Pub Date : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587681
Aman Hebbale, Ghr Vinay, Bvn Vamsi Krishna, Jalpa S. Shah
Diabetes is a chronic disease caused by the assimilation of blood sugar, mainly because of reduced production or no production of insulin within the body (type 1 diabetes), or because cells are irresponsive to the produced insulin (type 2 diabetes). In recent years, a multitude of people turned out to be diabetic and is increasing drastically. Moreover, a report by World Health Organization describes 346 million people are affected by diabetes around the world. Furthermore, the lack of a self-care system for monitoring and detecting signs at an early stage in the patient’s data causes pre-diabetes or diabetes condition which remains unrevealed in more than one-third of the population and later diagnosed with diabetes. The combination of machine learning techniques and the Internet of Things can provide an effective solution to predict diabetes well before. Therefore, this paper presents an Internet of Things (IoT) and Machine Learning-based non-invasive self-care system which monitors blood sugar and various vital parameters to predict diabetes well before. The non-invasive way of measuring blood sugar through a developed IoT sensor is much more comfortable compared to the invasive method. In the proposed system deployment of the SVM-based machine learning model on the cloud and its integration with the android application enables doctors and patients to monitor the vital parameters and associated risk easily. In addition to this, monitored parameters are sent to the doctor through email for further analysis, and suggestions in diet and lifestyle based on the monitored parameters are conveyed to the patient through an android application to prevent or reduce the risk of diabetes. Thus, the proposed self-care system can overcome challenges of the traditional way of monitoring diabetes and helps patient and doctor in monitoring, recording, and analyzing data for the prognosis of diabetes.
{"title":"IoT and Machine Learning based Self Care System for Diabetes Monitoring and Prediction","authors":"Aman Hebbale, Ghr Vinay, Bvn Vamsi Krishna, Jalpa S. Shah","doi":"10.1109/GCAT52182.2021.9587681","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587681","url":null,"abstract":"Diabetes is a chronic disease caused by the assimilation of blood sugar, mainly because of reduced production or no production of insulin within the body (type 1 diabetes), or because cells are irresponsive to the produced insulin (type 2 diabetes). In recent years, a multitude of people turned out to be diabetic and is increasing drastically. Moreover, a report by World Health Organization describes 346 million people are affected by diabetes around the world. Furthermore, the lack of a self-care system for monitoring and detecting signs at an early stage in the patient’s data causes pre-diabetes or diabetes condition which remains unrevealed in more than one-third of the population and later diagnosed with diabetes. The combination of machine learning techniques and the Internet of Things can provide an effective solution to predict diabetes well before. Therefore, this paper presents an Internet of Things (IoT) and Machine Learning-based non-invasive self-care system which monitors blood sugar and various vital parameters to predict diabetes well before. The non-invasive way of measuring blood sugar through a developed IoT sensor is much more comfortable compared to the invasive method. In the proposed system deployment of the SVM-based machine learning model on the cloud and its integration with the android application enables doctors and patients to monitor the vital parameters and associated risk easily. In addition to this, monitored parameters are sent to the doctor through email for further analysis, and suggestions in diet and lifestyle based on the monitored parameters are conveyed to the patient through an android application to prevent or reduce the risk of diabetes. Thus, the proposed self-care system can overcome challenges of the traditional way of monitoring diabetes and helps patient and doctor in monitoring, recording, and analyzing data for the prognosis of diabetes.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128913382","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 : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587827
S. Saha, S. Biswas
DVRs commonly use PI controllers. In spite of the fact that the required Proportional Integral controller does not alone provide the output, by using gains which are fixed when there is a variations in the operating conditions or system parameters. This problem is solved by an adaptive Proportional integral with fuzzy logic. The fuzzy controller will adjust the error and rate of error of the Proportional Integral controller according to respective readings and fuzzy control rules, in order to get adjusted to any operating conditions variations. The corresponding results of simulation proved that the method of adaptive Proportional Integral with fuzzy logic control considerably improves the DVR performance as compared to the normal Proportional Integral controller.
{"title":"Fuzzy Logic and PI Controller Implementation on Dynamic Voltage Restorer","authors":"S. Saha, S. Biswas","doi":"10.1109/GCAT52182.2021.9587827","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587827","url":null,"abstract":"DVRs commonly use PI controllers. In spite of the fact that the required Proportional Integral controller does not alone provide the output, by using gains which are fixed when there is a variations in the operating conditions or system parameters. This problem is solved by an adaptive Proportional integral with fuzzy logic. The fuzzy controller will adjust the error and rate of error of the Proportional Integral controller according to respective readings and fuzzy control rules, in order to get adjusted to any operating conditions variations. The corresponding results of simulation proved that the method of adaptive Proportional Integral with fuzzy logic control considerably improves the DVR performance as compared to the normal Proportional Integral controller.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129334475","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 : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587833
Manali K. Gawande, Shriya G. Ghulaxe, Tanvi R. Mahatme, A. Salvi, M. Bagewadi
Solar power became an increasingly popular as a source of renewable energy since past decade. The maximum power point tracking (MPPT) is easy and efficient algorithm used for Power tracking during the abundant availability of sunlight and at high temperature. However this might not be the case during weather intermittency. Sudden change in weather conditions cause sudden change in irradiance and gradual change in temperature can impact on the Power tracking capability of converter because of some constraints in the MPPT algorithm used. Study shows that during such variable weather conditions if large disturbance occurs in the power system, PV plants without LVRT capability may probably trip themselves from the grid. As the solar PV system has non-linear characteristics because of weather variations, it is important to use appropriate MPPT technique which can effectively track MPPT at sudden variation to improve overall efficiency of the PV panel. Here in the paper we proposed and analysed one of the new hybrid MPPT method which is - PSO-INC hybridised MPPT Method on solar panel of 300W. Through this we will see the steps that involved during the development of this new MPPT algorithm its simulation results
{"title":"Modern approach for hybridization of PSO-INC MPPT methods for efficient solar power tracking","authors":"Manali K. Gawande, Shriya G. Ghulaxe, Tanvi R. Mahatme, A. Salvi, M. Bagewadi","doi":"10.1109/GCAT52182.2021.9587833","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587833","url":null,"abstract":"Solar power became an increasingly popular as a source of renewable energy since past decade. The maximum power point tracking (MPPT) is easy and efficient algorithm used for Power tracking during the abundant availability of sunlight and at high temperature. However this might not be the case during weather intermittency. Sudden change in weather conditions cause sudden change in irradiance and gradual change in temperature can impact on the Power tracking capability of converter because of some constraints in the MPPT algorithm used. Study shows that during such variable weather conditions if large disturbance occurs in the power system, PV plants without LVRT capability may probably trip themselves from the grid. As the solar PV system has non-linear characteristics because of weather variations, it is important to use appropriate MPPT technique which can effectively track MPPT at sudden variation to improve overall efficiency of the PV panel. Here in the paper we proposed and analysed one of the new hybrid MPPT method which is - PSO-INC hybridised MPPT Method on solar panel of 300W. Through this we will see the steps that involved during the development of this new MPPT algorithm its simulation results","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129428415","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 : 2021-10-01DOI: 10.1109/gcat52182.2021.9587874
{"title":"Speakers [biographies only]","authors":"","doi":"10.1109/gcat52182.2021.9587874","DOIUrl":"https://doi.org/10.1109/gcat52182.2021.9587874","url":null,"abstract":"","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126897342","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 : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587809
Prasidha Prabhu, Harshini Ramaswamy, K. Nirmala
The advent of radiological methods in medical imaging has bestowed upon the healthcare industry a wide range of advantages such as increased speed and accuracy in clinical diagnoses, early prediction of the onset of diseases, and has also aided in the treatment of several health complications. A primary advancement in this field of medical imaging is Computed Tomography (CT), an imaging technique that has allowed us to view image slices from various organs, muscles, and soft tissues, in a three-dimensional perspective. Through the years CT has proved to be an indispensable aspect of medical imaging, and has gone through several technical advancements. While CT scans are one of the most preferred methods employed in medical imaging, they pose an imminent risk of the development of several health complications. These health complications arise due to the exposure of radiation, which is in marginally larger amounts than other imaging modalities. The trade-off between the dosage of radiation and the proportional image quality presents a medical challenge that needs to be solved. This problem can only be solved through post-scan enhancements of the reconstruction techniques employed to obtain the CT image. This paper delineates the popular back projection techniques, and presents a first-of-its-kind, quantitative comparison of the various shaping filters that can potentially enhance the CT image quality.
{"title":"A Quantitative Study on Shaping Filters in Computed Tomography Image Reconstruction","authors":"Prasidha Prabhu, Harshini Ramaswamy, K. Nirmala","doi":"10.1109/GCAT52182.2021.9587809","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587809","url":null,"abstract":"The advent of radiological methods in medical imaging has bestowed upon the healthcare industry a wide range of advantages such as increased speed and accuracy in clinical diagnoses, early prediction of the onset of diseases, and has also aided in the treatment of several health complications. A primary advancement in this field of medical imaging is Computed Tomography (CT), an imaging technique that has allowed us to view image slices from various organs, muscles, and soft tissues, in a three-dimensional perspective. Through the years CT has proved to be an indispensable aspect of medical imaging, and has gone through several technical advancements. While CT scans are one of the most preferred methods employed in medical imaging, they pose an imminent risk of the development of several health complications. These health complications arise due to the exposure of radiation, which is in marginally larger amounts than other imaging modalities. The trade-off between the dosage of radiation and the proportional image quality presents a medical challenge that needs to be solved. This problem can only be solved through post-scan enhancements of the reconstruction techniques employed to obtain the CT image. This paper delineates the popular back projection techniques, and presents a first-of-its-kind, quantitative comparison of the various shaping filters that can potentially enhance the CT image quality.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129186819","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 : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587458
Saurabh. V. Parhad, Shivai Ashok Aher, K. Warhade
The synthetic aperture radar images have a granular disturbance noise know as Speckle. The speckle is also called as a multiplicative noise. Over last few decades, various filters like lee, frost, wiener, mean and median filters are used and claimed to be efficient to reduce this granular noise present in SAR images. This process of removing speckles is also known as despeckling. The aim of this paper is to make a comparative review of despeckling methods. These methods will be used to highlight the trends and many approaches which changed over the years. This paper has discussed the technical aspects of the different filters and summarized it to use to remove the speckle in SAR images. Quantitative and qualitative parameters like mean, variance, edge saving index in horizontal & vertical, target to clutter ratio, equivalent number of looks have been analyzed and it concludes a method which uses different window sizes to reduce speckle in SAR images, which has efficient noise removal capabilities as compared with traditional methods like adaptive and non-adaptive filtering. It can extends to use of various machine learning algorithms to optimize the result towards betterment of different performance parameters.
{"title":"A Comparative Analysis of Speckle Noise Removal in SAR Images","authors":"Saurabh. V. Parhad, Shivai Ashok Aher, K. Warhade","doi":"10.1109/GCAT52182.2021.9587458","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587458","url":null,"abstract":"The synthetic aperture radar images have a granular disturbance noise know as Speckle. The speckle is also called as a multiplicative noise. Over last few decades, various filters like lee, frost, wiener, mean and median filters are used and claimed to be efficient to reduce this granular noise present in SAR images. This process of removing speckles is also known as despeckling. The aim of this paper is to make a comparative review of despeckling methods. These methods will be used to highlight the trends and many approaches which changed over the years. This paper has discussed the technical aspects of the different filters and summarized it to use to remove the speckle in SAR images. Quantitative and qualitative parameters like mean, variance, edge saving index in horizontal & vertical, target to clutter ratio, equivalent number of looks have been analyzed and it concludes a method which uses different window sizes to reduce speckle in SAR images, which has efficient noise removal capabilities as compared with traditional methods like adaptive and non-adaptive filtering. It can extends to use of various machine learning algorithms to optimize the result towards betterment of different performance parameters.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124447462","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 : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587532
Shivansh Gautam, S. Agrawal
Three phase Shunt Active Power Filters (SAPF) are widely used to inject required amount of compensating current to eliminate current harmonics generated by Non-Linear Loads (NLL) and restore sinusoidal waveform of the supply. This paper analyze the development of a three phase grid connected PV array generating a P&O algorithm based MPPT tracked DC power, converted to AC power by PLL controlled VSI supplying a NLL connected with SAPF constituting of series inductor, ANN based self-supported DC link capacitor connected to IGBT based Current controlled VSI compensating for load induced current harmonics in the line. The developed SAPF works on instantaneous active and reactive power measurements to calculate the reference current for the HBCC to produce the gate pulse for the inverter. The proposed model is developed in MATLAB 17a Simulink and Levenberg Marquardt training algorithm based ANN is implemented to regulate DC link capacitor voltage. Simulated results approves the proposed control technique for a fast and flexible dynamic response of the solar to three phase compensated grid system and Total Harmonic Distortion of supply current is found to be satisfactory as per the IEEE-519 standards.
{"title":"Performance Analysis of Three Phase Grid Connected PV Array with ANN Controlled SAPF","authors":"Shivansh Gautam, S. Agrawal","doi":"10.1109/GCAT52182.2021.9587532","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587532","url":null,"abstract":"Three phase Shunt Active Power Filters (SAPF) are widely used to inject required amount of compensating current to eliminate current harmonics generated by Non-Linear Loads (NLL) and restore sinusoidal waveform of the supply. This paper analyze the development of a three phase grid connected PV array generating a P&O algorithm based MPPT tracked DC power, converted to AC power by PLL controlled VSI supplying a NLL connected with SAPF constituting of series inductor, ANN based self-supported DC link capacitor connected to IGBT based Current controlled VSI compensating for load induced current harmonics in the line. The developed SAPF works on instantaneous active and reactive power measurements to calculate the reference current for the HBCC to produce the gate pulse for the inverter. The proposed model is developed in MATLAB 17a Simulink and Levenberg Marquardt training algorithm based ANN is implemented to regulate DC link capacitor voltage. Simulated results approves the proposed control technique for a fast and flexible dynamic response of the solar to three phase compensated grid system and Total Harmonic Distortion of supply current is found to be satisfactory as per the IEEE-519 standards.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125647650","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 : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587459
Niraj Kumar, R. Suman, Sanjay Kumar
Text classification and Topic Modelling is the backbone for the text analysis of huge amount of corpus of data. With an increase in unstructured data around us, it is very difficult to analyse the data very easily. There is a need for some methods that can be applied to the data to get the sensitive and semantic information from the corpus. Text classification is categorization of text in organised way for the interpretation of sensitive information from the text, while Topic modelling is finding the abstract topic for the collection of text or document. Topic modelling is used frequently to find semantic information from the textual data. In this paper we applied Parsing techniques on various websites to extract the HTML and XML data which includes the textual data and also applied Preprocessing techniques to clean the data. For the text classification purpose some of the Machine learning based classifiers that we have used in our experiment are Naive Bayes and also Logistic Regression Classifier. The models of the document are built using three different topic modelling methods which are Latent Semantic Analysis, Probabilistic Latent Semantic Analysis and Latent Dirichlet Allocation. In the further experiment we have done analysis and also comparison based upon the performance of the models and classifiers on the processed textual data.
{"title":"Text Classification and Topic Modelling of Web Extracted Data","authors":"Niraj Kumar, R. Suman, Sanjay Kumar","doi":"10.1109/GCAT52182.2021.9587459","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587459","url":null,"abstract":"Text classification and Topic Modelling is the backbone for the text analysis of huge amount of corpus of data. With an increase in unstructured data around us, it is very difficult to analyse the data very easily. There is a need for some methods that can be applied to the data to get the sensitive and semantic information from the corpus. Text classification is categorization of text in organised way for the interpretation of sensitive information from the text, while Topic modelling is finding the abstract topic for the collection of text or document. Topic modelling is used frequently to find semantic information from the textual data. In this paper we applied Parsing techniques on various websites to extract the HTML and XML data which includes the textual data and also applied Preprocessing techniques to clean the data. For the text classification purpose some of the Machine learning based classifiers that we have used in our experiment are Naive Bayes and also Logistic Regression Classifier. The models of the document are built using three different topic modelling methods which are Latent Semantic Analysis, Probabilistic Latent Semantic Analysis and Latent Dirichlet Allocation. In the further experiment we have done analysis and also comparison based upon the performance of the models and classifiers on the processed textual data.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125951728","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 : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587482
Manish Shinde, Ruturaj Chintawar, R. Chavan, Bhavesh Chatnani, Dr. Mrs. Nupur Giri
This paper introduces application of Multi Agent Deep Deterministic Policy Gradients algorithm for multiple traffic intersection problems. The problem of decrease in waiting time at traffic intersections is still unsolved. Reinforcement learning is the recent technique which was introduced in past years. This paper is an attempt to apply Reinforcement Learning for multiple intersections.
{"title":"Multiple Intersection Traffic Control using Reinforcement Learning","authors":"Manish Shinde, Ruturaj Chintawar, R. Chavan, Bhavesh Chatnani, Dr. Mrs. Nupur Giri","doi":"10.1109/GCAT52182.2021.9587482","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587482","url":null,"abstract":"This paper introduces application of Multi Agent Deep Deterministic Policy Gradients algorithm for multiple traffic intersection problems. The problem of decrease in waiting time at traffic intersections is still unsolved. Reinforcement learning is the recent technique which was introduced in past years. This paper is an attempt to apply Reinforcement Learning for multiple intersections.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134059580","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}
In 5G mobile communication systems, mm wave communication has become one of the most attractive techniques reason being a huge increase in wireless data traffic. Also, the mobile terminals have become thinner and in functionality, more versatile and continue to become more. A mobile terminal, nowadays consists 2G-4G antennas, NFC antennas, Wi-Fi antennas, and now 5G antennas as well. Thus, compact antenna arrays are required and are a very hot topic today for future mobiles. optimization technique has been used in this paper since it includes the searching and obtaining of the perfect solution possible for a given problem. In this project we’ve first proposed a rectangular patch antenna of size 3.237 mm $times 2.8$ mm $times 0.5$ mm with which a $1times 4$ antenna array has been designed of the dimensions 9.787 mm $times 34.76$ mm $times 0.5$ mm. This $1times 4$ antenna array was optimized using Particle Swarm optimization (PSO) and the parameters have been analysed and discussed. Dimensions are 13.237 mm $times$ 47.76 mm $times 0.5$ mm.
在5G移动通信系统中，毫米波通信已成为最具吸引力的技术之一，原因是无线数据流量的巨大增长。此外，移动终端已经变得更薄，在功能上，更多功能，并继续变得更多。一个移动终端，现在包括2G-4G天线、NFC天线、Wi-Fi天线，现在还有5G天线。因此，紧凑的天线阵列是必需的，并且是当今未来移动设备的一个非常热门的话题。本文采用了优化技术，因为它包括对给定问题的可能的完美解的搜索和获得。在本项目中，我们首先提出了尺寸为3.237 mm × 2.8 mm × 0.5 mm的矩形贴片天线，并设计了尺寸为9.787 mm × 34.76 mm × 0.5 mm的1 × 4$天线阵列，并利用粒子群算法对该天线阵列进行了优化，并对参数进行了分析和讨论。尺寸为13.237 mm × 47.76 mm × 0.5 mm。
{"title":"Design and Optimization of an Antenna Array for future 5G Applications using PSO Algorithm","authors":"Prashant Babbar, Sanjeev Saxena, Shubham Mishra, Asmita Rajawat","doi":"10.1109/GCAT52182.2021.9587552","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587552","url":null,"abstract":"In 5G mobile communication systems, mm wave communication has become one of the most attractive techniques reason being a huge increase in wireless data traffic. Also, the mobile terminals have become thinner and in functionality, more versatile and continue to become more. A mobile terminal, nowadays consists 2G-4G antennas, NFC antennas, Wi-Fi antennas, and now 5G antennas as well. Thus, compact antenna arrays are required and are a very hot topic today for future mobiles. optimization technique has been used in this paper since it includes the searching and obtaining of the perfect solution possible for a given problem. In this project we’ve first proposed a rectangular patch antenna of size 3.237 mm $times 2.8$ mm $times 0.5$ mm with which a $1times 4$ antenna array has been designed of the dimensions 9.787 mm $times 34.76$ mm $times 0.5$ mm. This $1times 4$ antenna array was optimized using Particle Swarm optimization (PSO) and the parameters have been analysed and discussed. Dimensions are 13.237 mm $times$ 47.76 mm $times 0.5$ mm.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132958493","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：