Pub Date : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9453025
A. Anand, Aditya Asok, Arpith P, S. S, G. Nandana, Swathy S. Panicker, Baby Sreeja S D, Sreenidhi P R
In this paper, the authors propose efficient Piezo-material with optimized structure body motion based energy harvesting based on the principles of piezoelectric effect. The authors plan to implement a secondary source of energy which can be powered by human motions and does not require replacement of batteries which could otherwise pave way for a cost margin that would amount to a larger cost over a longer period of time. The methods used are relevant to the principles of piezoelectricity which are powered by harnessing natural human vibrations. Nanogenerators are used for this purpose of energy conversion. The studies related to length optimizations, material and resonant frequency are conducted by using COMSOL Multiphysics software. Polyvinylidene Fluoride (PVDF) displayed the best output with regard to the materials studied. By patterning the initial structure, piezoelectric material was optimized to achieve a minimum Eigen frequency value due to the generation of mutual capacitance. The minimization of Eigen frequency value signified its ability to generate adequate output voltages even when exposed to minimal frequency vibrations which it can realize.
{"title":"Optimizing Design of Wearable Energy Generator for Body Motion based Energy Harvesting","authors":"A. Anand, Aditya Asok, Arpith P, S. S, G. Nandana, Swathy S. Panicker, Baby Sreeja S D, Sreenidhi P R","doi":"10.1109/ICOEI51242.2021.9453025","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453025","url":null,"abstract":"In this paper, the authors propose efficient Piezo-material with optimized structure body motion based energy harvesting based on the principles of piezoelectric effect. The authors plan to implement a secondary source of energy which can be powered by human motions and does not require replacement of batteries which could otherwise pave way for a cost margin that would amount to a larger cost over a longer period of time. The methods used are relevant to the principles of piezoelectricity which are powered by harnessing natural human vibrations. Nanogenerators are used for this purpose of energy conversion. The studies related to length optimizations, material and resonant frequency are conducted by using COMSOL Multiphysics software. Polyvinylidene Fluoride (PVDF) displayed the best output with regard to the materials studied. By patterning the initial structure, piezoelectric material was optimized to achieve a minimum Eigen frequency value due to the generation of mutual capacitance. The minimization of Eigen frequency value signified its ability to generate adequate output voltages even when exposed to minimal frequency vibrations which it can realize.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122480935","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452920
G. Manikandan, G. Bhuvaneswari, Suhasini, K. G. Saravanan, M. Parameswari, D.Sterlin Rani
Consistent versatility the board is a capacity to offer the different types of assistance during the correspondence in remote heterogeneous organizations. Because of the irregular versatility of the portable terminals, the availability between various cell phones gets lost. To give the lossless network between the cell phones, the handover from the purpose of current connection to another point is fundamental. To improve the Seamless portability the board and traffic signal, an effective model called Generalized Light Gradient Boost Decision Tree-based Traffic-Aware Seamless Mobility (GLGBDT-TASM) model is presented in the heterogeneous organization. At the point when a portable hub in the organization moves out of its correspondence range, the sign strength of the hubs is determined. In view of the sign strength assessment, the Generalized Light Gradient Boost Decision Tree classifier orders the versatile hubs into the feeble and solid sign strength with the limit esteem. The boosting calculation at first develops' frail students for example double choice tree to distinguish the frail sign strength of the portable hub. At that point the group classifier joins the consequences of frail students and limits the speculation mistake. This assists with playing out the handover just with the powerless sign strength of the hub coming about in limits the repetitive handover. Furthermore, the powerless sign strength of the portable hub from the current connection point handover towards the closest accessible connection highlight improve the consistent information conveyance. Followed by, transmission capacity accessibility is estimated for diminishing the bundle misfortune because of the organization traffic coming about in improves the consistent information conveyance between the hubs. The reenactment is completed to assess the exhibition of the GLGBDT-TASM model with two related methodologies. The outcomes show that the GLGBDT-TASM model viably improved traffic-mindful consistent versatility in a heterogeneous organization with least deferral and bundle misfortune just as a higher information conveyance rate when contrasted with best in class techniques.
{"title":"Traffic Control Loss and to Handle Seamless Mobility in a Heterogeneous Network with Lesser Transmission Delay","authors":"G. Manikandan, G. Bhuvaneswari, Suhasini, K. G. Saravanan, M. Parameswari, D.Sterlin Rani","doi":"10.1109/ICOEI51242.2021.9452920","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452920","url":null,"abstract":"Consistent versatility the board is a capacity to offer the different types of assistance during the correspondence in remote heterogeneous organizations. Because of the irregular versatility of the portable terminals, the availability between various cell phones gets lost. To give the lossless network between the cell phones, the handover from the purpose of current connection to another point is fundamental. To improve the Seamless portability the board and traffic signal, an effective model called Generalized Light Gradient Boost Decision Tree-based Traffic-Aware Seamless Mobility (GLGBDT-TASM) model is presented in the heterogeneous organization. At the point when a portable hub in the organization moves out of its correspondence range, the sign strength of the hubs is determined. In view of the sign strength assessment, the Generalized Light Gradient Boost Decision Tree classifier orders the versatile hubs into the feeble and solid sign strength with the limit esteem. The boosting calculation at first develops' frail students for example double choice tree to distinguish the frail sign strength of the portable hub. At that point the group classifier joins the consequences of frail students and limits the speculation mistake. This assists with playing out the handover just with the powerless sign strength of the hub coming about in limits the repetitive handover. Furthermore, the powerless sign strength of the portable hub from the current connection point handover towards the closest accessible connection highlight improve the consistent information conveyance. Followed by, transmission capacity accessibility is estimated for diminishing the bundle misfortune because of the organization traffic coming about in improves the consistent information conveyance between the hubs. The reenactment is completed to assess the exhibition of the GLGBDT-TASM model with two related methodologies. The outcomes show that the GLGBDT-TASM model viably improved traffic-mindful consistent versatility in a heterogeneous organization with least deferral and bundle misfortune just as a higher information conveyance rate when contrasted with best in class techniques.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122633844","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9453003
Sumedh Patil, Baba Patra, Neha Goyal, Kapil O. Gupta
Plants play a crucial role in nature and the well-being of the population. They have a significant contribution towards ecological stability and are also sources of our needs like food, medicine, and essential commercial products. As a result of massive scale deforestation, topsoil erosion, and habitat destruction, both the number and type of plants' existing species are steadily declining. So, plantation and identification and classification of plant species are essential for preserving plant species and accelerated farm as it will help in the better understanding of plants. Nevertheless, they are difficult to exercise as plant identification needs domain knowledge and experience. However, due to advances in machine learning and deep learning, this problem is tackled correctly. Various machine Learning and Deep Learning algorithms like Support Vector Machine, Artificial Neural Network, Convolutional Neural Network, Probabilistic Neural Network have successfully experimented on plant leaf images to identify the species with near correct accuracy. This article attempts a comparative analysis of various approaches used for plant identification. Several experiments with Swedish leaves confirm the effectiveness of machine learning and CNN based classification model.
{"title":"Recognizing Plant species using Digitized leaves- A comparative study","authors":"Sumedh Patil, Baba Patra, Neha Goyal, Kapil O. Gupta","doi":"10.1109/ICOEI51242.2021.9453003","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453003","url":null,"abstract":"Plants play a crucial role in nature and the well-being of the population. They have a significant contribution towards ecological stability and are also sources of our needs like food, medicine, and essential commercial products. As a result of massive scale deforestation, topsoil erosion, and habitat destruction, both the number and type of plants' existing species are steadily declining. So, plantation and identification and classification of plant species are essential for preserving plant species and accelerated farm as it will help in the better understanding of plants. Nevertheless, they are difficult to exercise as plant identification needs domain knowledge and experience. However, due to advances in machine learning and deep learning, this problem is tackled correctly. Various machine Learning and Deep Learning algorithms like Support Vector Machine, Artificial Neural Network, Convolutional Neural Network, Probabilistic Neural Network have successfully experimented on plant leaf images to identify the species with near correct accuracy. This article attempts a comparative analysis of various approaches used for plant identification. Several experiments with Swedish leaves confirm the effectiveness of machine learning and CNN based classification model.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131263799","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452990
U. Muthuraman, A. Swetha, J. J, P. Annapandi, N. Rajesh, J. A. Nesa Priya
For voltage sag compensation, an effective device used for gaining acceptance is dynamic voltage restorer. Depending upon the high voltage injection and the amount of energy stored in the restorer, the compensation capability of a dynamic voltage restorer (DVR) will occur. In the distribution system, phenomenon that mainly occurs is the voltage sag, which minimizes the RMS voltage for a short stretch of time. In order to compensate the voltage sag, a power electronic device that is DVR is utilized to inoculate a $3 phi$ voltage in series and to synchronise with the distribution feeder voltage. Here the working of DVR is explained. The control methods employed for compensation of sag, swell, harmonics by power circuit of DVR is explained and verified by using simulation. In the distribution system, power quality disturbance is the main concern, which develops tripping and malfunctions in sensitive equipment. The main power quality problems can be cleared by inoculating the real and reactive power to the point of connection (PCC) by DVR. In order to improve the efficiency of the distribution system, the remuneration of voltage sag and swell issues and the elimination of power factor issues and harmonics by DVR are explained in this study and it is done with and without ANN. During power quality events, it is found that, the obtained output in both the cases is the proposed system that readily find the harmonics and eliminates the power quality problems by inoculating the real/reactive power with no/less distortions than traditional system.
{"title":"Power Quality Improvement Based On Artificial Neural Network Controller and Dynamic Voltage Restorer","authors":"U. Muthuraman, A. Swetha, J. J, P. Annapandi, N. Rajesh, J. A. Nesa Priya","doi":"10.1109/ICOEI51242.2021.9452990","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452990","url":null,"abstract":"For voltage sag compensation, an effective device used for gaining acceptance is dynamic voltage restorer. Depending upon the high voltage injection and the amount of energy stored in the restorer, the compensation capability of a dynamic voltage restorer (DVR) will occur. In the distribution system, phenomenon that mainly occurs is the voltage sag, which minimizes the RMS voltage for a short stretch of time. In order to compensate the voltage sag, a power electronic device that is DVR is utilized to inoculate a $3 phi$ voltage in series and to synchronise with the distribution feeder voltage. Here the working of DVR is explained. The control methods employed for compensation of sag, swell, harmonics by power circuit of DVR is explained and verified by using simulation. In the distribution system, power quality disturbance is the main concern, which develops tripping and malfunctions in sensitive equipment. The main power quality problems can be cleared by inoculating the real and reactive power to the point of connection (PCC) by DVR. In order to improve the efficiency of the distribution system, the remuneration of voltage sag and swell issues and the elimination of power factor issues and harmonics by DVR are explained in this study and it is done with and without ANN. During power quality events, it is found that, the obtained output in both the cases is the proposed system that readily find the harmonics and eliminates the power quality problems by inoculating the real/reactive power with no/less distortions than traditional system.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"373 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127730441","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452816
B. Sridhar, S. Sridhar, V. Nanchariah, K. Gayatri
The main aim for this research work is to develop an Adaptive BSA (Backtracking Optimized Search Algorithm) method to solve the optimization problem in image segmentation. In adaptive optimization algorithms, the probability of intersection and mutation depends on the value of the appropriate solution to improve convergence performance. Because of its memory function and simple structure, BSA has powerful features to find a globally optimized solution. However, the algorithm is not yet sufficient to strike a balance between exploration and exploitation of a medical image. Therefore, an improved adaptive tracking and search algorithm has been proposed together with morphological operations, where adaptive bilateral filter will improve the sharpness of edges of a unique region for obtaining global digital optimization in order to reach the cluster image segmentation. The proposed work shows better color quality-based image segmentation for the detection of tumors in medical images. The proposed optimization algorithm results show better performance, when compared to the basic BSA optimization method.
{"title":"Cluster Medical Image Segmentation using Morphological Adaptive Bilateral Filter based BSA Algorithm","authors":"B. Sridhar, S. Sridhar, V. Nanchariah, K. Gayatri","doi":"10.1109/ICOEI51242.2021.9452816","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452816","url":null,"abstract":"The main aim for this research work is to develop an Adaptive BSA (Backtracking Optimized Search Algorithm) method to solve the optimization problem in image segmentation. In adaptive optimization algorithms, the probability of intersection and mutation depends on the value of the appropriate solution to improve convergence performance. Because of its memory function and simple structure, BSA has powerful features to find a globally optimized solution. However, the algorithm is not yet sufficient to strike a balance between exploration and exploitation of a medical image. Therefore, an improved adaptive tracking and search algorithm has been proposed together with morphological operations, where adaptive bilateral filter will improve the sharpness of edges of a unique region for obtaining global digital optimization in order to reach the cluster image segmentation. The proposed work shows better color quality-based image segmentation for the detection of tumors in medical images. The proposed optimization algorithm results show better performance, when compared to the basic BSA optimization method.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127746705","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9453088
L. Kumari, Mohammad Aatif Jaffery, K. Nigam, G. Manaswi, P. Tharangini
Parkinson's disease is a brain-related disease that is common in every person mainly persons above age 45 years. This disease causes numbness in muscles, swallowing problems, bending of the back, shivering in hands, smell dysfunction, speaking problem, Hearing problem, and many more. Parkinson's disease has to be diagnosed as early as possible since the clinical tests, which take hours to detect, may cost a loss of time and money. An automated model for detecting Parkinson's disease in a person with greater accuracy is proposed in this paper. While several models for detecting Parkinson's disease have been established, they are all less reliable and precise. Our model is created using the gradient boosted decision tree, which not only reliably predicts Parkinson's disease in a human, but also predicts it quickly. The feature set contains 22 parameters of the voice signal, which are given to the XGBoost classifier. The developed model predicts Parkinson's disease with 96.6% of accuracy, 95.6% of sensitivity, 100% of specificity, 100% of Precision, F-Score 97.7%.
{"title":"Detection of Parkinson's Disease using Extreme Gradient Boosting","authors":"L. Kumari, Mohammad Aatif Jaffery, K. Nigam, G. Manaswi, P. Tharangini","doi":"10.1109/ICOEI51242.2021.9453088","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453088","url":null,"abstract":"Parkinson's disease is a brain-related disease that is common in every person mainly persons above age 45 years. This disease causes numbness in muscles, swallowing problems, bending of the back, shivering in hands, smell dysfunction, speaking problem, Hearing problem, and many more. Parkinson's disease has to be diagnosed as early as possible since the clinical tests, which take hours to detect, may cost a loss of time and money. An automated model for detecting Parkinson's disease in a person with greater accuracy is proposed in this paper. While several models for detecting Parkinson's disease have been established, they are all less reliable and precise. Our model is created using the gradient boosted decision tree, which not only reliably predicts Parkinson's disease in a human, but also predicts it quickly. The feature set contains 22 parameters of the voice signal, which are given to the XGBoost classifier. The developed model predicts Parkinson's disease with 96.6% of accuracy, 95.6% of sensitivity, 100% of specificity, 100% of Precision, F-Score 97.7%.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131797557","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 general, the consumers benefit from cloud computing because of its scalability, performance, flexibility, and low infrastructure investment. Everyone is moving from traditional services towards various cloud services at minimal cost. Because of the benefits of virtualization and data storage, people are increasingly embracing them and posing some new security issues. Using virtualization is an advantage for consumers because security is one of the features that are taken care to lesser extent. This paper summarizes the need for virtualization along with its benefits and multiple security vulnerabilities are explained in detail by a diagram that illustrates about virtualization security issues that are virtual machine based, Hypervisor based and virtual machine based attacks. There are some recommendations to strengthen the security and privacy in virtualization.
{"title":"TOUR TOWARDS THE SECURITY CHALLENGES OF VIRTUALIZATION IN CLOUD COMPUTING: A SURVEY","authors":"Jinkani Avinash, Kanakatla Pranay, Nerandla Rakesh Goud, Poonam Tanwar, Shweta Sharma","doi":"10.1109/ICOEI51242.2021.9452879","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452879","url":null,"abstract":"In general, the consumers benefit from cloud computing because of its scalability, performance, flexibility, and low infrastructure investment. Everyone is moving from traditional services towards various cloud services at minimal cost. Because of the benefits of virtualization and data storage, people are increasingly embracing them and posing some new security issues. Using virtualization is an advantage for consumers because security is one of the features that are taken care to lesser extent. This paper summarizes the need for virtualization along with its benefits and multiple security vulnerabilities are explained in detail by a diagram that illustrates about virtualization security issues that are virtual machine based, Hypervisor based and virtual machine based attacks. There are some recommendations to strengthen the security and privacy in virtualization.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"37 31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125705614","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9453087
Mingdong Chen
With the rapid development of computer technology, geographic information system and remote sensing technology, the popularization of data information technology has been greatly promoted. Grassland, as an important part of natural resources, is increasingly managed by geographic information platform, including ground observation of grassland vegetation, remote sensing information data acquisition, positioning and navigation, and application of satellite remote sensing data. Grassland data acquisition provides scientific and technological means for the acquisition, processing, analysis, use and management of grassland vegetation and ecological information. At the same time, GIS platform can effectively integrate basic spatial database sharing, data services and applications, and significantly improve the development and application level of basic geospatial data.
{"title":"Grassland Data Acquisition based on Internet of Things and Cloud Computing","authors":"Mingdong Chen","doi":"10.1109/ICOEI51242.2021.9453087","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453087","url":null,"abstract":"With the rapid development of computer technology, geographic information system and remote sensing technology, the popularization of data information technology has been greatly promoted. Grassland, as an important part of natural resources, is increasingly managed by geographic information platform, including ground observation of grassland vegetation, remote sensing information data acquisition, positioning and navigation, and application of satellite remote sensing data. Grassland data acquisition provides scientific and technological means for the acquisition, processing, analysis, use and management of grassland vegetation and ecological information. At the same time, GIS platform can effectively integrate basic spatial database sharing, data services and applications, and significantly improve the development and application level of basic geospatial data.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129144371","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452985
A. Sen, Sowmya Bakka
Over the years, several new technologies have been implemented in order to automate substations, which constitute an integral part of any electric power system. With the advent of the fully automated power grid, known as smart grid, many nations have been able to achieve this. The new international standard IEC 61850 offers several benefits for the design of a substation, the most significant one being the elimination of wired technologies, which has been replaced by wireless technologies such as ZigBee, WiMAX, WLAN, Wireless HART, etc. Wired technology poses several disadvantages such as the need for trenches, manual labor required for assembling and testing of wires and complex installation methods. Wireless technologies act as an easy solution, making wired communication redundant. Thus, extensive research and development of wireless technologies for substation automation is a necessity. This article provides a comprehensive review of the state-of-the-art existing wireless technologies with regards to their features, short comings as well as future work to be incorporated, in order to facilitate further development in this field.
{"title":"A Study of Wireless Communication for Substation Automation","authors":"A. Sen, Sowmya Bakka","doi":"10.1109/ICOEI51242.2021.9452985","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452985","url":null,"abstract":"Over the years, several new technologies have been implemented in order to automate substations, which constitute an integral part of any electric power system. With the advent of the fully automated power grid, known as smart grid, many nations have been able to achieve this. The new international standard IEC 61850 offers several benefits for the design of a substation, the most significant one being the elimination of wired technologies, which has been replaced by wireless technologies such as ZigBee, WiMAX, WLAN, Wireless HART, etc. Wired technology poses several disadvantages such as the need for trenches, manual labor required for assembling and testing of wires and complex installation methods. Wireless technologies act as an easy solution, making wired communication redundant. Thus, extensive research and development of wireless technologies for substation automation is a necessity. This article provides a comprehensive review of the state-of-the-art existing wireless technologies with regards to their features, short comings as well as future work to be incorporated, in order to facilitate further development in this field.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132017944","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 : 2021-06-03DOI: 10.1109/ICOEI51242.2021.9452832
S. Srivastava, Prateek Gupta, Pranjal Kumar
Facial expression is a verbal act of speech that is expressed on the face in terms of our emotions. Emotional recognition to identify facial expression plays crucial role in various applications like psychology, linguistics etc. Playing an important role in the fields of artificial intelligence and robotics, the automatic recognition of facial expression is therefore a need for generation. Emotion recognition plays an important role in the area of human machine communication. Emotional recognition is usually done in four stages which include pre-processing, facial recognition, feature extraction, and classification. In this paper, we have used deep learning to identify the seven main human emotions: anger, disgust, fear, happiness, sadness, surprise and neutrality.
{"title":"Emotion Recognition Based Emoji Retrieval Using Deep Learning","authors":"S. Srivastava, Prateek Gupta, Pranjal Kumar","doi":"10.1109/ICOEI51242.2021.9452832","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452832","url":null,"abstract":"Facial expression is a verbal act of speech that is expressed on the face in terms of our emotions. Emotional recognition to identify facial expression plays crucial role in various applications like psychology, linguistics etc. Playing an important role in the fields of artificial intelligence and robotics, the automatic recognition of facial expression is therefore a need for generation. Emotion recognition plays an important role in the area of human machine communication. Emotional recognition is usually done in four stages which include pre-processing, facial recognition, feature extraction, and classification. In this paper, we have used deep learning to identify the seven main human emotions: anger, disgust, fear, happiness, sadness, surprise and neutrality.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131590142","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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