Pub Date : 2022-05-06DOI: 10.1109/PCEMS55161.2022.9807986
Shivam Gorbade, R. Shrivastava, Ankit A. Bhurane
With the advent of technology and growing demand for energy-efficient technology in wireless communication, there is a need to ponder over the Security aspect of the Wireless Ambient system. In this paper, we have done an Analysis of Physical Layer Security for Ambient Backscatter Communication having Multiple Tags and Mobile sources using Performance Analysis based on Secrecy Outage Probability. More specifically we have derived an equation for SOP considering source mobile and plotted results with varying relative speed and the number of tags.
{"title":"Physical Layer Security Analysis in Ambient Backscatter Communication With Source and Reader Mobility","authors":"Shivam Gorbade, R. Shrivastava, Ankit A. Bhurane","doi":"10.1109/PCEMS55161.2022.9807986","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9807986","url":null,"abstract":"With the advent of technology and growing demand for energy-efficient technology in wireless communication, there is a need to ponder over the Security aspect of the Wireless Ambient system. In this paper, we have done an Analysis of Physical Layer Security for Ambient Backscatter Communication having Multiple Tags and Mobile sources using Performance Analysis based on Secrecy Outage Probability. More specifically we have derived an equation for SOP considering source mobile and plotted results with varying relative speed and the number of tags.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114556885","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 : 2022-05-06DOI: 10.1109/PCEMS55161.2022.9808052
Rajesh Nagula, Kushagra Srivastava, K. Surender
Sensor Fusion deals with the amalgamation of multiple sensor data to provide a steady and reliable estimate of the pose: position and orientation of the system, generally a robot, relative to its environment. A good strategy for extracting sensor data and minimizing errors from the sensor needs to be adopted to address this challenge. Many algorithms have been employed to improve and solve this problem in recent times. Despite the tremendous expansion of work in this domain, a precise compilation and comparison of various methodologies have remained an unexplored subject. This paper presents the current state-of-the-art multi-sensor fusion methods, with a significant focus on partially Global Navigation Satellite System (GNSS) dependent techniques. We have investigated works with various architecture and classified them into two major categories: Loosely-coupled and Tightly-coupled. These methods are further differentiated based on the optimization used for minimizing error.
{"title":"An Overview of Multi-Sensor Fusion Methods with Partial Reliance on GNSS","authors":"Rajesh Nagula, Kushagra Srivastava, K. Surender","doi":"10.1109/PCEMS55161.2022.9808052","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9808052","url":null,"abstract":"Sensor Fusion deals with the amalgamation of multiple sensor data to provide a steady and reliable estimate of the pose: position and orientation of the system, generally a robot, relative to its environment. A good strategy for extracting sensor data and minimizing errors from the sensor needs to be adopted to address this challenge. Many algorithms have been employed to improve and solve this problem in recent times. Despite the tremendous expansion of work in this domain, a precise compilation and comparison of various methodologies have remained an unexplored subject. This paper presents the current state-of-the-art multi-sensor fusion methods, with a significant focus on partially Global Navigation Satellite System (GNSS) dependent techniques. We have investigated works with various architecture and classified them into two major categories: Loosely-coupled and Tightly-coupled. These methods are further differentiated based on the optimization used for minimizing error.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"9 18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131662121","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 : 2022-05-06DOI: 10.1109/PCEMS55161.2022.9808051
Anish Kumar Vishwakarma, K. Bhurchandi
Forecast video quality in the absence of a reference video is a difficult task. This paper proposes a novel method for evaluating the quality of videos using the Radon transform. We propose fractal analysis of Radon coefficients to determine the video quality in the absence of reference data. Fractal analysis is a mathematical technique for characterizing the properties of objects that have an irregular or complex structure. It is used to extract the structural changes that occur in video frames as a result of various distortions. Additionally, a support vector regression model is used to predict the quality score of the video. Three widely used and publicly available video quality databases are used to validate the proposed NR-VQA model. In terms of quality prediction performance, the proposed model outperforms the majority of existing state-of-the-art methods.
{"title":"Fractal Analysis of Radon Coefficients for No-Reference Video Quality Assessment (NR-VQA)","authors":"Anish Kumar Vishwakarma, K. Bhurchandi","doi":"10.1109/PCEMS55161.2022.9808051","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9808051","url":null,"abstract":"Forecast video quality in the absence of a reference video is a difficult task. This paper proposes a novel method for evaluating the quality of videos using the Radon transform. We propose fractal analysis of Radon coefficients to determine the video quality in the absence of reference data. Fractal analysis is a mathematical technique for characterizing the properties of objects that have an irregular or complex structure. It is used to extract the structural changes that occur in video frames as a result of various distortions. Additionally, a support vector regression model is used to predict the quality score of the video. Three widely used and publicly available video quality databases are used to validate the proposed NR-VQA model. In terms of quality prediction performance, the proposed model outperforms the majority of existing state-of-the-art methods.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122568751","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 : 2022-05-06DOI: 10.1109/PCEMS55161.2022.9807974
S. Khobragade, Akshata Kinage, Divyanshu Shambharkar, Abhay Gandhi
Autonomous vehicles, these days have been gaining a lot of interest and it seems to promise a safer, more reliable world. Autonomous cars on one hand have bloomed into commercial production, but on the other hand, autonomous trains in particular have not yet been in the limelight. The paper builds around the premise that in unmanned railway technology, perceiving the driving environment in front of the train and identifying the potential safety threats are critical issues. In response, we propose a way based on computer vision to detect the railway tracks in real-time which can be used for safety and automation purposes. Followed by anomaly detection using deep learning based object detection algorithm. We experimentally show that track extracted has good continuity and low noise, and the probable obstacles also get appropriately detected.
{"title":"Real-time Track and Anomaly Detection in Complex Railway Environment","authors":"S. Khobragade, Akshata Kinage, Divyanshu Shambharkar, Abhay Gandhi","doi":"10.1109/PCEMS55161.2022.9807974","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9807974","url":null,"abstract":"Autonomous vehicles, these days have been gaining a lot of interest and it seems to promise a safer, more reliable world. Autonomous cars on one hand have bloomed into commercial production, but on the other hand, autonomous trains in particular have not yet been in the limelight. The paper builds around the premise that in unmanned railway technology, perceiving the driving environment in front of the train and identifying the potential safety threats are critical issues. In response, we propose a way based on computer vision to detect the railway tracks in real-time which can be used for safety and automation purposes. Followed by anomaly detection using deep learning based object detection algorithm. We experimentally show that track extracted has good continuity and low noise, and the probable obstacles also get appropriately detected.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114284481","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 : 2022-05-06DOI: 10.1109/PCEMS55161.2022.9807988
Jillella Sai Charan Reddy, C. Venkatesh, S. Sinha, S. Mazumdar
Colorectal cancer is a form of cancer that has its incidence all over the globe. It starts in the colon as a group of cells growing on the inner wall; these are called polyps. Not all polyps are cancerous, but they should be identified and removed. The detection of polyps during colonoscopy may be susceptible to human errors. Missed polyps due to human errors can lead to colorectal cancer. Advancements in the field of artificial intelligence brought revolutionary changes in several fields. A computerized algorithm that guides doctors can be a better option for reducing human error. For this purpose we have implemented a tracking by detection model which helps doctors during screening process. For detection of polyps we have trained our detection algorithm using YOLO-v4. For training we have used 1705 polyp images taken from various databases. For tracking polyps we have implemented DeepSORT algorithm. To evaluate the model, we have tested it on 2 colonoscopy videos acquired from hospitals. Performance of the model on these two videos is evaluated by computing two metrics Multiple Object Tracking Accuracy(MOTA) and Multiple Object Tracking Precision(MOTP). Our model is able to track polyps and promising results were obtained.
{"title":"Real time Automatic Polyp Detection in White light Endoscopy videos using a combination of YOLO and DeepSORT","authors":"Jillella Sai Charan Reddy, C. Venkatesh, S. Sinha, S. Mazumdar","doi":"10.1109/PCEMS55161.2022.9807988","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9807988","url":null,"abstract":"Colorectal cancer is a form of cancer that has its incidence all over the globe. It starts in the colon as a group of cells growing on the inner wall; these are called polyps. Not all polyps are cancerous, but they should be identified and removed. The detection of polyps during colonoscopy may be susceptible to human errors. Missed polyps due to human errors can lead to colorectal cancer. Advancements in the field of artificial intelligence brought revolutionary changes in several fields. A computerized algorithm that guides doctors can be a better option for reducing human error. For this purpose we have implemented a tracking by detection model which helps doctors during screening process. For detection of polyps we have trained our detection algorithm using YOLO-v4. For training we have used 1705 polyp images taken from various databases. For tracking polyps we have implemented DeepSORT algorithm. To evaluate the model, we have tested it on 2 colonoscopy videos acquired from hospitals. Performance of the model on these two videos is evaluated by computing two metrics Multiple Object Tracking Accuracy(MOTA) and Multiple Object Tracking Precision(MOTP). Our model is able to track polyps and promising results were obtained.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125592009","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}
Skin diseases are very common and the diagnosis is tricky and challenging. Latest research in the field of medicine along with the help of advanced technology has proved to be quite useful not only in diagnosis but also for treatment. Application of deep learning methods for diagnosis of skin diseases has given remarkable results. Computer aided results are quick and provide a quick overview of the disease.This paper aims to diagnose the skin disease from the infected skin image captured and provide details of the disease and recommend medication. To achieve this we have used stateof-the-art convolutional neural network(CNN) architecture MobileNetV2 for model building and training.This is particularly helpful for both doctors and individuals to analyze the disease. For doctors, they can validate their opinion with this prediction and individuals can have an idea of the disease at the beginning itself and can be helpful to prevent the disease further since prevention is always better than cure.
{"title":"A Deep Learning Model that Diagnosis Skin Diseases and Recommends Medication","authors":"Rayan Shaik, Sai Krishna Bodhapati, Abhiram Uddandam, Lokesh Krupal, Joydeep Sengupta","doi":"10.1109/PCEMS55161.2022.9808065","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9808065","url":null,"abstract":"Skin diseases are very common and the diagnosis is tricky and challenging. Latest research in the field of medicine along with the help of advanced technology has proved to be quite useful not only in diagnosis but also for treatment. Application of deep learning methods for diagnosis of skin diseases has given remarkable results. Computer aided results are quick and provide a quick overview of the disease.This paper aims to diagnose the skin disease from the infected skin image captured and provide details of the disease and recommend medication. To achieve this we have used stateof-the-art convolutional neural network(CNN) architecture MobileNetV2 for model building and training.This is particularly helpful for both doctors and individuals to analyze the disease. For doctors, they can validate their opinion with this prediction and individuals can have an idea of the disease at the beginning itself and can be helpful to prevent the disease further since prevention is always better than cure.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132300277","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 : 2022-05-06DOI: 10.1109/PCEMS55161.2022.9807870
Satyam Upadhyay, Gunjan Vyas, Devraj Singh, S. Jindal
In most of the universities, hostel mess has a different menu for each week or day, which not only wastes paper but is also difficult for students to remember. It would be great if users get a menu whenever in need on their mobile phone and help them decide whether to have their meals in a mess or college cafe. So, to overcome such situations, this daily problem can be solved, using GSM and 8051 microcontroller to know the menu, just like a bot on an IRCTC’s or any other website does, which helps by searching a specific keyword to help out with consumers problems. Similarly, a keyword like “menu” can be sent as an SMS to GSM which will act as an input to the microcontroller and according to that specific day and time it will process the menu and give the output to the GSM which will be sent to the user’s mobile phone as an SMS, so in-short GSM will act as an interface for handling messaging service. By this, students can know their offered meal anytime anywhere and can respond by texting “yes” to make a plate for them. If a student does not respond “yes” then his/her portion of food will be reduced in the mess pantry while preparing the meal. Therefore, this will limit food wastage as well.
{"title":"Food Menu on mobile phone using GSM AND 8051 Microcontroller","authors":"Satyam Upadhyay, Gunjan Vyas, Devraj Singh, S. Jindal","doi":"10.1109/PCEMS55161.2022.9807870","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9807870","url":null,"abstract":"In most of the universities, hostel mess has a different menu for each week or day, which not only wastes paper but is also difficult for students to remember. It would be great if users get a menu whenever in need on their mobile phone and help them decide whether to have their meals in a mess or college cafe. So, to overcome such situations, this daily problem can be solved, using GSM and 8051 microcontroller to know the menu, just like a bot on an IRCTC’s or any other website does, which helps by searching a specific keyword to help out with consumers problems. Similarly, a keyword like “menu” can be sent as an SMS to GSM which will act as an input to the microcontroller and according to that specific day and time it will process the menu and give the output to the GSM which will be sent to the user’s mobile phone as an SMS, so in-short GSM will act as an interface for handling messaging service. By this, students can know their offered meal anytime anywhere and can respond by texting “yes” to make a plate for them. If a student does not respond “yes” then his/her portion of food will be reduced in the mess pantry while preparing the meal. Therefore, this will limit food wastage as well.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134496615","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 : 2022-05-06DOI: 10.1109/PCEMS55161.2022.9807858
Chithraja Rajan, Jyoti Patel, V. Satpute, D. P. Samajdar
This paper focuses on Hetero-Junction Nanowire TFET (HJ-NW-TFET) based circuit implementation. Here, a combination of an electrically doped drain, physically doped source and hetero materials form a HJ that provide better ON current and low ambipolarity in NW-TFET. Formerly, only device electrical characteristics are imported in circuit through Verilog-A modeling and least has been investigated regarding linearity and reliability. Whereas, physical variations incorporated during fabrication and environmental changes are two serious sources of design deviations which can neither be eliminated nor can be predicated as they are inherited and unique in nature. Therefore, to check the device performance in various situations a lookup table based low power comparator is implemented using HJ-NW-TFET. Comparator designed in this way has 10 ns delay even in low supply voltage and the effect of 10 % variations on HJ-NW-TFET performance is less than 5 % which promises distortion free and fault tolerant real circuit applications.
{"title":"A Novel NW-TFET Based Low Power, High Speed and Variations Resistant Comparator with Improved Linearity","authors":"Chithraja Rajan, Jyoti Patel, V. Satpute, D. P. Samajdar","doi":"10.1109/PCEMS55161.2022.9807858","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9807858","url":null,"abstract":"This paper focuses on Hetero-Junction Nanowire TFET (HJ-NW-TFET) based circuit implementation. Here, a combination of an electrically doped drain, physically doped source and hetero materials form a HJ that provide better ON current and low ambipolarity in NW-TFET. Formerly, only device electrical characteristics are imported in circuit through Verilog-A modeling and least has been investigated regarding linearity and reliability. Whereas, physical variations incorporated during fabrication and environmental changes are two serious sources of design deviations which can neither be eliminated nor can be predicated as they are inherited and unique in nature. Therefore, to check the device performance in various situations a lookup table based low power comparator is implemented using HJ-NW-TFET. Comparator designed in this way has 10 ns delay even in low supply voltage and the effect of 10 % variations on HJ-NW-TFET performance is less than 5 % which promises distortion free and fault tolerant real circuit applications.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132226291","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 : 2022-05-06DOI: 10.1109/pcems55161.2022.9807904
{"title":"PCEMS 2022 Cover Page","authors":"","doi":"10.1109/pcems55161.2022.9807904","DOIUrl":"https://doi.org/10.1109/pcems55161.2022.9807904","url":null,"abstract":"","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123212684","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 : 2022-05-06DOI: 10.1109/PCEMS55161.2022.9807936
S. B. Gundre, V. Ratnaparkhe
A dual-band monopole antenna with a simple, flexible structure designed for wearable applications is proposed in this paper. These antennas are expected to perform with the least amount of degradation in vicinity to the human body. To meet these requirements, the wearable antenna design becomes challenging. Moreover, human body has high dielectric permittivity and losses that significantly affect the desired antenna performance, especially causing the detuning. Thus, a dual-band wearable antenna is projected to cater a solution to this problem. The proposed antenna of 35 mm X 36 mm has a compact size and designed on a flexible jeans material substrate. The antenna resonating at 2.8 GHz and 3.8 GHz provides dual band operation over 2.68 GHz- 2.95 GHz and 3.65 GHz-4.18 GHz which claims its application in WiMAX. The SAR measured is well within the standard limits even without incorporating the structures to mitigate back radiation. The obtained specific absorption rate (SAR) values at lower and higher resonating frequencies are 1.50 W/kg and 1.59 W/kg respectively without back radiation prevention structure. Furthermore, a technique to calibrate the antenna structure for mitigating the moisture effect in the textile fabric is proposed. The proposed antenna asserts its place under on-body communication as it offers all the traits essential for a wearable antenna.
提出了一种结构简单、灵活的可穿戴双频单极天线。预计这些天线在接近人体时性能退化最小。为了满足这些要求，可穿戴天线的设计变得具有挑战性。此外，人体具有较高的介电常数和损耗，严重影响天线的预期性能，特别是造成失谐。因此，双频可穿戴天线被设计用来解决这个问题。所提出的天线尺寸为35 mm X 36 mm，尺寸紧凑，设计在柔性牛仔裤材料基板上。该天线谐振频率为2.8 GHz和3.8 GHz，可在2.68 GHz- 2.95 GHz和3.65 GHz-4.18 GHz范围内提供双频工作，可用于WiMAX。即使没有加入减轻背辐射的结构，测量的SAR也完全在标准范围内。在没有防背辐射结构的情况下，得到的比吸收率(SAR)在低、高谐振频率下分别为1.50 W/kg和1.59 W/kg。在此基础上，提出了一种消除织物水分效应的天线结构标定技术。该天线在人体通信中占有一席之地，因为它提供了可穿戴天线的所有基本特征。
{"title":"Simple and Flexible Structure of Dual-band Monopole Wearable Patch Antenna","authors":"S. B. Gundre, V. Ratnaparkhe","doi":"10.1109/PCEMS55161.2022.9807936","DOIUrl":"https://doi.org/10.1109/PCEMS55161.2022.9807936","url":null,"abstract":"A dual-band monopole antenna with a simple, flexible structure designed for wearable applications is proposed in this paper. These antennas are expected to perform with the least amount of degradation in vicinity to the human body. To meet these requirements, the wearable antenna design becomes challenging. Moreover, human body has high dielectric permittivity and losses that significantly affect the desired antenna performance, especially causing the detuning. Thus, a dual-band wearable antenna is projected to cater a solution to this problem. The proposed antenna of 35 mm X 36 mm has a compact size and designed on a flexible jeans material substrate. The antenna resonating at 2.8 GHz and 3.8 GHz provides dual band operation over 2.68 GHz- 2.95 GHz and 3.65 GHz-4.18 GHz which claims its application in WiMAX. The SAR measured is well within the standard limits even without incorporating the structures to mitigate back radiation. The obtained specific absorption rate (SAR) values at lower and higher resonating frequencies are 1.50 W/kg and 1.59 W/kg respectively without back radiation prevention structure. Furthermore, a technique to calibrate the antenna structure for mitigating the moisture effect in the textile fabric is proposed. The proposed antenna asserts its place under on-body communication as it offers all the traits essential for a wearable antenna.","PeriodicalId":248874,"journal":{"name":"2022 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (PCEMS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127240591","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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