Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085387
K. Deepak, U. Chaithanya, M. Lingmaiah, Shaik Abdul Siraj, K. Narahari Kalyan Kumar, Nageti Aravind
Applications of multilevel inverters are increasing day by day due to their capability to operate for higher voltage with less harmonic components at output terminals. The Neutral Point Clamped (NPC) and Cascaded H-Bridge (CHB) inverters are two well-known multilevel inverter topologies that are used as traditional converters. Different methods of producing pulses to activate semiconductor switches in multilevel inverters are used to minimize harmonics. Pulse Width Modulation (PWM) methodologies for multilevel inverters are introducing every day to make system more applicable. Among many, a Sinusoidal PWM (SPWM) technique is a popular method for generating pulses to switches. Compared to NPC, the structure of CHB is simple and having more futures. However, for a higher level, number of switches of inverter goes increase. Hence, asymmetrical CHB configuration is implemented with a smaller number of switches for higher levels. Various multilevel topologies with suitable SPWM methods are proposed in this paper. For analysis of proposed configuration, five and fifteen level inverters of CHB configuration is presented with phase and line voltages. Extensive results are presented in this paper with the help of MATLAB/Simulink package.
{"title":"Performance Comparisons of Multilevel Inverter Topologies","authors":"K. Deepak, U. Chaithanya, M. Lingmaiah, Shaik Abdul Siraj, K. Narahari Kalyan Kumar, Nageti Aravind","doi":"10.1109/ICEARS56392.2023.10085387","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085387","url":null,"abstract":"Applications of multilevel inverters are increasing day by day due to their capability to operate for higher voltage with less harmonic components at output terminals. The Neutral Point Clamped (NPC) and Cascaded H-Bridge (CHB) inverters are two well-known multilevel inverter topologies that are used as traditional converters. Different methods of producing pulses to activate semiconductor switches in multilevel inverters are used to minimize harmonics. Pulse Width Modulation (PWM) methodologies for multilevel inverters are introducing every day to make system more applicable. Among many, a Sinusoidal PWM (SPWM) technique is a popular method for generating pulses to switches. Compared to NPC, the structure of CHB is simple and having more futures. However, for a higher level, number of switches of inverter goes increase. Hence, asymmetrical CHB configuration is implemented with a smaller number of switches for higher levels. Various multilevel topologies with suitable SPWM methods are proposed in this paper. For analysis of proposed configuration, five and fifteen level inverters of CHB configuration is presented with phase and line voltages. Extensive results are presented in this paper with the help of MATLAB/Simulink package.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115727500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085247
Libina M, Mahan K
Good voice communication has become a top requirement in today’s rapidly growing world. Noise from the surroundings affects the quality of voice and audio signals in acoustic applications. The original voice signal that was broadcast can occasionally no longer be recovered. Acoustic Noise Cancellation (ANC) is a method for improving the quality of speech and audio signals by removing noise in the voice signal. The adaptive filter, a crucial component of the ANC, reduces noise without first knowing the difference between the signal and the noise. Conventional filters would cause the desired voice stream to be distorted. So, when speech and noise signals are random, adaptive filters are appropriate. A primary input with a damaged signal and a reference input with noise that is unknowably associated with the noise in the primary input make up the ANC’s two inputs. The reference input is adaptively filtered and subtracted from the primary input to get the clean speech signal estimation. The performance of the LMS and NLMS algorithms is significantly impacted by the step size and filter length M. Smaller mean square errors lead to longer convergence times (MSE). When it is large, the algorithm diverges, which reduces the adaptive filter’s efficacy. The trade-off between convergence time and MSE must thus be balanced when deciding on a step size, which is a difficult problem. Another practical difficulty is presented by selecting the filter’s tap length M. As filter length M rises, so do the filter’s convergence time and MSE. Consequently, a shorter-length filter is required. Unfortunately, deciding on the number of filter taps is mostly a matter of experience and trial and error. In LMS and NLMS algorithms, it can be challenging to choose the step size of the algorithm and the length of the adaptive filter M to provide the most excellent possible noise cancellation.
{"title":"Hybrid Noise Reduction And Enhancement of Audio Quality using Deep Learning","authors":"Libina M, Mahan K","doi":"10.1109/ICEARS56392.2023.10085247","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085247","url":null,"abstract":"Good voice communication has become a top requirement in today’s rapidly growing world. Noise from the surroundings affects the quality of voice and audio signals in acoustic applications. The original voice signal that was broadcast can occasionally no longer be recovered. Acoustic Noise Cancellation (ANC) is a method for improving the quality of speech and audio signals by removing noise in the voice signal. The adaptive filter, a crucial component of the ANC, reduces noise without first knowing the difference between the signal and the noise. Conventional filters would cause the desired voice stream to be distorted. So, when speech and noise signals are random, adaptive filters are appropriate. A primary input with a damaged signal and a reference input with noise that is unknowably associated with the noise in the primary input make up the ANC’s two inputs. The reference input is adaptively filtered and subtracted from the primary input to get the clean speech signal estimation. The performance of the LMS and NLMS algorithms is significantly impacted by the step size and filter length M. Smaller mean square errors lead to longer convergence times (MSE). When it is large, the algorithm diverges, which reduces the adaptive filter’s efficacy. The trade-off between convergence time and MSE must thus be balanced when deciding on a step size, which is a difficult problem. Another practical difficulty is presented by selecting the filter’s tap length M. As filter length M rises, so do the filter’s convergence time and MSE. Consequently, a shorter-length filter is required. Unfortunately, deciding on the number of filter taps is mostly a matter of experience and trial and error. In LMS and NLMS algorithms, it can be challenging to choose the step size of the algorithm and the length of the adaptive filter M to provide the most excellent possible noise cancellation.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115755742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085256
A. T, S. S., R. A., Santhosh K M
Better area and delay performance is the goal of the modulo multiplier architecture that has been created in this paper. The design's architecture increases both the maximum frequency and the area that is occupied on the intended FPGA. Lightweight elliptic curve encryption is constructed using the suggested architecture as a modular multiplier over general G(p). In this design, radix-2 Montgomery Modular Multiplication structure is enhanced. In order to decrease the critical route latency and raise the maximum frequency, the suggested architecture does not perform subtraction or multiplication operations, instead it performs only one pre-calculated addition operation, which reduces the loops of process in computing. When compared to other state-of-the-art modular multipliers, these multipliers' accuracy is equivalent with better area and delay.
{"title":"FPGA –based Optimized Design of Montgomery Modular Multiplier using Karatsuba Algorithm","authors":"A. T, S. S., R. A., Santhosh K M","doi":"10.1109/ICEARS56392.2023.10085256","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085256","url":null,"abstract":"Better area and delay performance is the goal of the modulo multiplier architecture that has been created in this paper. The design's architecture increases both the maximum frequency and the area that is occupied on the intended FPGA. Lightweight elliptic curve encryption is constructed using the suggested architecture as a modular multiplier over general G(p). In this design, radix-2 Montgomery Modular Multiplication structure is enhanced. In order to decrease the critical route latency and raise the maximum frequency, the suggested architecture does not perform subtraction or multiplication operations, instead it performs only one pre-calculated addition operation, which reduces the loops of process in computing. When compared to other state-of-the-art modular multipliers, these multipliers' accuracy is equivalent with better area and delay.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"9 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120807059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085273
M. Subbarao, J. T. S. Sindhu, N. N. S. Harshitha, K. Vasavi, A. S. Krishna, G. Ram
Retinal imaging analysis is used to diagnose and classify retinal diseases like age-related macular degeneration (AMD), retinal detachment, diabetic retinopathy (DR), retinitis pigmentosa, and retinoblastoma. The automated detection of retinal disorders is a significant step towards early disease diagnosis and the prevention of disease progression. Historically, a number of cutting-edge techniques have been created to aid in the automatic segmentation and detection of retinal landmarks and diseases. But new advances in deep learning and advanced ophthalmology imaging modalities have given researchers access to a whole new domain. In this paper, two multilayer deep neural networks convolutional neural network (CNN) and AlexNet are presented for the early detection of retinal degeneration. Further analysis is carried out by applying three different types of optimizers to train the classifiers, such as ADAM, RMSProp, and SGDM. The performance analysis is carried out with high-resolution fundus images at three different training rates to determine the superiority of the classifiers.
{"title":"Detection of Retinal Degeneration via High-Resolution Fundus Images using Deep Neural Networks","authors":"M. Subbarao, J. T. S. Sindhu, N. N. S. Harshitha, K. Vasavi, A. S. Krishna, G. Ram","doi":"10.1109/ICEARS56392.2023.10085273","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085273","url":null,"abstract":"Retinal imaging analysis is used to diagnose and classify retinal diseases like age-related macular degeneration (AMD), retinal detachment, diabetic retinopathy (DR), retinitis pigmentosa, and retinoblastoma. The automated detection of retinal disorders is a significant step towards early disease diagnosis and the prevention of disease progression. Historically, a number of cutting-edge techniques have been created to aid in the automatic segmentation and detection of retinal landmarks and diseases. But new advances in deep learning and advanced ophthalmology imaging modalities have given researchers access to a whole new domain. In this paper, two multilayer deep neural networks convolutional neural network (CNN) and AlexNet are presented for the early detection of retinal degeneration. Further analysis is carried out by applying three different types of optimizers to train the classifiers, such as ADAM, RMSProp, and SGDM. The performance analysis is carried out with high-resolution fundus images at three different training rates to determine the superiority of the classifiers.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121043494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085395
P. G, M. T, Gowrishankar C, Rohith Bhat C, Gowrishankar V, S. M.
The concerned workers ensure that vehicles are parked in the appropriate spaces. Employees must repeatedly poll their coworkers via personal surveys or the company's internal phone system to ensure that everything is correct. If there is an available parking space, the driver will manually move the vehicle there, regardless of any obstacles. If there is no available space, the car must return and try again later. The proposed intelligent parking system, if implemented, would solve all parking problems. This will take less time and fuel than other options. Intelligent parking solutions will fundamentally alter automobile-centric cities. It may make parking more convenient by bringing order to the chaos. People are always concerned that finding a parking spot will take too long, particularly in densely populated cities. This study focuses on developing a new system in which residents in high-traffic areas can earn extra money by renting out their unused parking spaces to those in need. This strategy could help malls to manage parking more effectively during peak shopping hours. A customer can save time by reserving a parking space ahead of time.
{"title":"An IoT based Low Cost E-Parking System in Smart Cities","authors":"P. G, M. T, Gowrishankar C, Rohith Bhat C, Gowrishankar V, S. M.","doi":"10.1109/ICEARS56392.2023.10085395","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085395","url":null,"abstract":"The concerned workers ensure that vehicles are parked in the appropriate spaces. Employees must repeatedly poll their coworkers via personal surveys or the company's internal phone system to ensure that everything is correct. If there is an available parking space, the driver will manually move the vehicle there, regardless of any obstacles. If there is no available space, the car must return and try again later. The proposed intelligent parking system, if implemented, would solve all parking problems. This will take less time and fuel than other options. Intelligent parking solutions will fundamentally alter automobile-centric cities. It may make parking more convenient by bringing order to the chaos. People are always concerned that finding a parking spot will take too long, particularly in densely populated cities. This study focuses on developing a new system in which residents in high-traffic areas can earn extra money by renting out their unused parking spaces to those in need. This strategy could help malls to manage parking more effectively during peak shopping hours. A customer can save time by reserving a parking space ahead of time.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127381612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085579
P. Sudha, J. Jegathesh Amalraj, M. Sivakumar
Recently, financial globalization is an extremely improved in distinct manners for enhancing service quality with advanced resources. An effectual application of bitcoin Blockchain (BC) approaches allows the shareholders to be concern regarding the risk and return of financial product. The shareholders mainly concentrate on the predictive of risk and return rates of financial product. Thus, an automated return rate bitcoin predictive method develops vital for BC financial product (FP). A newly planned machine learning (ML) and deep learning (DL) techniques offers a way for the return rate predictor systems. This work designs a Lion Swarm Optimization with Deep Learning Driven Predictive Model on Blockchain Financial Product Return Rates (LSODL-BFPRR) technique. The projected LSODL-BFPRR technique lies in the effectual forecasting of return rates in the BC financial sector. In the presented LSODL-BFPRR technique, stacked bidirectional gated recurrent unit (SBiGRU) approach was exploited for return rate classification. To modify the hyperparameters based on the SBiGRU approach, the LSO algorithm is used. The LSODL- BFPRR technique exploits Ethereum (ETH) return rate as the target. The experimental outcomes of the LSODL-BFPRR technique are tested using a series of simulations and the results demonstrate the effectual predicting results of the LSODL-BFPRR technique over other ones.
{"title":"Lion Swarm Optimization with Deep Learning Driven Predictive Model on Blockchain Financial Product Return Rates","authors":"P. Sudha, J. Jegathesh Amalraj, M. Sivakumar","doi":"10.1109/ICEARS56392.2023.10085579","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085579","url":null,"abstract":"Recently, financial globalization is an extremely improved in distinct manners for enhancing service quality with advanced resources. An effectual application of bitcoin Blockchain (BC) approaches allows the shareholders to be concern regarding the risk and return of financial product. The shareholders mainly concentrate on the predictive of risk and return rates of financial product. Thus, an automated return rate bitcoin predictive method develops vital for BC financial product (FP). A newly planned machine learning (ML) and deep learning (DL) techniques offers a way for the return rate predictor systems. This work designs a Lion Swarm Optimization with Deep Learning Driven Predictive Model on Blockchain Financial Product Return Rates (LSODL-BFPRR) technique. The projected LSODL-BFPRR technique lies in the effectual forecasting of return rates in the BC financial sector. In the presented LSODL-BFPRR technique, stacked bidirectional gated recurrent unit (SBiGRU) approach was exploited for return rate classification. To modify the hyperparameters based on the SBiGRU approach, the LSO algorithm is used. The LSODL- BFPRR technique exploits Ethereum (ETH) return rate as the target. The experimental outcomes of the LSODL-BFPRR technique are tested using a series of simulations and the results demonstrate the effectual predicting results of the LSODL-BFPRR technique over other ones.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"26 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125679295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085499
Harmeet Kaur Kochhar, Mrudula Kilaru, N. Aljohani, Himanshu Rai Goyal, Devendra Singh, DilipKumar Jang Bahadur Saini
Artificial intelligence (AI) has the potential to transform clinical decision-making and assistance. In any case, the utilization of current AI methods remains only as a supportive solution to make clinical decisions. The existing methodologies fail to perform in-depth analysis to deliver accurate predictions. This study reviews the integration of advanced technologies AutoML in healthcare sector by considering the data privacy, heterogeneity and interpretability. This review will be a useful resource for medical practitioners interested in applying information science methods to their field of study.
{"title":"Implementing Deep Learning Techniques into Healthcare System Improvement","authors":"Harmeet Kaur Kochhar, Mrudula Kilaru, N. Aljohani, Himanshu Rai Goyal, Devendra Singh, DilipKumar Jang Bahadur Saini","doi":"10.1109/ICEARS56392.2023.10085499","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085499","url":null,"abstract":"Artificial intelligence (AI) has the potential to transform clinical decision-making and assistance. In any case, the utilization of current AI methods remains only as a supportive solution to make clinical decisions. The existing methodologies fail to perform in-depth analysis to deliver accurate predictions. This study reviews the integration of advanced technologies AutoML in healthcare sector by considering the data privacy, heterogeneity and interpretability. This review will be a useful resource for medical practitioners interested in applying information science methods to their field of study.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"21 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115550284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085329
Saravanan Alagarsamy, Muthuvel P, K. Kumar, M. Reddy, M. M. Naidu, M. V. Kumar
Diabetes needs to be managed constantly because it is a chronic and complicated medical illness. The importance of creating cutting-edge solutions to aid in the management of this condition is growing as diabetes prevalence rises. This study suggests using machine learning to manage healthcare costs and anticipate the onset of diabetes. To be more precise, we suggest combining supervised and unsupervised learning techniques to deliver patient-specific real-time forecasts and track the development of the disease. Using publicly accessible diabetes datasets, we will assess the performance of the suggested approach and contrast the findings with current techniques. In addition, we'll talk about how applying machine learning approaches could help with diabetes management. The goal of this paper is to present the potential of machine learning for enhancing diabetes treatment and to offer a framework for further investigation in this field.
{"title":"System for Predicting the Diabetes using Machine Learning Techniques","authors":"Saravanan Alagarsamy, Muthuvel P, K. Kumar, M. Reddy, M. M. Naidu, M. V. Kumar","doi":"10.1109/ICEARS56392.2023.10085329","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085329","url":null,"abstract":"Diabetes needs to be managed constantly because it is a chronic and complicated medical illness. The importance of creating cutting-edge solutions to aid in the management of this condition is growing as diabetes prevalence rises. This study suggests using machine learning to manage healthcare costs and anticipate the onset of diabetes. To be more precise, we suggest combining supervised and unsupervised learning techniques to deliver patient-specific real-time forecasts and track the development of the disease. Using publicly accessible diabetes datasets, we will assess the performance of the suggested approach and contrast the findings with current techniques. In addition, we'll talk about how applying machine learning approaches could help with diabetes management. The goal of this paper is to present the potential of machine learning for enhancing diabetes treatment and to offer a framework for further investigation in this field.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116456179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085043
Cintamaria Simon, M. Rajeswari
With the advancements in speech recognition and AI technology, there is a growing demand for convenient and efficient ways to interact with technology. A Voice-based Virtual Assistant is a technologically advanced solution that uses speech recognition and artificial intelligence to provide users with a convenient and efficient way to interact with devices, access information, and perform tasks. It makes use of the GPT-3 language processing model by OpenAI to respond intelligently. With the help of spoken commands and natural language processing, users can communicate with the virtual assistant using this technology, which is intended to function as a chat interface. However, as with any technology that collects and stores personal information, security is a major concern. The added security feature addresses this concern by incorporating encryption, authentication, and access controls to ensure that personal data remains secure. This not only protects the user’s privacy but also helps to prevent unauthorized access to sensitive information, such as bank account numbers, passwords, and other confidential data.
{"title":"Voice-based Virtual Assistant with Security","authors":"Cintamaria Simon, M. Rajeswari","doi":"10.1109/ICEARS56392.2023.10085043","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085043","url":null,"abstract":"With the advancements in speech recognition and AI technology, there is a growing demand for convenient and efficient ways to interact with technology. A Voice-based Virtual Assistant is a technologically advanced solution that uses speech recognition and artificial intelligence to provide users with a convenient and efficient way to interact with devices, access information, and perform tasks. It makes use of the GPT-3 language processing model by OpenAI to respond intelligently. With the help of spoken commands and natural language processing, users can communicate with the virtual assistant using this technology, which is intended to function as a chat interface. However, as with any technology that collects and stores personal information, security is a major concern. The added security feature addresses this concern by incorporating encryption, authentication, and access controls to ensure that personal data remains secure. This not only protects the user’s privacy but also helps to prevent unauthorized access to sensitive information, such as bank account numbers, passwords, and other confidential data.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122500786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085635
D. E, I. S, Indrajith C R, K. A
The characteristics of a country's healthcare system are thought to be among the most crucial factors in this paper's description of the electronic health record using block chain technology. Currently, the patient's medical information is kept in electronic health records (EHR). EHR does, however, have some drawbacks, including interoperability, security, and privacy. All these problems result in a deterioration in the standard of the medical system and an expand in healthcare costs because data are split among various medical facilities in various locations. Medical data management presents several special difficulties, such as data access and the frequency with which data is accessed outside of a medical facility. The potential for blockchain technology to help improve the current healthcare system exists. This paper aims to show how EHR can be used in the healthcare industry. EHR sharing systems can be made more effective, secure, and private with the help of blockchain technology. On the other hand, current solutions that depend on a central bibliography are liable to conventional safety problems like Denial of Service (DoS) attacks and alone bit of defeat, as are conventional bibliography systems. Additionally, earlier solutions did not address performance and scalability issues, leaving users vulnerable to privacy linking attacks.
{"title":"Design and Development of an E-Healthcare Records Management System using Blockchain Algorithm","authors":"D. E, I. S, Indrajith C R, K. A","doi":"10.1109/ICEARS56392.2023.10085635","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085635","url":null,"abstract":"The characteristics of a country's healthcare system are thought to be among the most crucial factors in this paper's description of the electronic health record using block chain technology. Currently, the patient's medical information is kept in electronic health records (EHR). EHR does, however, have some drawbacks, including interoperability, security, and privacy. All these problems result in a deterioration in the standard of the medical system and an expand in healthcare costs because data are split among various medical facilities in various locations. Medical data management presents several special difficulties, such as data access and the frequency with which data is accessed outside of a medical facility. The potential for blockchain technology to help improve the current healthcare system exists. This paper aims to show how EHR can be used in the healthcare industry. EHR sharing systems can be made more effective, secure, and private with the help of blockchain technology. On the other hand, current solutions that depend on a central bibliography are liable to conventional safety problems like Denial of Service (DoS) attacks and alone bit of defeat, as are conventional bibliography systems. Additionally, earlier solutions did not address performance and scalability issues, leaving users vulnerable to privacy linking attacks.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122841982","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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