Road traffic is frequently congested due to the metropolitan cities' fast population expansion and urban mobility. The conventional approaches, including timers or human control, have been shown to be inadequate for resolving this problem. In order to handle a variety of challenges with controlling traffic on roadways and to assist authorities in effective planning, an abstract solution has been proposed to control traffic lights according to the density of vehicles on different lanes of road. The solution shall take input from surveillance cameras, evaluate the density using machine learning algorithm and provide the optimal time duration to manage traffic lights. This approach offers a substitute for the conventional approach, which uses monotonous, fixed-time traffic signals. The suggested strategy attempts to lessen road congestion while simultaneously improving the quality of transportation. Moreover, it also ensures minimum standby timing of vehicles on road intersections using graph structure and polynomials.
{"title":"Proposed Approach for Dynamic Automobile Traffic Management System","authors":"Deepa Abin, Aditya Yadav, Prathamesh Bhagat, Harsh Mankar, Shubham Raut","doi":"10.1109/ICEARS56392.2023.10085231","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085231","url":null,"abstract":"Road traffic is frequently congested due to the metropolitan cities' fast population expansion and urban mobility. The conventional approaches, including timers or human control, have been shown to be inadequate for resolving this problem. In order to handle a variety of challenges with controlling traffic on roadways and to assist authorities in effective planning, an abstract solution has been proposed to control traffic lights according to the density of vehicles on different lanes of road. The solution shall take input from surveillance cameras, evaluate the density using machine learning algorithm and provide the optimal time duration to manage traffic lights. This approach offers a substitute for the conventional approach, which uses monotonous, fixed-time traffic signals. The suggested strategy attempts to lessen road congestion while simultaneously improving the quality of transportation. Moreover, it also ensures minimum standby timing of vehicles on road intersections using graph structure and polynomials.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"19 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":"122158822","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/ICEARS56392.2023.10085481
Shikha Prasher, Leema Nelson, A. S. Sindhu, S. Sumathi, Mukta Jagdish
In this study, a machine learning model for contingency classification of an energy system was developed. A greater cost reduction can be achieved from the huge amount of data extracted from the energy infrastructure, and analysis of early contingency detection is performed. The complexity of contingency analysis can be reduced by mining, which reduces the hardware use. In this research, two different machine learning algorithms, a Multi-Class Support Vector Machine (MCSVM) and a Multi-Class Relevance Vector Machine (MCRVM), are used to classify the different contingency levels using the mined data, which comprises the voltage, power generated, and angles from line. Combined data cleaning and analysis served as a data transformation technique. Principal Component Analysis (PCA) is used to reduce the dimensionality of data for classification. The trained model using Multi-class SVM and RVM was generated using the line data output mapped on the composite contingency index obtained from it. The model thus generated would act as a classification black box that would classify the condition as normal, alarming or lowly contingent. A MATLAB simulation was carried out on an IEEE 30 bus system and classification of the contingency into three levels of contingency was observed to be satisfactory.
在本研究中，建立了一个用于能源系统偶然性分类的机器学习模型。通过从能源基础设施中提取大量数据，并进行早期突发事件检测分析，可以实现更大的成本降低。通过挖掘可以降低偶然性分析的复杂性，从而减少硬件的使用。本研究采用多类支持向量机(Multi-Class Support Vector machine, MCSVM)和多类相关向量机(Multi-Class Relevance Vector machine, MCRVM)两种不同的机器学习算法，利用挖掘的数据(包括电压、产生的功率和与线的角度)对不同的事故级别进行分类。结合数据清理和分析作为一种数据转换技术。主成分分析(PCA)是一种将数据降维进行分类的方法。利用多类支持向量机和RVM的训练模型，将得到的线数据输出映射到综合应急指数上，生成训练模型。由此产生的模型将作为一个分类黑箱，将情况分为正常、警报或低偶然。在ieee30总线系统上进行了MATLAB仿真，结果表明，将偶然性划分为三个级别是令人满意的。
{"title":"MCSVM and MCRVM based Contingency Classification Model","authors":"Shikha Prasher, Leema Nelson, A. S. Sindhu, S. Sumathi, Mukta Jagdish","doi":"10.1109/ICEARS56392.2023.10085481","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085481","url":null,"abstract":"In this study, a machine learning model for contingency classification of an energy system was developed. A greater cost reduction can be achieved from the huge amount of data extracted from the energy infrastructure, and analysis of early contingency detection is performed. The complexity of contingency analysis can be reduced by mining, which reduces the hardware use. In this research, two different machine learning algorithms, a Multi-Class Support Vector Machine (MCSVM) and a Multi-Class Relevance Vector Machine (MCRVM), are used to classify the different contingency levels using the mined data, which comprises the voltage, power generated, and angles from line. Combined data cleaning and analysis served as a data transformation technique. Principal Component Analysis (PCA) is used to reduce the dimensionality of data for classification. The trained model using Multi-class SVM and RVM was generated using the line data output mapped on the composite contingency index obtained from it. The model thus generated would act as a classification black box that would classify the condition as normal, alarming or lowly contingent. A MATLAB simulation was carried out on an IEEE 30 bus system and classification of the contingency into three levels of contingency was observed to be satisfactory.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"1 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":"128691432","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/ICEARS56392.2023.10084966
Md. Ether Deowan, Ahsan Kabir Nuhel, MD Jannatul Naim, Mir Mohibullah Sazid, Iftekhar Haider, Ferdous Alam, Priyanka Roy
Providing space for both power plants and agriculture can be a significant difficulty for densely populated nations with limited land. In this paper, transparent photovoltaic (PV) panels are utilized to construct a solar power plant that can simultaneously produce electricity to the national grid and serve as land for agriculture, as sunlight can penetrate through transparent PV panels. This will allow the system to generate electricity in frames land without harming the agriculture. In addition to enhancing agricultural output, agro-photovoltaic adds to the provision of off-grid power in developing and rural regions. For enhancing the protection of the system Directional Over current relay (DOCR) is used for analyzing the faults. To connect the power plant in the load, the hardware specifications of transparent PV panels, boost converters, inverters, and transformers is reviewed in depth.
{"title":"Development of an Agro-Photovoltaic Transparent Solar Panel and DOCR for Agriculture and Grid System Usage","authors":"Md. Ether Deowan, Ahsan Kabir Nuhel, MD Jannatul Naim, Mir Mohibullah Sazid, Iftekhar Haider, Ferdous Alam, Priyanka Roy","doi":"10.1109/ICEARS56392.2023.10084966","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10084966","url":null,"abstract":"Providing space for both power plants and agriculture can be a significant difficulty for densely populated nations with limited land. In this paper, transparent photovoltaic (PV) panels are utilized to construct a solar power plant that can simultaneously produce electricity to the national grid and serve as land for agriculture, as sunlight can penetrate through transparent PV panels. This will allow the system to generate electricity in frames land without harming the agriculture. In addition to enhancing agricultural output, agro-photovoltaic adds to the provision of off-grid power in developing and rural regions. For enhancing the protection of the system Directional Over current relay (DOCR) is used for analyzing the faults. To connect the power plant in the load, the hardware specifications of transparent PV panels, boost converters, inverters, and transformers is reviewed in depth.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"65 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":"124596676","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/ICEARS56392.2023.10084933
Ravi Raja A, Sistla Jyothirmy, Gottam Geethika, Seetha Bharath Sai, B. Saiteja, V. H. Prasad Reddy
Now-a-days stress is one of the major issues in every individual’s life. It may cause many physiological and psychological problems. Many researchers have taken this into account and proposed various stress detection models. This paper mainly focuses on various stress detection models which are published in the latest years. The stress level of an individual is classified using machine learning algorithms like K-Nearest Neighbor (KNN), Naive Bayes (NB), Logistic regression (LR), Support Vector Machine (SVM) etc. It is observed that SVM produces a high accuracy when compared with other classifiers. The organization of the paper is as follows, Section I gives a brief introduction on stress and a basic idea about the datasets used by the researchers. Section II provides literature review. Section III contains analysis on collected literature.
{"title":"Machine Learning Algorithms based Detection and Analysis of Stress - A Review","authors":"Ravi Raja A, Sistla Jyothirmy, Gottam Geethika, Seetha Bharath Sai, B. Saiteja, V. H. Prasad Reddy","doi":"10.1109/ICEARS56392.2023.10084933","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10084933","url":null,"abstract":"Now-a-days stress is one of the major issues in every individual’s life. It may cause many physiological and psychological problems. Many researchers have taken this into account and proposed various stress detection models. This paper mainly focuses on various stress detection models which are published in the latest years. The stress level of an individual is classified using machine learning algorithms like K-Nearest Neighbor (KNN), Naive Bayes (NB), Logistic regression (LR), Support Vector Machine (SVM) etc. It is observed that SVM produces a high accuracy when compared with other classifiers. The organization of the paper is as follows, Section I gives a brief introduction on stress and a basic idea about the datasets used by the researchers. Section II provides literature review. Section III contains analysis on collected literature.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"26 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":"130308058","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/ICEARS56392.2023.10084995
Adil Alahmad, F. Kaçar, Ö. Farsakoğlu, C. P. Uzunoğlu
In order to keep up with rising customer demand, more and more MVDs are being used to fuel MV motors. Power delivery to a load may be modulated by changing the pulse width. A digital signal might be transformed into an analog one using the pulse width modulation (PWM) technique. A pulse-width modulated (PWM) signal, which takes the form of a rectangular wave, alternates between ON and OFF states. The characteristics of a pulse-width modulation (PWM) signal are determined by its frequency and duty cycle. The inverter's switching and harmonic losses may be minimized by using PWM technology. In order to cut down on switching loss, hybrid PWM inverters operate half of their switches at low frequencies while operating the other half at high frequencies. Because switching loss and heat dissipation from switches are unpredictable, system reliability is reduced. It's possible that switching will lead to poor heat dissipation and power losses. However, problems like these may be lessened with the use of a PWM technique. By alternating between low-frequency and high-frequency signals, the output voltage and frequency may be adjusted, which in turn reduces the power supply's harmonic content. Methods such as Multiple Space Vector Modulation, Selective Harmonic Elimination, Multilevel Carrier Phase Shifted, and Multilevel Carrier Level Shifted Pulse Width Modulation has been considered. However, although these methods effectively reduce higher-order harmonics, it is more complex to increase inverter efficiency in a way that does not introduce additional losses. To eliminate these harmonics, a filter is made. Comparisons are made between sinusoidal PWM, PWM with a phase angle of sixty degrees, and trapezoidal PWM in terms of performance. The study tracked the effects of modulation index and carrier frequency adjustments on inverter output.
{"title":"Medium-Voltage Drives (MVD) - Pulse Width Modulation (PWM) Techniques","authors":"Adil Alahmad, F. Kaçar, Ö. Farsakoğlu, C. P. Uzunoğlu","doi":"10.1109/ICEARS56392.2023.10084995","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10084995","url":null,"abstract":"In order to keep up with rising customer demand, more and more MVDs are being used to fuel MV motors. Power delivery to a load may be modulated by changing the pulse width. A digital signal might be transformed into an analog one using the pulse width modulation (PWM) technique. A pulse-width modulated (PWM) signal, which takes the form of a rectangular wave, alternates between ON and OFF states. The characteristics of a pulse-width modulation (PWM) signal are determined by its frequency and duty cycle. The inverter's switching and harmonic losses may be minimized by using PWM technology. In order to cut down on switching loss, hybrid PWM inverters operate half of their switches at low frequencies while operating the other half at high frequencies. Because switching loss and heat dissipation from switches are unpredictable, system reliability is reduced. It's possible that switching will lead to poor heat dissipation and power losses. However, problems like these may be lessened with the use of a PWM technique. By alternating between low-frequency and high-frequency signals, the output voltage and frequency may be adjusted, which in turn reduces the power supply's harmonic content. Methods such as Multiple Space Vector Modulation, Selective Harmonic Elimination, Multilevel Carrier Phase Shifted, and Multilevel Carrier Level Shifted Pulse Width Modulation has been considered. However, although these methods effectively reduce higher-order harmonics, it is more complex to increase inverter efficiency in a way that does not introduce additional losses. To eliminate these harmonics, a filter is made. Comparisons are made between sinusoidal PWM, PWM with a phase angle of sixty degrees, and trapezoidal PWM in terms of performance. The study tracked the effects of modulation index and carrier frequency adjustments on inverter output.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"1 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":"130338339","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/ICEARS56392.2023.10085361
Sivanandam K, P. M, Naveen B, S. S
Farming is a major industry in most poor nations. Modern agriculture is continually progressing in terms of farming methods and agricultural innovations. Farmers may find it difficult to adjust to ever-evolving market, consumer, and policy demands. Among the challenges that farmers face, (i) Fixing the climate crisis brought on by deforestation and factory emissions (ii) Crop development may be hampered by deficiencies in soil nutrients brought on by a lack of minerals including potassium, N, and phosphorus. (iii) Farmers should avoid planting the same crops year after year without experimenting with anything new. They just throw on a bunch of fertilizers, regardless of how much or how good a quality they are. The purpose of this research is to determine which crop prediction model is the most effective at helping farmers make informed decisions about which crops to grow given a variety of environmental and agronomic variables. In this article, Selection Model is used to analyze the well-known algorithms including K-Nearest Neighbor.
{"title":"An Efficient Machine Learning Approaches for Crop Recommendation based on Soil Characteristics","authors":"Sivanandam K, P. M, Naveen B, S. S","doi":"10.1109/ICEARS56392.2023.10085361","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085361","url":null,"abstract":"Farming is a major industry in most poor nations. Modern agriculture is continually progressing in terms of farming methods and agricultural innovations. Farmers may find it difficult to adjust to ever-evolving market, consumer, and policy demands. Among the challenges that farmers face, (i) Fixing the climate crisis brought on by deforestation and factory emissions (ii) Crop development may be hampered by deficiencies in soil nutrients brought on by a lack of minerals including potassium, N, and phosphorus. (iii) Farmers should avoid planting the same crops year after year without experimenting with anything new. They just throw on a bunch of fertilizers, regardless of how much or how good a quality they are. The purpose of this research is to determine which crop prediction model is the most effective at helping farmers make informed decisions about which crops to grow given a variety of environmental and agronomic variables. In this article, Selection Model is used to analyze the well-known algorithms including K-Nearest Neighbor.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"30 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":"123848883","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/ICEARS56392.2023.10085354
Shilpa H.K
As the prevalence of new forms of financial transaction exists, such as instalment cards, has grown, so too has the sophistication and pervasiveness of fraud. After that, I'll discuss measures taken to detect and prevent fraud. As a result of their ability to construct models that understand and recognize the possibility of scam based on previous incidences of scam, data mining techniques are able to differentiate fraud. One of the financial frauds, the fiscal summary deception, has expanded rapidly around the globe. Corporate governance, financial reporting, and review capabilities have all taken a hit as a result of high-profile firm failures. Worldwide, companies are increasingly concerned about the growing threat of fraud using financial summaries. Because data mining approaches are well-suited to finding the grounds for dishonest financial declaration, Recognizing Fiscal Statement Scam stands apart as one of the key application areas of Facts Mining.
{"title":"Analyzing the Bank Scam's Financial Fraud and its Technological Repercussions using Data Mining","authors":"Shilpa H.K","doi":"10.1109/ICEARS56392.2023.10085354","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085354","url":null,"abstract":"As the prevalence of new forms of financial transaction exists, such as instalment cards, has grown, so too has the sophistication and pervasiveness of fraud. After that, I'll discuss measures taken to detect and prevent fraud. As a result of their ability to construct models that understand and recognize the possibility of scam based on previous incidences of scam, data mining techniques are able to differentiate fraud. One of the financial frauds, the fiscal summary deception, has expanded rapidly around the globe. Corporate governance, financial reporting, and review capabilities have all taken a hit as a result of high-profile firm failures. Worldwide, companies are increasingly concerned about the growing threat of fraud using financial summaries. Because data mining approaches are well-suited to finding the grounds for dishonest financial declaration, Recognizing Fiscal Statement Scam stands apart as one of the key application areas of Facts Mining.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"42 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":"123157432","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}
The need for image encryption is increasing as a result of the increased usage of the Internet and other communication tools. It is easy to attack and steal images sent over unsecured open channels. Techniques of encryption are necessary to safeguard the photos from attackers. In the modern period, the area of encryption is growing significantly. Given how dangerous cyber assaults become, image security is of the highest importance. One of the most well-liked methods to hide information is using image encryption. Based on various algorithms, there exist several ways for picture encryption. Some of them include the RSA algorithm, which offers faster encryption s peed and less security by encrypting data with public and private keys. Even though it takes longer, a different algorithm known as the Chaos-based algorithm offers greater picture security. The RSA and Chaos-based algorithms may be combined to produce advanced encryption, which gives high security in a shorter period of time. By using an RSA- generated key with a sufficient key s pace to thwart brute force attacks from succeeding, the encryption performance may increase without compromising the security.
{"title":"Image Security is Improved by Super Encryption using RSA and Chaos Algorithms","authors":"Dhulipalla Venkata Rao, Sanepalli Pavan Kumar Reddy, Chidaraboina Anusha, Dendukuri Bhoomika, Rayalla Venkateswarlu","doi":"10.1109/ICEARS56392.2023.10085142","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085142","url":null,"abstract":"The need for image encryption is increasing as a result of the increased usage of the Internet and other communication tools. It is easy to attack and steal images sent over unsecured open channels. Techniques of encryption are necessary to safeguard the photos from attackers. In the modern period, the area of encryption is growing significantly. Given how dangerous cyber assaults become, image security is of the highest importance. One of the most well-liked methods to hide information is using image encryption. Based on various algorithms, there exist several ways for picture encryption. Some of them include the RSA algorithm, which offers faster encryption s peed and less security by encrypting data with public and private keys. Even though it takes longer, a different algorithm known as the Chaos-based algorithm offers greater picture security. The RSA and Chaos-based algorithms may be combined to produce advanced encryption, which gives high security in a shorter period of time. By using an RSA- generated key with a sufficient key s pace to thwart brute force attacks from succeeding, the encryption performance may increase without compromising the security.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"17 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":"121280280","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/ICEARS56392.2023.10085130
Anitha E, A. Antonidoss
Presently, the medical industry is facing a serious issue. Machine Learning (ML) is emerging as a solution to analyze large datasets and develop predictive modeling or pattern classification. With the knowledge provided, clinicians could manage unhealthy patients without having a comprehensive of the ailment. As a result, ailments are occasionally misinterpreted and inadequately treated. Researchers teach the system to ascertain the likelihood of the person's ailment based on the symptoms given by the doctor using the existing statistical model. ML is the area of computer science that would be expanding the greatest, and health informatics is quite difficult. A goal of ML is to create predictive algorithms to learn and improve over time. Numerous industries employ the ML approach but the healthcare sector has benefited significantly from them. To increase patient safety and healthcare quality, it provides a wide range of warning and decision-support technologies. The proposed approach, which was created using ML algorithms, aids in earlier disease prediction. Doctors would benefit from they get more acquainted with novel ailments. Due to this knowledge, doctors should be able to treat patients appropriately by switching between illnesses.
{"title":"A Review on Disease Prediction Approach using Data Analytics and Machine Learning Algorithms","authors":"Anitha E, A. Antonidoss","doi":"10.1109/ICEARS56392.2023.10085130","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085130","url":null,"abstract":"Presently, the medical industry is facing a serious issue. Machine Learning (ML) is emerging as a solution to analyze large datasets and develop predictive modeling or pattern classification. With the knowledge provided, clinicians could manage unhealthy patients without having a comprehensive of the ailment. As a result, ailments are occasionally misinterpreted and inadequately treated. Researchers teach the system to ascertain the likelihood of the person's ailment based on the symptoms given by the doctor using the existing statistical model. ML is the area of computer science that would be expanding the greatest, and health informatics is quite difficult. A goal of ML is to create predictive algorithms to learn and improve over time. Numerous industries employ the ML approach but the healthcare sector has benefited significantly from them. To increase patient safety and healthcare quality, it provides a wide range of warning and decision-support technologies. The proposed approach, which was created using ML algorithms, aids in earlier disease prediction. Doctors would benefit from they get more acquainted with novel ailments. Due to this knowledge, doctors should be able to treat patients appropriately by switching between illnesses.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"101 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":"128138090","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/ICEARS56392.2023.10085019
R. Senkamalavalli, M. Nalini, G. Kalaimani, P. Iyyanar
Multiple uses of Wireless Sensor Networks (WSNs) in the real world would need the probable dispersion of a large number of sensor nodes. The adaptability and flexibility is very difficult in the traditional WSNs which uses balancing load technology. Software-defined networking (SDN) is a good choice because it lets you see what resources are used and also set up boundaries. In WSN, the highest traffic load causes an overflow of the data queue. As a result, important data should be lost. Also, the sensor node’s energy is rapidly drained, and the whole network’s lifespan is damaged. Traffic-aware routing with round robin technique (TARR) for equating the load in a software-defined WSN is proposed to solve this problem. The network contains two significant functions, namely, the formation of the network and the action of the network. This approach recognizes the traffic by obtaining or forwarding packets via control and data messages. In this approach, the round-robin technique is used during congestion situations. Thus, the data is forwarded constantly. As a result, the recipient node receives all data packets efficiently. The results of the simulation demonstrate that the TARR technique boosts network throughput while simultaneously reducing both packet loss and latency in a software-defined WSN.
{"title":"Traffic Aware Routing with Round Robin Technique for Equating the Load in Software Defined WSN","authors":"R. Senkamalavalli, M. Nalini, G. Kalaimani, P. Iyyanar","doi":"10.1109/ICEARS56392.2023.10085019","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085019","url":null,"abstract":"Multiple uses of Wireless Sensor Networks (WSNs) in the real world would need the probable dispersion of a large number of sensor nodes. The adaptability and flexibility is very difficult in the traditional WSNs which uses balancing load technology. Software-defined networking (SDN) is a good choice because it lets you see what resources are used and also set up boundaries. In WSN, the highest traffic load causes an overflow of the data queue. As a result, important data should be lost. Also, the sensor node’s energy is rapidly drained, and the whole network’s lifespan is damaged. Traffic-aware routing with round robin technique (TARR) for equating the load in a software-defined WSN is proposed to solve this problem. The network contains two significant functions, namely, the formation of the network and the action of the network. This approach recognizes the traffic by obtaining or forwarding packets via control and data messages. In this approach, the round-robin technique is used during congestion situations. Thus, the data is forwarded constantly. As a result, the recipient node receives all data packets efficiently. The results of the simulation demonstrate that the TARR technique boosts network throughput while simultaneously reducing both packet loss and latency in a software-defined WSN.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"8 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":"122275372","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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