
{"title":"Antipodal Vivaldi Antenna with Dielectric Lens for Biomedical Imaging Applications","authors":"W. Thaiwirot, Dechawat Kamoldej, Phongsapuk Detchporn, P. Thongdit, Shalermchon Tangwachirapan","doi":"10.1109/RI2C56397.2022.9910304","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910304","url":null,"abstract":"This paper presents the antipodal Vivaldi antenna (AVA) with dielectric lens. The AVA which efficiently focuses the energy toward the end-fire direction is required for biomedical applications. For this purpose, the various shapes of dielectric lens i.e., rectangular, triangular, trapezoid, sine, and elliptical-shaped dielectric lens as an extension of dielectric substrate are proposed. The effects of different dielectric lens shapes on enhancement of the gain and electric field in near field region are investigated. In order to confirm the validate in the designing, the AVA with elliptical dielectric lens is fabricated with the dimension of 45 mm × 90 mm. The measured results show that the proposed antenna can provide wide impedance bandwidth, covering the frequency range from 3.06 GHz to over 10 GHz. The proposed antenna has a maximum gain of 13.18 dBi at 10 GHz.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134052188","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 : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910267
S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul
The development of inertial sensor technology and the growing utilization of wearable electronics (such as smartwatches, smart bands, and other intelligent gadgets) have facilitated the advancement of studies into automated Fall Detection Systems (FDSs). In the last decade, there has been significant scientific interest in maintaining FDSs. Focused on assessing the data acquired by wearable inertial sensors, machine learning (ML) techniques have demonstrated high efficacy in distinguishing falls from typical motions or activities of daily living (ADLs). In most research, unfortunately, the effectiveness of machine learning classifiers was constrained by feature extraction and selection processes that relied on human-made decisions. Recently, deep learning (DL) model findings s how their effectiveness for FDS. One of these effective DL models is the ResNeXt model, a deep neural network that operates based on convolutional layers with aggregated residual transformation. This study investigates the influence of sensor placement on various body locations for the fall detection issue. The ResNeXt model was assessed and compared to other baseline deep learning algorithms using the public UMAFall dataset for fall detection. Employing sensor data on waist location, the suggested model attained the most significant classification ac curacy of 97.275% when classifying falls.
{"title":"The Effect of Sensor Placement for Accurate Fall Detection based on Deep Learning Model","authors":"S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul","doi":"10.1109/RI2C56397.2022.9910267","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910267","url":null,"abstract":"The development of inertial sensor technology and the growing utilization of wearable electronics (such as smartwatches, smart bands, and other intelligent gadgets) have facilitated the advancement of studies into automated Fall Detection Systems (FDSs). In the last decade, there has been significant scientific interest in maintaining FDSs. Focused on assessing the data acquired by wearable inertial sensors, machine learning (ML) techniques have demonstrated high efficacy in distinguishing falls from typical motions or activities of daily living (ADLs). In most research, unfortunately, the effectiveness of machine learning classifiers was constrained by feature extraction and selection processes that relied on human-made decisions. Recently, deep learning (DL) model findings s how their effectiveness for FDS. One of these effective DL models is the ResNeXt model, a deep neural network that operates based on convolutional layers with aggregated residual transformation. This study investigates the influence of sensor placement on various body locations for the fall detection issue. The ResNeXt model was assessed and compared to other baseline deep learning algorithms using the public UMAFall dataset for fall detection. Employing sensor data on waist location, the suggested model attained the most significant classification ac curacy of 97.275% when classifying falls.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128620449","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}
The biggest problem with using the toilet in department stores is that people do not know the restroom location, the number of users (volume), the restroom status (available/unavailable), and the symbol direction not clear. It raises new issues to find the restroom and wait in a queue if several people are in line. This paper proposed the application of microcontrollers and the Internet of Things for checking restroom status. The system consists of three main modules, 1) counting the number of users in the toilet and turning off the light if there is no available user, 2) verifying sink status (available/unavailable), and 3) verifying toilet status (available/unavailable). Also, the system can control and monitor by using the mobile application supported by the Internet of Things. The results showed that the proposed system works all functions, and the satisfaction assessment of users is, on average, 4.57 out of 5. The application of the system can be used for a smart room in daily life.
{"title":"Microcontroller and Internet of Things Application for Smart Restroom","authors":"Jirawat Thaenthong, Varinthon Kwanjun, Phimsai Charoensuk","doi":"10.1109/RI2C56397.2022.9910335","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910335","url":null,"abstract":"The biggest problem with using the toilet in department stores is that people do not know the restroom location, the number of users (volume), the restroom status (available/unavailable), and the symbol direction not clear. It raises new issues to find the restroom and wait in a queue if several people are in line. This paper proposed the application of microcontrollers and the Internet of Things for checking restroom status. The system consists of three main modules, 1) counting the number of users in the toilet and turning off the light if there is no available user, 2) verifying sink status (available/unavailable), and 3) verifying toilet status (available/unavailable). Also, the system can control and monitor by using the mobile application supported by the Internet of Things. The results showed that the proposed system works all functions, and the satisfaction assessment of users is, on average, 4.57 out of 5. The application of the system can be used for a smart room in daily life.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116915622","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 : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910318
S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul
Smartwatches are becoming more popular for recognizing and monitoring human actions in everyday life. These wearable devices are equipped with various IMU sensors for ubiquitous data processing and recording of human physical activity data. Sensor-based human activity recognition (HAR) has risen to the top of the list of the most active research topic due to its widely real-life applications in various practical domains, such as healthcare monitoring, sports and exercise tracking, and misbehavior prevention. Many machine learning and deep learning approaches have been recently proposed to solve the problem of human activity recognition, focusing on activities of daily living. However, an exciting and challenging HAR topic deals with more complex human activities such as eating-related activities. This paper proposes a sensor-based HAR framework using data from eating-related activities recorded by a smartwatch sensor. In this framework, five d eep learning networks (CNN, LSTM, BiLSTM, Stacked LSTM, CNN-LSTM, and LSTM-CNN) are evaluated for their recognition of eating-related activities. To ensure the model’s dependability, data from eating-related activities on the standard publicly available dataset WISDM-HARB are utilized to evaluate the proposed framework using state-of-the-art metrics: accuracy and confusion matrices. Experiment findings demonstrate that the S tacked LSTM model outperforms other deep learning models, achieving an accuracy of 97.37%.
{"title":"Deep Learning Networks for Eating and Drinking Recognition based on Smartwatch Sensors","authors":"S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul","doi":"10.1109/RI2C56397.2022.9910318","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910318","url":null,"abstract":"Smartwatches are becoming more popular for recognizing and monitoring human actions in everyday life. These wearable devices are equipped with various IMU sensors for ubiquitous data processing and recording of human physical activity data. Sensor-based human activity recognition (HAR) has risen to the top of the list of the most active research topic due to its widely real-life applications in various practical domains, such as healthcare monitoring, sports and exercise tracking, and misbehavior prevention. Many machine learning and deep learning approaches have been recently proposed to solve the problem of human activity recognition, focusing on activities of daily living. However, an exciting and challenging HAR topic deals with more complex human activities such as eating-related activities. This paper proposes a sensor-based HAR framework using data from eating-related activities recorded by a smartwatch sensor. In this framework, five d eep learning networks (CNN, LSTM, BiLSTM, Stacked LSTM, CNN-LSTM, and LSTM-CNN) are evaluated for their recognition of eating-related activities. To ensure the model’s dependability, data from eating-related activities on the standard publicly available dataset WISDM-HARB are utilized to evaluate the proposed framework using state-of-the-art metrics: accuracy and confusion matrices. Experiment findings demonstrate that the S tacked LSTM model outperforms other deep learning models, achieving an accuracy of 97.37%.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194222","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 : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910309
P. Kittiboonanan, Jack B. McWilliams, Polsin Taechamaneesatit, A. Ratanavis
In this research, we present the use of a solid-state laser for the paint removal on an aluminum AA6061 sheet. The laser utilized, was operating at a wavelength of 1064 nm and used to remove paint applied from a hand-held spray paint can. The pulse duration of the laser was 100 ns at 50 kHz of repetition rate, maximum pulse energy being 1 mJ. The laser pulse frequencies were varied from 50 kHz to 200 kHz and in combination with varying the features of pulse overlapping, an infinite array of paint removal parameters can be achieved. The cleaning results are shown in the images by the SEM and the spectrums from the EDX operating mode, used to determine the cleaning result of painted layer. This study shows that this laser technology is a contactless cleaning method to remove paint on an Aluminum AA6061 sheet. This is an alternative cleaning method, environmentally friendly and contributes to reduce pollution on the atmosphere.
{"title":"Effect of Laser Pulse Overlap using Nanosecond Pulsed Lasers for Paint Removal on AA6061","authors":"P. Kittiboonanan, Jack B. McWilliams, Polsin Taechamaneesatit, A. Ratanavis","doi":"10.1109/RI2C56397.2022.9910309","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910309","url":null,"abstract":"In this research, we present the use of a solid-state laser for the paint removal on an aluminum AA6061 sheet. The laser utilized, was operating at a wavelength of 1064 nm and used to remove paint applied from a hand-held spray paint can. The pulse duration of the laser was 100 ns at 50 kHz of repetition rate, maximum pulse energy being 1 mJ. The laser pulse frequencies were varied from 50 kHz to 200 kHz and in combination with varying the features of pulse overlapping, an infinite array of paint removal parameters can be achieved. The cleaning results are shown in the images by the SEM and the spectrums from the EDX operating mode, used to determine the cleaning result of painted layer. This study shows that this laser technology is a contactless cleaning method to remove paint on an Aluminum AA6061 sheet. This is an alternative cleaning method, environmentally friendly and contributes to reduce pollution on the atmosphere.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126727385","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 : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910338
N. Chudpooti, Patchadaporn Sangpet, Sukanya Chudpooti, P. Akkaraekthalin, I. Robertson, N. Somjit
This paper presents a 3D-printed hemispherical lens incorporated with a square patch microstrip antenna for liquid-mixture characterization. The proposed hemispherical lens antenna is designed, fabricated, and integrated with the microstrip patch planar antenna. An Acrylonitrile Butadiene Styrene (ABS) is selected to design the 3D-printed lens antenna by using the fused deposition modeling (FDM) method, due to available 3D-printed material in the laboratory. The optimum dimensions and shape of the hemispherical lens antenna are obtained by using the 3D EM Simulation CST Studio, which is used to investigate the characteristic of the antenna, e.g., gain, radiation pattern, and reflection coefficient. To characterize the liquid content in NaCl solution, the level of the transmission coefficient (S21) is detected. The proposed sensor system offers various preferable features, e.g., non-destructive method and non-contact measurement. Five liquid solutions under test (LUT), e.g., 5%, 10%, 15%, 20%, and 25% NaCl in the NaCl-aqueous solutions, are measured and performed to generate the extraction model. The proposed sensor also offers other advantages, e.g., real-time monitoring and no life-cycle limitation.
本文提出了一种3d打印的半球面透镜，该透镜结合了方形贴片微带天线，用于液体混合物的表征。设计、制作了半球面透镜天线，并将其与微带贴片平面天线集成。由于实验室中有可用的3d打印材料，因此选择丙烯腈-丁二烯-苯乙烯(ABS)材料使用熔融沉积建模(FDM)方法来设计3d打印透镜天线。利用3D EM Simulation CST Studio获得了半球面透镜天线的最佳尺寸和形状，并对天线的增益、辐射方向图和反射系数等特性进行了研究。为了表征NaCl溶液中的液体含量，检测了透射系数(S21)的水平。所提出的传感器系统提供各种优选特性，例如，非破坏性方法和非接触式测量。通过测量NaCl水溶液中5%、10%、15%、20%和25% NaCl的五种被测液体溶液(LUT)，生成萃取模型。该传感器还具有其他优点，例如实时监控和无生命周期限制。
{"title":"An Incorporated 3D-Printed Lens with Square Microstrip Patch Antenna for NaCl Solution Discrimination","authors":"N. Chudpooti, Patchadaporn Sangpet, Sukanya Chudpooti, P. Akkaraekthalin, I. Robertson, N. Somjit","doi":"10.1109/RI2C56397.2022.9910338","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910338","url":null,"abstract":"This paper presents a 3D-printed hemispherical lens incorporated with a square patch microstrip antenna for liquid-mixture characterization. The proposed hemispherical lens antenna is designed, fabricated, and integrated with the microstrip patch planar antenna. An Acrylonitrile Butadiene Styrene (ABS) is selected to design the 3D-printed lens antenna by using the fused deposition modeling (FDM) method, due to available 3D-printed material in the laboratory. The optimum dimensions and shape of the hemispherical lens antenna are obtained by using the 3D EM Simulation CST Studio, which is used to investigate the characteristic of the antenna, e.g., gain, radiation pattern, and reflection coefficient. To characterize the liquid content in NaCl solution, the level of the transmission coefficient (S21) is detected. The proposed sensor system offers various preferable features, e.g., non-destructive method and non-contact measurement. Five liquid solutions under test (LUT), e.g., 5%, 10%, 15%, 20%, and 25% NaCl in the NaCl-aqueous solutions, are measured and performed to generate the extraction model. The proposed sensor also offers other advantages, e.g., real-time monitoring and no life-cycle limitation.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122661614","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 : 2022-08-04DOI: 10.1109/RI2C56397.2022.9910285
Nattawat Chantasen, Nattakarn Shutimarrungson, A. Boonpoonga, Lakkhana Bannawat, P. Akkaraekthalin
This paper presents an investigation of the metal crack with the chipless RFID tag. The main part of the tags is a circular microstrip patch antenna (CMPA) resonator. To indicate the bit ID of tags using the resonant frequencies, the slots were created within the CMPA resonator. A short-time matrix pencil method (STMPM) was used to extract poles of the chipless RFID tag from signal backscattering. The performance of metal crack detection using STMPM was evaluated via simulations. The resonant frequencies of the tag were investigated in order to detect the crack of the metal plate. The results showed a crack on the metal affects natural frequencies shift.
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