Advances in histopathological image segmentation have a significant role in the diagnosis and begin treatment immediately including a study of Cytomegalovirus(CMV) for the tissues. Histopathological change with confirmation by immuno-histochemical or in situ hybridization study is a gold standard for diagnosis of CMV tissue infection. This required pathologists to identify the histopathological change which is time-consuming and can be missed in tissue with a subtle change. Automatic analysis of histopathological images with Deep Learning(DL) can help pathologists to diagnose CMV tissue infection more accurately. Typical issues with histopathological images which impede automatic analysis are the extremely enormous size of histopathological images more than 1 gigapixel, the limitations of GPU memory, and a limited number of histopathology images. Additionally, whole slide histopathological images are split huge images into multiple small image patches by cropping using the sliding window technique. In this paper, we propose TransEN U-Net which derives a benefit of a hybrid CNN-Transformer base on the U-shaped architecture for boosting the performance of segmentation of histopathology. The transformer encoder not only is able to the patches but also the relative self-attention mechanism in order to share information between sequences. Experiment results of segmenting images by the two-dimensional indicate that the TransEN U-Net can productively discriminate CMV viral inclusions including achieving higher values in terms of DSC score.
{"title":"TransEN U-Net: Enhance Image Segmentation of Cytomegalovirus Infected Cells in Histopathological Images","authors":"Warunee Sermpanichakij, Duangjai Jitkongchuen, Tanatip Prasertchai","doi":"10.1109/ECTIDAMTNCON57770.2023.10139588","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139588","url":null,"abstract":"Advances in histopathological image segmentation have a significant role in the diagnosis and begin treatment immediately including a study of Cytomegalovirus(CMV) for the tissues. Histopathological change with confirmation by immuno-histochemical or in situ hybridization study is a gold standard for diagnosis of CMV tissue infection. This required pathologists to identify the histopathological change which is time-consuming and can be missed in tissue with a subtle change. Automatic analysis of histopathological images with Deep Learning(DL) can help pathologists to diagnose CMV tissue infection more accurately. Typical issues with histopathological images which impede automatic analysis are the extremely enormous size of histopathological images more than 1 gigapixel, the limitations of GPU memory, and a limited number of histopathology images. Additionally, whole slide histopathological images are split huge images into multiple small image patches by cropping using the sliding window technique. In this paper, we propose TransEN U-Net which derives a benefit of a hybrid CNN-Transformer base on the U-shaped architecture for boosting the performance of segmentation of histopathology. The transformer encoder not only is able to the patches but also the relative self-attention mechanism in order to share information between sequences. Experiment results of segmenting images by the two-dimensional indicate that the TransEN U-Net can productively discriminate CMV viral inclusions including achieving higher values in terms of DSC score.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"23 1","pages":"238-243"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83281325","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 physiological variables of drinking coconut water compared to plain water (2 ml per kg of body weight) in running mini-marathons $(mathbf{N}=6)$ and half-marathons $(mathbf{N}=6)$. The results show that the average running time and recovery time of the mini-marathon volunteers who drank coconut water were statistically significantly higher than normal water $(mathbf{p} < 0.05)$. For the half-marathon volunteers, drinking coconut water or plain water had no effect on total running time, but drinking coconut water had a significantly greater effect on recovery time after running $(mathbf{p} < 0.05)$, than drinking plain water. In conclusion, drinking coconut water influences the average running time and recovery time of mini-marathon participants, as well as the recovery time of half-marathon participants.
{"title":"Effects of Drinking Coconut Water on Circulatory and Respiratory Function and Post-Workout Recovery in Long Distance Runners","authors":"Pranee U-siri, Pattawan Lapo, Pichet Chailert, Payungsak Tantipaiboonwong, Komsak Pintha","doi":"10.1109/ECTIDAMTNCON57770.2023.10139338","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139338","url":null,"abstract":"The physiological variables of drinking coconut water compared to plain water (2 ml per kg of body weight) in running mini-marathons $(mathbf{N}=6)$ and half-marathons $(mathbf{N}=6)$. The results show that the average running time and recovery time of the mini-marathon volunteers who drank coconut water were statistically significantly higher than normal water $(mathbf{p} < 0.05)$. For the half-marathon volunteers, drinking coconut water or plain water had no effect on total running time, but drinking coconut water had a significantly greater effect on recovery time after running $(mathbf{p} < 0.05)$, than drinking plain water. In conclusion, drinking coconut water influences the average running time and recovery time of mini-marathon participants, as well as the recovery time of half-marathon participants.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"11 1 Pt 1 1","pages":"524-527"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87971036","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}
Fall risk assessment is an effective and simple measure to evaluate the balance of people especially the elderly who are likely to have balance disorder. Lose of body balance increases a fall risk which could lead to severe damage to aging persons. In this paper, we propose to apply pose estimation technique based on PoseNet method to detect body joints from webcam's video for two types of fall risk assessment: Five Times Sit to Stand Test (FTSTS) and 30-Second Chair Stand Test (30CST). The experiments were performed with 17 volunteers concurrently with the measures of a healthcare expert. The results revealed that our proposed technique corresponds well with the measure of the expert evaluating by a Pearson correlation coefficient which equals to 0.903 and 0.980 for FTSTS and 30CST respectively.
{"title":"Application of Pose Estimation on Webcam for Fall Risk Assessment","authors":"Surapong Uttama, Patsakorn Chumpoo, Worasak Rueangsirarak","doi":"10.1109/ECTIDAMTNCON57770.2023.10139584","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139584","url":null,"abstract":"Fall risk assessment is an effective and simple measure to evaluate the balance of people especially the elderly who are likely to have balance disorder. Lose of body balance increases a fall risk which could lead to severe damage to aging persons. In this paper, we propose to apply pose estimation technique based on PoseNet method to detect body joints from webcam's video for two types of fall risk assessment: Five Times Sit to Stand Test (FTSTS) and 30-Second Chair Stand Test (30CST). The experiments were performed with 17 volunteers concurrently with the measures of a healthcare expert. The results revealed that our proposed technique corresponds well with the measure of the expert evaluating by a Pearson correlation coefficient which equals to 0.903 and 0.980 for FTSTS and 30CST respectively.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"2000 1","pages":"577-580"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88078692","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 : 2023-03-22DOI: 10.1109/ECTIDAMTNCON57770.2023.10139521
Jieyi Yang, Die Hu, E. Kurul, J. Tah, N. Mahat, Somhatai Timsard, Achara Khamaksorn
The increasing need for diverse living environments continues to be driven by rapid economic growth and a significant improvement of people's living standards. As one of the five pillars of an industrial economy, the construction industry has undergone more dynamic development than many other industries. However, construction companies still suffer from many problems, such as knowledge loss, inefficient collaboration, and low competitiveness. These challenges require organisations to systematically manage their knowledge and facilitate collaboration among stakeholders. Knowledge can be shared and developed by means of an effective knowledge transfer system and construction companies can enjoy high returns by collaborating in innovative construction projects, thereby enabling them to acquire a lasting competitive advantage. However, there appears to be a lack of research and analysis of the factors that affect the transfer of knowledge in collaborative and innovative construction projects. Therefore, the aim of this study is to define the related influential factors based on a systematic review of the literature (SRL). A search of the Scopus database from 2013 to 2022 yielded 162 articles, nine of which were selected to address the research problem. The analytical results of the SLR indicate that the key factors that affect the transfer of knowledge and collaboration in innovative architectural projects include the working environment, communication among project members, partners and social capital, talent training, team culture, and leadership, which are also the driving force for the development of these projects.
{"title":"Factors That Affect Knowledge Transfer and Collaborative Innovation in Construction Projects: A Systematic Literature Review","authors":"Jieyi Yang, Die Hu, E. Kurul, J. Tah, N. Mahat, Somhatai Timsard, Achara Khamaksorn","doi":"10.1109/ECTIDAMTNCON57770.2023.10139521","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139521","url":null,"abstract":"The increasing need for diverse living environments continues to be driven by rapid economic growth and a significant improvement of people's living standards. As one of the five pillars of an industrial economy, the construction industry has undergone more dynamic development than many other industries. However, construction companies still suffer from many problems, such as knowledge loss, inefficient collaboration, and low competitiveness. These challenges require organisations to systematically manage their knowledge and facilitate collaboration among stakeholders. Knowledge can be shared and developed by means of an effective knowledge transfer system and construction companies can enjoy high returns by collaborating in innovative construction projects, thereby enabling them to acquire a lasting competitive advantage. However, there appears to be a lack of research and analysis of the factors that affect the transfer of knowledge in collaborative and innovative construction projects. Therefore, the aim of this study is to define the related influential factors based on a systematic review of the literature (SRL). A search of the Scopus database from 2013 to 2022 yielded 162 articles, nine of which were selected to address the research problem. The analytical results of the SLR indicate that the key factors that affect the transfer of knowledge and collaboration in innovative architectural projects include the working environment, communication among project members, partners and social capital, talent training, team culture, and leadership, which are also the driving force for the development of these projects.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"1967 1","pages":"171-176"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91374143","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 : 2023-03-22DOI: 10.1109/ECTIDAMTNCON57770.2023.10139721
S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul
With the onset of technological advancements, biosensors are being effectively used in a variety of contexts, including the diagnosis of diseases, the promotion of their prevention and rehabilitation, the monitoring of patient health, and human activity recognition (HAR). Recently, HAR research results have been obtained and applied in many commercial applications such as fall detection using smart watch sensors, activity classification using smart home sensors. However, previous HAR models utilizing wearable sensors primarily utilized data from healthy individuals, and such models are frequently inaccurate when applied to individuals with medical mobility impairments. In this work, surface electromyography and goniometer sensors were used to categorize various types of rehabilitation activities based on HAR models developed for individuals with knee abnormalities. To achieve the goal of our study, a deep residual network called ResNeXt was proposed to detect human activities with high performance. To investigate the classification performance of deep learning models, a 5-fold cross-validation technique was applied for both training and testing. Based on the results of our study, the combination of features extracted from the goniometer and electromyograph signals resulted in the highest F1-score (93.31%) and the best accuracy (93.52%).
{"title":"Human Activity Recognition for People with Knee Abnormality Using Surface Electromyography and Knee Angle Sensors","authors":"S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul","doi":"10.1109/ECTIDAMTNCON57770.2023.10139721","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139721","url":null,"abstract":"With the onset of technological advancements, biosensors are being effectively used in a variety of contexts, including the diagnosis of diseases, the promotion of their prevention and rehabilitation, the monitoring of patient health, and human activity recognition (HAR). Recently, HAR research results have been obtained and applied in many commercial applications such as fall detection using smart watch sensors, activity classification using smart home sensors. However, previous HAR models utilizing wearable sensors primarily utilized data from healthy individuals, and such models are frequently inaccurate when applied to individuals with medical mobility impairments. In this work, surface electromyography and goniometer sensors were used to categorize various types of rehabilitation activities based on HAR models developed for individuals with knee abnormalities. To achieve the goal of our study, a deep residual network called ResNeXt was proposed to detect human activities with high performance. To investigate the classification performance of deep learning models, a 5-fold cross-validation technique was applied for both training and testing. Based on the results of our study, the combination of features extracted from the goniometer and electromyograph signals resulted in the highest F1-score (93.31%) and the best accuracy (93.52%).","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"31 1","pages":"483-487"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81629505","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 : 2023-03-22DOI: 10.1109/ECTIDAMTNCON57770.2023.10139750
Samphors Eng, K. Chou, Kosorl Thourn, V. Vai, Bunthern Kim, J. Thiriet, H. Yahoui
Several production industries pay increased attention to the fourth industrial revolution on a global scale. Academics are studying potential changes to the workforce's education and skill set as a result of Industry 4.0. To satisfy the needs of the business from the standpoint of Industry 4.0, capacity building of people from national institutions/ universities is crucial. Best practices for curriculum design also cover the technical skills needed for the company's questionnaires. The Institute of Technology of Cambodia (ITC) as part of the project implementation unit under the Erasmus+ project ASEAN Factori 4.0, has been working persistently with European universities to upgrade staff capacity and improve its curriculum. As part of the mission, ITC has done both offline and online surveys to address the needs and skill gap for industrial automation inside manufacturing and processing plants at the regional level. This survey also tries to determine the employment potentiality and demands of working professionals. Moreover, the identification of specialized technology and equipment used in the industry is collected in this study. The result has shown that there is a huge demand for experts that has knowledge in industrial automation and equipment such as Programmable Logic Controller (PLC) which has been addressed and updated in the curricula.
{"title":"A Survey on Industrial Sector Status for Curricula Improvement Linked to Industry 4.0 in Electrical Engineering Program at ITC","authors":"Samphors Eng, K. Chou, Kosorl Thourn, V. Vai, Bunthern Kim, J. Thiriet, H. Yahoui","doi":"10.1109/ECTIDAMTNCON57770.2023.10139750","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139750","url":null,"abstract":"Several production industries pay increased attention to the fourth industrial revolution on a global scale. Academics are studying potential changes to the workforce's education and skill set as a result of Industry 4.0. To satisfy the needs of the business from the standpoint of Industry 4.0, capacity building of people from national institutions/ universities is crucial. Best practices for curriculum design also cover the technical skills needed for the company's questionnaires. The Institute of Technology of Cambodia (ITC) as part of the project implementation unit under the Erasmus+ project ASEAN Factori 4.0, has been working persistently with European universities to upgrade staff capacity and improve its curriculum. As part of the mission, ITC has done both offline and online surveys to address the needs and skill gap for industrial automation inside manufacturing and processing plants at the regional level. This survey also tries to determine the employment potentiality and demands of working professionals. Moreover, the identification of specialized technology and equipment used in the industry is collected in this study. The result has shown that there is a huge demand for experts that has knowledge in industrial automation and equipment such as Programmable Logic Controller (PLC) which has been addressed and updated in the curricula.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"34 4 1","pages":"330-334"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81635493","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 : 2023-03-22DOI: 10.1109/ECTIDAMTNCON57770.2023.10139642
Porntida Kaewkamol, Yingzhuo Chen
Smart hotels have recently been established along with the advancement of digital technology and innovations. Smart hotels are likely to leverage hotel services to increase customer satisfaction especially from the new generation customers. However, the past research focused mostly on the customer satisfaction in traditional hotels. There is still a need for the study about customer satisfaction of smart hotels to expand the understanding of important factors regrading customer satisfaction in smart hotels. Thus, this study aims at exploring the factors towards customer satisfaction for smart hotels. Online review data, from both numerical ratings and textual reviews, for the selected hotel were collected and analysed by using content analysis. The results found six factors that are related to customer satisfaction for smart hotels, which are smart facilities, infrastructure, location, catering facilities, value creation and services.
{"title":"Customer Satisfaction Factors of Smart Hotels based on Customer Reviews in Online Platform","authors":"Porntida Kaewkamol, Yingzhuo Chen","doi":"10.1109/ECTIDAMTNCON57770.2023.10139642","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139642","url":null,"abstract":"Smart hotels have recently been established along with the advancement of digital technology and innovations. Smart hotels are likely to leverage hotel services to increase customer satisfaction especially from the new generation customers. However, the past research focused mostly on the customer satisfaction in traditional hotels. There is still a need for the study about customer satisfaction of smart hotels to expand the understanding of important factors regrading customer satisfaction in smart hotels. Thus, this study aims at exploring the factors towards customer satisfaction for smart hotels. Online review data, from both numerical ratings and textual reviews, for the selected hotel were collected and analysed by using content analysis. The results found six factors that are related to customer satisfaction for smart hotels, which are smart facilities, infrastructure, location, catering facilities, value creation and services.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"16 1","pages":"43-46"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87082814","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 : 2023-03-22DOI: 10.1109/ECTIDAMTNCON57770.2023.10139688
Sirikanya Singcuna, P. Kittisupakorn, D. Banjerdpongchai, Jarukamon Dawkrajai, P. Daskalov, Tsvetelina Georgieva
The “Asean Factori 4.0” project under Erasmus+ programme CBHE supported the PLC training and benchmark to the Center of Excellence in Intelligent Control Automation of Process Systems (ICAPS) at Chulalongkorn University (CU). Various PLC projects including PID-type feedback control loop that would be utilized as an in-class tool to enhance understanding of PID principle and effects of tuning parameters on the process was programmed using the CODESYS software with Visualization. The PLC projects were executed on the PLC benchmark with visualization on an HMI display designed by the GALILEO software. The curriculum modification to include Industry 4.0 (I4.0) and PLC as well as conducting seminars on PLC by ICAPS guarantees sustainability of the “Asean Factori 4.0” project.
{"title":"Implementing PID Control on PLC Benchmark to Enhance Industrial Automation Skills Towards ASEAN FACTORI 4.0","authors":"Sirikanya Singcuna, P. Kittisupakorn, D. Banjerdpongchai, Jarukamon Dawkrajai, P. Daskalov, Tsvetelina Georgieva","doi":"10.1109/ECTIDAMTNCON57770.2023.10139688","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139688","url":null,"abstract":"The “Asean Factori 4.0” project under Erasmus+ programme CBHE supported the PLC training and benchmark to the Center of Excellence in Intelligent Control Automation of Process Systems (ICAPS) at Chulalongkorn University (CU). Various PLC projects including PID-type feedback control loop that would be utilized as an in-class tool to enhance understanding of PID principle and effects of tuning parameters on the process was programmed using the CODESYS software with Visualization. The PLC projects were executed on the PLC benchmark with visualization on an HMI display designed by the GALILEO software. The curriculum modification to include Industry 4.0 (I4.0) and PLC as well as conducting seminars on PLC by ICAPS guarantees sustainability of the “Asean Factori 4.0” project.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"20 1","pages":"409-414"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89724630","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 : 2023-03-22DOI: 10.1109/ECTIDAMTNCON57770.2023.10139617
Nattaphit Jengsriwong, Suppakarn Chansareewittaya
In this paper, the real practical tests of applied LoRaWAN are presented. The esp32 with LoRaWAN is used as the mainboard. The used RSSI signal strength unit is dB. The cases of testing include indoor and outdoor. Moreover, indoor testing combines both single-stair and multi-stair. The horizontal and diagonal directions are included, too. After that, the GPS module is attached to this mainboard for sending the location of the testing board via LoRaWan. The final testing shows the long distance. The longest distance signal testing is 5.67 km. The benefit of this testing is to develop for more distance and apply to any application. The final product of the developed GPS tracker can be used in various applications such as tracking lost children of the lost vehicle in the future.
{"title":"LoRaWAN GPS Tracker","authors":"Nattaphit Jengsriwong, Suppakarn Chansareewittaya","doi":"10.1109/ECTIDAMTNCON57770.2023.10139617","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139617","url":null,"abstract":"In this paper, the real practical tests of applied LoRaWAN are presented. The esp32 with LoRaWAN is used as the mainboard. The used RSSI signal strength unit is dB. The cases of testing include indoor and outdoor. Moreover, indoor testing combines both single-stair and multi-stair. The horizontal and diagonal directions are included, too. After that, the GPS module is attached to this mainboard for sending the location of the testing board via LoRaWan. The final testing shows the long distance. The longest distance signal testing is 5.67 km. The benefit of this testing is to develop for more distance and apply to any application. The final product of the developed GPS tracker can be used in various applications such as tracking lost children of the lost vehicle in the future.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"1 1","pages":"199-202"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81714569","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 : 2023-03-22DOI: 10.1109/ECTIDAMTNCON57770.2023.10139540
Vojtech Blazek, L. Prokop, S. Mišák, Pavel Kedroň, Ivo Pergl
This article presents optimisation tools for optimising electric consumption in household microgrid environments with Vehicle To Grid (V2G) technology. Optimalisation tools are based on a Non-dominated sorting genetic algorithm II (NSGA-2). Furthermore, this article describes the digitalised digital twin of the physical microgrid. The physical microgrid simulates a typical Czech household whose primary stochastic energy source is a photovoltaic plant (PV). Microgrid works off-grid. The study's results showed a positive impact on optimising potential electrical self-sufficiency in the microgrid in the conditions of Central Europe. The optimization results most efficiently under tariff mode with electric vehicles (EV). The worst results are achieved in the microgrid, where optimisation is disabled, but tariff mode is activated. This article has served as an initial study of whether it Is worthwhile to use this optimisation.
{"title":"Impact of Energy Consumption Optimisation on the Electrical Self-Sufficiency of a Microgrid with Vehicle-to-Grid Technology","authors":"Vojtech Blazek, L. Prokop, S. Mišák, Pavel Kedroň, Ivo Pergl","doi":"10.1109/ECTIDAMTNCON57770.2023.10139540","DOIUrl":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139540","url":null,"abstract":"This article presents optimisation tools for optimising electric consumption in household microgrid environments with Vehicle To Grid (V2G) technology. Optimalisation tools are based on a Non-dominated sorting genetic algorithm II (NSGA-2). Furthermore, this article describes the digitalised digital twin of the physical microgrid. The physical microgrid simulates a typical Czech household whose primary stochastic energy source is a photovoltaic plant (PV). Microgrid works off-grid. The study's results showed a positive impact on optimising potential electrical self-sufficiency in the microgrid in the conditions of Central Europe. The optimization results most efficiently under tariff mode with electric vehicles (EV). The worst results are achieved in the microgrid, where optimisation is disabled, but tariff mode is activated. This article has served as an initial study of whether it Is worthwhile to use this optimisation.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"30 1","pages":"279-283"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89631225","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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