Pub Date : 2021-10-01DOI: 10.1109/GCAT52182.2021.9587743
A. Chaitanya Kumar, Arjun Sharma, Velmathi Guruviah
Vehicular operation especially through four-wheeled vehicles is one of the most common ways of traveling across the world. A possibility for an unfortunate accident is always a possibility. Unfortunately, about 1.35 million people globally lose their lives on an average every year according to the World Health Organization (WHO) [1], many such incidents are preventable. To help address these avoidable incidents, there is a need to implement a means to keep a check on the driver at all times of vehicle operation. The authors propose a real-time solution that detects any and all instances of a driver experiencing drowsiness/fatigue or any form of distraction while driving. The implementation also undertakes appropriate measures to alert the driver and other passengers apart from any designated contacts about each such incidence of interest wherein the driver showcases said behaviors. Finally, the authors develop the above functionalities as an application compatible in devices running Windows or Linux Operating Systems.
{"title":"Driver Activity Oversight System","authors":"A. Chaitanya Kumar, Arjun Sharma, Velmathi Guruviah","doi":"10.1109/GCAT52182.2021.9587743","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587743","url":null,"abstract":"Vehicular operation especially through four-wheeled vehicles is one of the most common ways of traveling across the world. A possibility for an unfortunate accident is always a possibility. Unfortunately, about 1.35 million people globally lose their lives on an average every year according to the World Health Organization (WHO) [1], many such incidents are preventable. To help address these avoidable incidents, there is a need to implement a means to keep a check on the driver at all times of vehicle operation. The authors propose a real-time solution that detects any and all instances of a driver experiencing drowsiness/fatigue or any form of distraction while driving. The implementation also undertakes appropriate measures to alert the driver and other passengers apart from any designated contacts about each such incidence of interest wherein the driver showcases said behaviors. Finally, the authors develop the above functionalities as an application compatible in devices running Windows or Linux Operating Systems.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"34 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":"128488820","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/GCAT52182.2021.9587664
Rohan Sanghavi, Fenil Chheda, Sachin Kanchan, S. Kadge
Atrial fibrillation is a type of heart abnormality often called as an arrhythmia. It is detected when the heart does not beat at a normal pace i.e at spurious time intervals. Automatic atrial fibrillation (AFib) detection is a problem that has been tackled by researchers and engineers for a few decades. It is the most common of the arrhythmias [5]. Many people are susceptible to get AFib. According to the Centers for Disease Control and Prevention (CDC), approximately 2% of people younger than 65 years old have AFib, while about 9% of people ages 65 and older have it [6]. A device which can differentiate between sinus rhythm and AFib would be a gift for people having this illness.
{"title":"Detection Of Atrial Fibrillation in Electrocardiogram Signals using Machine Learning","authors":"Rohan Sanghavi, Fenil Chheda, Sachin Kanchan, S. Kadge","doi":"10.1109/GCAT52182.2021.9587664","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587664","url":null,"abstract":"Atrial fibrillation is a type of heart abnormality often called as an arrhythmia. It is detected when the heart does not beat at a normal pace i.e at spurious time intervals. Automatic atrial fibrillation (AFib) detection is a problem that has been tackled by researchers and engineers for a few decades. It is the most common of the arrhythmias [5]. Many people are susceptible to get AFib. According to the Centers for Disease Control and Prevention (CDC), approximately 2% of people younger than 65 years old have AFib, while about 9% of people ages 65 and older have it [6]. A device which can differentiate between sinus rhythm and AFib would be a gift for people having this illness.","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":"130871070","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/GCAT52182.2021.9587860
Neetu Agrawal, Manish Gupta, Sanjay Chauhan
As in investigation, Four U-shaped MIMO antennas with decoupling structures for 5G applications are shown. The proposed MIMO antenna design consist low profile Micro-strip monopole antennas that are arranged orthogonally at the corner of FR4 substrate. Multiple Input multiple output antenna resonating at 3.5336GHz which is suitable for low frequency 5G band application. Mutual coupling between radiating elements is reduced by partially ground structure (PSG) and orthogonal antenna element positioning. The entire configuration is created on a 36 x 36mm2 substrate. With an SWR of less than 2, the frequency bands recorded range from 3.20 to 3.86 GHz. Between neighboring and lateral ports; the estimated isolation is more than 14 dB.
在研究中，展示了用于5G应用的四个u形MIMO天线，具有解耦结构。所提出的MIMO天线设计由低轮廓微带单极天线组成，其正交布置在FR4衬底的角落。多输入多输出天线谐振频率为3.5336GHz，适用于低频5G频段应用。通过部分接地结构和正交天线单元定位，降低了辐射单元之间的相互耦合。整个配置是在36 x 36mm2基板上创建的。当信噪比小于2时，记录的频段范围为3.20 ~ 3.86 GHz。在邻近港口和侧面港口之间;估计隔离度大于14db。
{"title":"Design and Simulation of MIMO antenna for low frequency 5G band application","authors":"Neetu Agrawal, Manish Gupta, Sanjay Chauhan","doi":"10.1109/GCAT52182.2021.9587860","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587860","url":null,"abstract":"As in investigation, Four U-shaped MIMO antennas with decoupling structures for 5G applications are shown. The proposed MIMO antenna design consist low profile Micro-strip monopole antennas that are arranged orthogonally at the corner of FR4 substrate. Multiple Input multiple output antenna resonating at 3.5336GHz which is suitable for low frequency 5G band application. Mutual coupling between radiating elements is reduced by partially ground structure (PSG) and orthogonal antenna element positioning. The entire configuration is created on a 36 x 36mm2 substrate. With an SWR of less than 2, the frequency bands recorded range from 3.20 to 3.86 GHz. Between neighboring and lateral ports; the estimated isolation is more than 14 dB.","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":"131120402","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/GCAT52182.2021.9587545
N. S, H. S. Devi
Leaves are the primary sources for identifying a healthy plant and identifying many plant diseases. When leaf disease has not been correctly analyzed and early detection is not taken may produce a severe effect on the plants, which results in the loss of yield and quality of the production. Identifying or monitoring the diseases manually requires a tremendous amount of work and a lot of processing time. To overcome this, today, image processing has been widely used to identify conditions in plants to increase production. This paper has proposed a methodology to segment the leaf region using different color space models and flood filling algorithms. This system can be future used to classify the type of leaf disease.
{"title":"Leaf Region Segmentation for Plant Leaf Disease Detection using Color Conversion and Flood Filling","authors":"N. S, H. S. Devi","doi":"10.1109/GCAT52182.2021.9587545","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587545","url":null,"abstract":"Leaves are the primary sources for identifying a healthy plant and identifying many plant diseases. When leaf disease has not been correctly analyzed and early detection is not taken may produce a severe effect on the plants, which results in the loss of yield and quality of the production. Identifying or monitoring the diseases manually requires a tremendous amount of work and a lot of processing time. To overcome this, today, image processing has been widely used to identify conditions in plants to increase production. This paper has proposed a methodology to segment the leaf region using different color space models and flood filling algorithms. This system can be future used to classify the type of leaf disease.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"7 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":"129869934","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/GCAT52182.2021.9587758
Sneha Goel, Arpit Mittal, Shipra, Ankush Gupta
Blogging is something where you can share your knowledge with a large network and it also serves as a means to continue your passion. In this project, we have designed a blogging application which has features like facial authentication, social media integration along with Paytm integration. It has been developed by making use of the functionalities available in the Open-Computer-Vision (Open CV) library using Python. It has used Haar-Cascades for face detection purposes and Local binary pattern histograms (LBPH) recognizer for facial recognition.
写博客是你可以在一个大的网络上分享你的知识的地方，也是你继续激情的一种方式。在这个项目中，我们设计了一个博客应用程序，它具有面部认证，社交媒体集成以及Paytm集成等功能。它是通过使用Python利用开放计算机视觉(Open computer - vision, Open CV)库中的可用功能开发的。它使用haar级联进行人脸检测，使用局部二值模式直方图(LBPH)识别器进行人脸识别。
{"title":"A Blogging Application Based on Facial Authentication","authors":"Sneha Goel, Arpit Mittal, Shipra, Ankush Gupta","doi":"10.1109/GCAT52182.2021.9587758","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587758","url":null,"abstract":"Blogging is something where you can share your knowledge with a large network and it also serves as a means to continue your passion. In this project, we have designed a blogging application which has features like facial authentication, social media integration along with Paytm integration. It has been developed by making use of the functionalities available in the Open-Computer-Vision (Open CV) library using Python. It has used Haar-Cascades for face detection purposes and Local binary pattern histograms (LBPH) recognizer for facial recognition.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"7 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":"128899525","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/GCAT52182.2021.9587551
Nachiket Dunbray, R. Rane, Sparsh Nimje, Jayesh Katade, Shreyas Mavale
Diabetes is also known as diabetes mellitus is one of the world’s most prominent health hazards of the current times. It is a chronic disease in which the pancreas isn’t able to produce the right amounts of insulin for the body to absorb glucose into the body cells for energy and stays in the bloodstream in turn raising the blood glucose levels. If this is not detected and treated on time, it can affect other body organs as well and leads to organ failure thus becoming fatal.Machine learning and data mining are two emerging fields in today’s tech world. With the help of these methods, we can observe the past data behaviors and can then predict the future outcomes to a certain extent. This brings rise to the term ‘prediction models’ that we all know in today’s tech world. Keeping this in mind, we can create predictive models for diabetes prediction. This helps in the early detection of diabetes so that it can be treated at the earliest to avoid complications. By finding out the highest accuracy model, we can accurately predict whether the patient is diabetic beforehand and prevent further health issues. This research paper discusses the techniques that have been used to create a unique predictive model for the prediction of diabetes.
{"title":"A Novel Prediction Model for Diabetes Detection Using Gridsearch and A Voting Classifier between Lightgbm and KNN","authors":"Nachiket Dunbray, R. Rane, Sparsh Nimje, Jayesh Katade, Shreyas Mavale","doi":"10.1109/GCAT52182.2021.9587551","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587551","url":null,"abstract":"Diabetes is also known as diabetes mellitus is one of the world’s most prominent health hazards of the current times. It is a chronic disease in which the pancreas isn’t able to produce the right amounts of insulin for the body to absorb glucose into the body cells for energy and stays in the bloodstream in turn raising the blood glucose levels. If this is not detected and treated on time, it can affect other body organs as well and leads to organ failure thus becoming fatal.Machine learning and data mining are two emerging fields in today’s tech world. With the help of these methods, we can observe the past data behaviors and can then predict the future outcomes to a certain extent. This brings rise to the term ‘prediction models’ that we all know in today’s tech world. Keeping this in mind, we can create predictive models for diabetes prediction. This helps in the early detection of diabetes so that it can be treated at the earliest to avoid complications. By finding out the highest accuracy model, we can accurately predict whether the patient is diabetic beforehand and prevent further health issues. This research paper discusses the techniques that have been used to create a unique predictive model for the prediction of diabetes.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"168 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":"121621984","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/GCAT52182.2021.9587478
P. Mahapatro, Jatinderkumar R. Saini
This paper presents Zika Virus Analysis. Zika virus infection during pregnancy causes neurological disorder, Guillain-Barre syndrome, and birth defects in newborns. No cure or vaccine is available. The study of genome replication will bring some insight into the Zika virus. One of the important tasks in the cell is Genome replication. The daughter cells inherit its own copy of the genome, and then the cell divides in the process of genome replication. Ori is the position in the genome where the genome replicates. Finding the position of ori is a complicated task even for biologists. This task can be performed using Genome analysis. This paper presents the Genome analysis of Zika virus using innovative programming techniques instead of using a laboratory. Identifying the position ori will help the biologist in finding the position where the genome replication occurs.
{"title":"An Innovative Computer Programming based Analysis of Zika Virus for Identification of Genome Replication Location","authors":"P. Mahapatro, Jatinderkumar R. Saini","doi":"10.1109/GCAT52182.2021.9587478","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587478","url":null,"abstract":"This paper presents Zika Virus Analysis. Zika virus infection during pregnancy causes neurological disorder, Guillain-Barre syndrome, and birth defects in newborns. No cure or vaccine is available. The study of genome replication will bring some insight into the Zika virus. One of the important tasks in the cell is Genome replication. The daughter cells inherit its own copy of the genome, and then the cell divides in the process of genome replication. Ori is the position in the genome where the genome replicates. Finding the position of ori is a complicated task even for biologists. This task can be performed using Genome analysis. This paper presents the Genome analysis of Zika virus using innovative programming techniques instead of using a laboratory. Identifying the position ori will help the biologist in finding the position where the genome replication occurs.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"78 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":"120954620","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/GCAT52182.2021.9587574
Shafiqullah Sarwary, R. Perveen
In this paper the PV model system has connected with grid which have 100kv power capacity by using Simulink software. It also provide information related to behaviours of PV (Photovoltaic) characteristics and its model. The photovoltaic which connected with the grid contains a PV cells, distribution of system, a manage system along with load. Control technique of photo-voltaic structure attach to the Grid having two operative power. One is control of current that regulate the controlling of current at the point of ordinary coupling. So it carry out power factor and control the power factor as well regulates the voltage. The next one is control voltage, which use to achieve output of photovoltaic voltage, maximum power tracked quickly and fast of photovoltaic array. Maximum power point tracking growth the quality and the ability of the energy of PV panel highly. I have used the Pertub and observe method in this paper to obtained effectively results. The put forward of simulation model and the results we obtained would provide the deep acknowledgement of photovoltaic grid connected system.
{"title":"PV Cell Connected to Grid Power System","authors":"Shafiqullah Sarwary, R. Perveen","doi":"10.1109/GCAT52182.2021.9587574","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587574","url":null,"abstract":"In this paper the PV model system has connected with grid which have 100kv power capacity by using Simulink software. It also provide information related to behaviours of PV (Photovoltaic) characteristics and its model. The photovoltaic which connected with the grid contains a PV cells, distribution of system, a manage system along with load. Control technique of photo-voltaic structure attach to the Grid having two operative power. One is control of current that regulate the controlling of current at the point of ordinary coupling. So it carry out power factor and control the power factor as well regulates the voltage. The next one is control voltage, which use to achieve output of photovoltaic voltage, maximum power tracked quickly and fast of photovoltaic array. Maximum power point tracking growth the quality and the ability of the energy of PV panel highly. I have used the Pertub and observe method in this paper to obtained effectively results. The put forward of simulation model and the results we obtained would provide the deep acknowledgement of photovoltaic grid connected system.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"27 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":"126063260","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/GCAT52182.2021.9587565
Aniket Zope, Vandana Inamdar
In recent times the use of digital images has increased the demand for high-resolution images. The images captured are sometimes affected by noise, making visualization of the objects difficult, so the image super-resolution method is used to solve this problem. This research is based on a predefined Edge Informed Single Image Super-Resolution(EISR). The model is based on a deep learning approach that uses a convolutional neural network(CNN) and works on single image super-resolution(SISR). The first stage of the proposed model is the bi-cubic interpolation stage, followed by the Edge enhancement and Image completion stage. A qualitative comparison between the existing and proposed models on the x2 scaling factor is made.
{"title":"Edge Enhancement for Image Super-Resolution using Deep Learning Approach","authors":"Aniket Zope, Vandana Inamdar","doi":"10.1109/GCAT52182.2021.9587565","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587565","url":null,"abstract":"In recent times the use of digital images has increased the demand for high-resolution images. The images captured are sometimes affected by noise, making visualization of the objects difficult, so the image super-resolution method is used to solve this problem. This research is based on a predefined Edge Informed Single Image Super-Resolution(EISR). The model is based on a deep learning approach that uses a convolutional neural network(CNN) and works on single image super-resolution(SISR). The first stage of the proposed model is the bi-cubic interpolation stage, followed by the Edge enhancement and Image completion stage. A qualitative comparison between the existing and proposed models on the x2 scaling factor is made.","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":"124131120","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/GCAT52182.2021.9587662
P. S. Chatterjee
Cognitive Wireless Sensor Networks (CWSN) uses the spectrum resources in an intelligent manner in comparison to a normal Wireless Sensor Network (WSN). The technique which enables CWSNs in this regard is known as Opportunistic Spectrum Sensing (OSS) for data transfer. The OSS process significantly reduces the collisions and the delays for data delivery in a network. This OSS process is vulnerable to several security threats. A Primary User Emulation (PUE) attack in CWSN is a sort of Denial of Service (DoS) attack wherein hostile Secondary Users (SU) strive to imitate Primary Users (PUs) in effort to expand their personal spectrum intake or to prohibit other SUs from getting the spectrum. In this survey, we discussed the PUE attack and its associated dangers in CWSNs, as well as categorized the available state-of-the-art PUE attack detection strategies.
{"title":"A Systematic Survey for Detecting and Counteracting PUE Attacks in CWSNs","authors":"P. S. Chatterjee","doi":"10.1109/GCAT52182.2021.9587662","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587662","url":null,"abstract":"Cognitive Wireless Sensor Networks (CWSN) uses the spectrum resources in an intelligent manner in comparison to a normal Wireless Sensor Network (WSN). The technique which enables CWSNs in this regard is known as Opportunistic Spectrum Sensing (OSS) for data transfer. The OSS process significantly reduces the collisions and the delays for data delivery in a network. This OSS process is vulnerable to several security threats. A Primary User Emulation (PUE) attack in CWSN is a sort of Denial of Service (DoS) attack wherein hostile Secondary Users (SU) strive to imitate Primary Users (PUs) in effort to expand their personal spectrum intake or to prohibit other SUs from getting the spectrum. In this survey, we discussed the PUE attack and its associated dangers in CWSNs, as well as categorized the available state-of-the-art PUE attack detection strategies.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"36 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":"127855994","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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