Pub Date : 2023-03-02DOI: 10.1109/ICEARS56392.2023.10085153
A. Rahul Harikumar, Tanay Grover, M. Kanchana
The advancement of innovative technology that can accurately aid in the timely detection of intoxication in humans, particularly in scenarios requiring intoxication detection while driving, requires more research attention. Despite the fact that there are conceptual ideas for using facial recognition to perform this task, the results still need improvement. While the existing research works have demonstrated the capabilities of specific architectures, this article intends to develop an improved system to predict whether a driver is intoxicated or not by utilizing an ocular approach and CNNs. It also provides a general overview of face recognition and its applications. It can be assumed that if an improved system is developed and implemented in vehicles, the severe effects of drunk driving will be reduced. This study has tested five methods, within which four methods are composed of CNN architectures: VGG19, VGG16, MobileNet V2, and ResNet 50. The performance of an LSTM+ Attention Mechanism approach is also tested in this scenario. Finally, this article demonstrates that the VGG16 architecture provides the best validation accuracy for the given classification problem while also considering the results of other approaches to assess its applicability in alcoholic detection systems.
{"title":"Detection of Intoxication in Automobile Drivers","authors":"A. Rahul Harikumar, Tanay Grover, M. Kanchana","doi":"10.1109/ICEARS56392.2023.10085153","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085153","url":null,"abstract":"The advancement of innovative technology that can accurately aid in the timely detection of intoxication in humans, particularly in scenarios requiring intoxication detection while driving, requires more research attention. Despite the fact that there are conceptual ideas for using facial recognition to perform this task, the results still need improvement. While the existing research works have demonstrated the capabilities of specific architectures, this article intends to develop an improved system to predict whether a driver is intoxicated or not by utilizing an ocular approach and CNNs. It also provides a general overview of face recognition and its applications. It can be assumed that if an improved system is developed and implemented in vehicles, the severe effects of drunk driving will be reduced. This study has tested five methods, within which four methods are composed of CNN architectures: VGG19, VGG16, MobileNet V2, and ResNet 50. The performance of an LSTM+ Attention Mechanism approach is also tested in this scenario. Finally, this article demonstrates that the VGG16 architecture provides the best validation accuracy for the given classification problem while also considering the results of other approaches to assess its applicability in alcoholic detection systems.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"6 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":"128202167","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/ICEARS56392.2023.10084977
Sivanantham, Basireddy Satish Kumar Reddy, J. SaiGnaneswar, Kalahasti Balaji, K. S. Vivek Reddy, Kusam Lokesh Reddy
A deep learning approach will be used to recover ancient pictures that have suffered significant damage. Unlike typical reconstruction processes that are easily handled by supervised learning methods, real-world picture degradation seems to be complex, and the system is unable to generalize due to domain differences between synthetic pictures and actual old pictures. Therefore, using huge amounts of synthetic image pairs combined with real photos, Therefore, using huge amounts of synthetic picture pairs combined with real photos, A unique triplet domain translation network. Two variational autoencoders (VAEs) have been trained to create latent spaces from both fresh and old images, respectively. The translation between two regions is thenmanaged to learn using artificially paired data. This translation normalizes well to actual photographs as the domain gap is filled in the compact latent space. The translation between these two various latent regions has been taught using artificially paired data. This translation normalizes well to images found in the real world because the compact latent space is filled with the domain gap. A global division with an incomplete nonlocal block will target structural issues like cuts and bruises and a local division attacking unstructured defects like unwanted noise and poor contrast to handle the various degradations mixed throughout an old photograph. The latent space fusion of two branches increases the ability to correct numerous flaws in old images. Convolutional neural networks (CNNs) outperform multiple-layer sequenced neural network models at identifying distinct marks, forms, and patterns in images, making them the most efficient method for processing data. The filters are applied by CNN to every pixel in the image. When it comes to visual quality, the suggested method for repairing old photographs performs better than cutting-edge techniques.
{"title":"Deep Learning based Image Enhancing Environment with Noise Suppression","authors":"Sivanantham, Basireddy Satish Kumar Reddy, J. SaiGnaneswar, Kalahasti Balaji, K. S. Vivek Reddy, Kusam Lokesh Reddy","doi":"10.1109/ICEARS56392.2023.10084977","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10084977","url":null,"abstract":"A deep learning approach will be used to recover ancient pictures that have suffered significant damage. Unlike typical reconstruction processes that are easily handled by supervised learning methods, real-world picture degradation seems to be complex, and the system is unable to generalize due to domain differences between synthetic pictures and actual old pictures. Therefore, using huge amounts of synthetic image pairs combined with real photos, Therefore, using huge amounts of synthetic picture pairs combined with real photos, A unique triplet domain translation network. Two variational autoencoders (VAEs) have been trained to create latent spaces from both fresh and old images, respectively. The translation between two regions is thenmanaged to learn using artificially paired data. This translation normalizes well to actual photographs as the domain gap is filled in the compact latent space. The translation between these two various latent regions has been taught using artificially paired data. This translation normalizes well to images found in the real world because the compact latent space is filled with the domain gap. A global division with an incomplete nonlocal block will target structural issues like cuts and bruises and a local division attacking unstructured defects like unwanted noise and poor contrast to handle the various degradations mixed throughout an old photograph. The latent space fusion of two branches increases the ability to correct numerous flaws in old images. Convolutional neural networks (CNNs) outperform multiple-layer sequenced neural network models at identifying distinct marks, forms, and patterns in images, making them the most efficient method for processing data. The filters are applied by CNN to every pixel in the image. When it comes to visual quality, the suggested method for repairing old photographs performs better than cutting-edge techniques.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"408 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":"115921881","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/ICEARS56392.2023.10085459
Mrunalini T, R. P, Geethanjali D, Anuja E, M. R
Paper cones are used in spinning mills to wrap the yarn. The role of paper cones is dominant in textile industries since it acts as a yarn carrier. The applications of the texcone are extended to automatic, semi-automatic and even manual winders. There are nearly eight major sizes of tex paper cones based on which the yarn with different weights is wrapped. Due to the increasing demand for textile products, there is an elevated need for textile paper cones in the upcoming years. The paper cones produced are printed with inks on its top nose and tapered ends, so as to identify the yarns with various thickness and to pick them easily. Around 4000 plus colour variations are possible to be printed on the edges of the tex cone for easy identification of thread colour and thickness. Many textile industries are demanding custom printing of design on tex cones for yarn identification. customer logos and other unique symbols or signs are printed on paper cones for branding purposes. The most important consideration is to monitor the level of the ink in the ink tray and reservoir. Because in most of the tex cone manufacturing industries, although all the processes of tex cone manufacturing take place automatically, the printing at the edges of the end product is held manually. So, there is a need to ensure the availability of the ink. Once printed wrongly or printed without sufficient ink, the cone will be wasted. Which cost around 3 to 5 Rs per cone. In order to overcome this the suggested model has been developed. The model is created to automate and monitor the ink level. Because of this human intervention is cut down and cone waste is minimized.
{"title":"Automated Ink Level Sensing using Electromechanical System for Tex-Cone Industries","authors":"Mrunalini T, R. P, Geethanjali D, Anuja E, M. R","doi":"10.1109/ICEARS56392.2023.10085459","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085459","url":null,"abstract":"Paper cones are used in spinning mills to wrap the yarn. The role of paper cones is dominant in textile industries since it acts as a yarn carrier. The applications of the texcone are extended to automatic, semi-automatic and even manual winders. There are nearly eight major sizes of tex paper cones based on which the yarn with different weights is wrapped. Due to the increasing demand for textile products, there is an elevated need for textile paper cones in the upcoming years. The paper cones produced are printed with inks on its top nose and tapered ends, so as to identify the yarns with various thickness and to pick them easily. Around 4000 plus colour variations are possible to be printed on the edges of the tex cone for easy identification of thread colour and thickness. Many textile industries are demanding custom printing of design on tex cones for yarn identification. customer logos and other unique symbols or signs are printed on paper cones for branding purposes. The most important consideration is to monitor the level of the ink in the ink tray and reservoir. Because in most of the tex cone manufacturing industries, although all the processes of tex cone manufacturing take place automatically, the printing at the edges of the end product is held manually. So, there is a need to ensure the availability of the ink. Once printed wrongly or printed without sufficient ink, the cone will be wasted. Which cost around 3 to 5 Rs per cone. In order to overcome this the suggested model has been developed. The model is created to automate and monitor the ink level. Because of this human intervention is cut down and cone waste is minimized.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"41 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":"132978424","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}
New statistics show that about 950,000 individuals a year lose their lives to breast carcinoma, making it the deadliest form of cancer worldwide. Early detection and accurate diagnosis of an illness can increase the likelihood of a favorable result, decreasing the mortality rate. Premature victims can be spared if the disease is detected early. Investigators who study cancer face various challenges, including the difficulty of differentiating benign and malignant tumors and the difficulty of classifying mild and metastatic breast cancer. Here, the pattern-recognition algorithms are used to accurately identify every tumor. However, they are all based on the idea of "binary grouping" (malignant and benign). This research made use of different pre-trained networks to speed up the training process. While evaluating the efficacy of the models, many measures were used. By using the images captured during the modeling process, both breasts can be shown together, without having to split them to show the right and left sides. After the data preparation phases, the Ensemble learning model showed the highest classification performance with an accuracy value of 100% when compared to the other pre-trained network models. In this research, thermographic images of breast cancer were used to classify the disease, and the results were combined with experimental data to form a computer-aided diagnosis method. Clinical data is used to validate the models' predictions. After constructing and evaluating two models with distinct designs, the model using the same design performed best, suggesting that the clinical data decisions were essential in improving the model's performance.
{"title":"An Improved Machine Learning and Deep Learning based Breast Cancer Detection using Thermographic Images","authors":"Darani Rajasekhar, Mahammad Rafi D, S. Chandre, Vandana Kate, Jhakeshwar Prasad, Anandbabu Gopatoti","doi":"10.1109/ICEARS56392.2023.10085612","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085612","url":null,"abstract":"New statistics show that about 950,000 individuals a year lose their lives to breast carcinoma, making it the deadliest form of cancer worldwide. Early detection and accurate diagnosis of an illness can increase the likelihood of a favorable result, decreasing the mortality rate. Premature victims can be spared if the disease is detected early. Investigators who study cancer face various challenges, including the difficulty of differentiating benign and malignant tumors and the difficulty of classifying mild and metastatic breast cancer. Here, the pattern-recognition algorithms are used to accurately identify every tumor. However, they are all based on the idea of \"binary grouping\" (malignant and benign). This research made use of different pre-trained networks to speed up the training process. While evaluating the efficacy of the models, many measures were used. By using the images captured during the modeling process, both breasts can be shown together, without having to split them to show the right and left sides. After the data preparation phases, the Ensemble learning model showed the highest classification performance with an accuracy value of 100% when compared to the other pre-trained network models. In this research, thermographic images of breast cancer were used to classify the disease, and the results were combined with experimental data to form a computer-aided diagnosis method. Clinical data is used to validate the models' predictions. After constructing and evaluating two models with distinct designs, the model using the same design performed best, suggesting that the clinical data decisions were essential in improving the model's performance.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"113 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":"134491290","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/ICEARS56392.2023.10085203
Bhavan Kumar S B, Guhan S, Manyam Kishore, S. R, Alfred Daniel J
Potholes can cause serious damage to vehicles and pose a threat to road safety. Pothole detection can help identify and repair hazardous potholes before they cause accidents. Potholes can cause delays and disruptions to traffic flow, leading to increased travel time and reduced efficiency. By detecting and repairing potholes, traffic flow can be improved. Potholes are a sign of wear and tear on roads and can lead to more significant problems if left unaddressed. Early detection and repair of potholes can help prevent further damage to roads and infrastructure, reducing maintenance costs and prolonging the lifespan of the road. Pothole detection and repair can improve the overall condition of roads, providing a smoother and safer driving experience for drivers and passengers. By detecting and repairing potholes in a timely manner, resources can be better allocated, reducing the costs associated with road maintenance and improving efficiency. Henceforth, pothole detection is crucial for ensuring road safety, improving traffic flow, maintaining infrastructure, and optimizing resource allocation.
{"title":"Deep Learning Approach for Pothole Detection - A Systematic Review","authors":"Bhavan Kumar S B, Guhan S, Manyam Kishore, S. R, Alfred Daniel J","doi":"10.1109/ICEARS56392.2023.10085203","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085203","url":null,"abstract":"Potholes can cause serious damage to vehicles and pose a threat to road safety. Pothole detection can help identify and repair hazardous potholes before they cause accidents. Potholes can cause delays and disruptions to traffic flow, leading to increased travel time and reduced efficiency. By detecting and repairing potholes, traffic flow can be improved. Potholes are a sign of wear and tear on roads and can lead to more significant problems if left unaddressed. Early detection and repair of potholes can help prevent further damage to roads and infrastructure, reducing maintenance costs and prolonging the lifespan of the road. Pothole detection and repair can improve the overall condition of roads, providing a smoother and safer driving experience for drivers and passengers. By detecting and repairing potholes in a timely manner, resources can be better allocated, reducing the costs associated with road maintenance and improving efficiency. Henceforth, pothole detection is crucial for ensuring road safety, improving traffic flow, maintaining infrastructure, and optimizing resource allocation.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"37 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":"131876608","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}
Advancement in technology has resulted in birth of critical and complex software. These require thorough testing to ensure production of reliable and high performance software. Testing is the most expensive part of the software life cycle and an estimate of testing efforts can result in smart utilization of resources. Testability is the ease of finding faults in a software and its estimate can reduce costs and increase life of the software. However the area lacks adequate research and standardisation. Current studies majorly report on Object Oriented paradigm and code level testability. This study aims to provide a broader review on Testability metrics, models and establishing relationship between program attributes and testability. Through this survey 29 studies have been selected for analysis. Our studies conclude that testability metrics at code level and design metric corresponding to size are commonly used. Relationships amongst these metrics with their test efforts are established using various machine learning models and presents testability trends with various program attributes. This comprehensive review helps in identifying suitable metric, expected trends with various program attributes and selection of suitable models to automate processes.
{"title":"A Qualitative and Comprehensive Analysis of Software Testability Metrics and their Trends","authors":"Siddhi Purohit, Simran Singh, Mansi Agarwal, Neha Verma","doi":"10.1109/ICEARS56392.2023.10085333","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085333","url":null,"abstract":"Advancement in technology has resulted in birth of critical and complex software. These require thorough testing to ensure production of reliable and high performance software. Testing is the most expensive part of the software life cycle and an estimate of testing efforts can result in smart utilization of resources. Testability is the ease of finding faults in a software and its estimate can reduce costs and increase life of the software. However the area lacks adequate research and standardisation. Current studies majorly report on Object Oriented paradigm and code level testability. This study aims to provide a broader review on Testability metrics, models and establishing relationship between program attributes and testability. Through this survey 29 studies have been selected for analysis. Our studies conclude that testability metrics at code level and design metric corresponding to size are commonly used. Relationships amongst these metrics with their test efforts are established using various machine learning models and presents testability trends with various program attributes. This comprehensive review helps in identifying suitable metric, expected trends with various program attributes and selection of suitable models to automate processes.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"123 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":"133829550","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 the tourism and hotel industry, the Internet of Things (IoT) is recognized for its potential to create new business opportunities. With IoT, the tourism and hospitality industries can leverage technology to enhance customer experiences, streamline operations, and increase profitability. This study analyses 188 articles related to the Internet of Things (IoT) that were published between 2010 and 2022, and sourced from Scopus database. The bibliometric tool "biblioshiny" was used to analyze the data and examine annual publications, authorship, sources, keywords, and citations. Results revealed a significant increase in annual scientific production and the average number of citations per document over the past decade. From 2015 to 2000, keywords like internet, management, model, technology, progress, networks and cities dominated the research. From 2020 onwards, researchers have shown their interest in the keywords of challenges, industry, behavior, big data, system and architecture.
{"title":"Use of Internet of Things in the Tourism and Hospitality Realm: A Descriptive Bibliometric Study using Bibliometrix R - Tool","authors":"Ajit Kumar Singh, Pankaj Kumar Tyagi, Afshan Irshad, Anita Kumari Singh, Priyanka Tyagi, Balraj Benedict","doi":"10.1109/ICEARS56392.2023.10085341","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085341","url":null,"abstract":"In the tourism and hotel industry, the Internet of Things (IoT) is recognized for its potential to create new business opportunities. With IoT, the tourism and hospitality industries can leverage technology to enhance customer experiences, streamline operations, and increase profitability. This study analyses 188 articles related to the Internet of Things (IoT) that were published between 2010 and 2022, and sourced from Scopus database. The bibliometric tool \"biblioshiny\" was used to analyze the data and examine annual publications, authorship, sources, keywords, and citations. Results revealed a significant increase in annual scientific production and the average number of citations per document over the past decade. From 2015 to 2000, keywords like internet, management, model, technology, progress, networks and cities dominated the research. From 2020 onwards, researchers have shown their interest in the keywords of challenges, industry, behavior, big data, system and architecture.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"22 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":"115605113","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/ICEARS56392.2023.10085520
Gokul M, K. R, Arun Prasath T, Anisha M
A technique for capturing the electrical impulses of the stomach is called Electrogastrography (EGG). A visual depiction of the electrical impulses in the stomach is called an electrogastrogram (EGG). A non-invasive, straightforward, and independent approach for identifying stomach dysrhythmias is the EGG. The purpose of the study was to employ the Water Load Test (WLT) to contrast the EGGs of healthy persons and those who had ambiguous stomach discomfort or pain. Fast Fourier Transform (FFT) analysis of the EGG results was used to identify dysrhythmias and contrast the electrical activity of the stomach in healthy and painful subjects. According to the study, normal and pathological activity in the stomach may be distinguished with confidence by changes in average power (1–5) and instantaneous frequency (0.05–0.1 Hz). The study's findings are consistent with cutting-edge methods for anticipating stomach dysrhythmias.
{"title":"Electrogastrogram Analysis of Unclear Stomach Pain","authors":"Gokul M, K. R, Arun Prasath T, Anisha M","doi":"10.1109/ICEARS56392.2023.10085520","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085520","url":null,"abstract":"A technique for capturing the electrical impulses of the stomach is called Electrogastrography (EGG). A visual depiction of the electrical impulses in the stomach is called an electrogastrogram (EGG). A non-invasive, straightforward, and independent approach for identifying stomach dysrhythmias is the EGG. The purpose of the study was to employ the Water Load Test (WLT) to contrast the EGGs of healthy persons and those who had ambiguous stomach discomfort or pain. Fast Fourier Transform (FFT) analysis of the EGG results was used to identify dysrhythmias and contrast the electrical activity of the stomach in healthy and painful subjects. According to the study, normal and pathological activity in the stomach may be distinguished with confidence by changes in average power (1–5) and instantaneous frequency (0.05–0.1 Hz). The study's findings are consistent with cutting-edge methods for anticipating stomach dysrhythmias.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"46 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":"115785100","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/ICEARS56392.2023.10085271
Maithili P, K. R, Shanthi T, Sadhana S, G. U, Giridharan R
The battery is the primary energy source to be monitored in electric vehicles and their healthy operation. This study analyzes the parameters of lead acid battery. Since Lead Acid (LA) is less efficient than lithium-ion, Lead acid is preferred in power storage systems for its large current capability, cost efficiency and convenience usage. Lead acid batteries are widely used in power storage devices like UPS grid-scale power systems. This paper explains about the battery monitoring system of lead acid in real time aspects. Also, to monitor the discharging rate of lead acid batteries and accomplish self-discharging if needed. Batteries lifetime depends on both charging and discharging. So self-discharging is proposed in this paper to increase the lifetime of battery. SOC and SOD estimation is simulated by using MATLAB Simulink. In addition to this, the development of microcontroller programming for lead acid battery life is performed. Thus, the lifetime of battery can be extended. Here the proposed solution will not only increase the life span but also increases the efficiency of the battery and its operation. The SOC estimation is done using Extended Kalman Filter (EKF) method which is advanced to Coulomb’s counting method. By comparing and using these techniques, the efficient values are plotted and used for analysis. Thus, this paper focuses only on the simulation of the main parameters involved in the battery monitoring system.
{"title":"An Improved Automotive Battery Monitoring System","authors":"Maithili P, K. R, Shanthi T, Sadhana S, G. U, Giridharan R","doi":"10.1109/ICEARS56392.2023.10085271","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085271","url":null,"abstract":"The battery is the primary energy source to be monitored in electric vehicles and their healthy operation. This study analyzes the parameters of lead acid battery. Since Lead Acid (LA) is less efficient than lithium-ion, Lead acid is preferred in power storage systems for its large current capability, cost efficiency and convenience usage. Lead acid batteries are widely used in power storage devices like UPS grid-scale power systems. This paper explains about the battery monitoring system of lead acid in real time aspects. Also, to monitor the discharging rate of lead acid batteries and accomplish self-discharging if needed. Batteries lifetime depends on both charging and discharging. So self-discharging is proposed in this paper to increase the lifetime of battery. SOC and SOD estimation is simulated by using MATLAB Simulink. In addition to this, the development of microcontroller programming for lead acid battery life is performed. Thus, the lifetime of battery can be extended. Here the proposed solution will not only increase the life span but also increases the efficiency of the battery and its operation. The SOC estimation is done using Extended Kalman Filter (EKF) method which is advanced to Coulomb’s counting method. By comparing and using these techniques, the efficient values are plotted and used for analysis. Thus, this paper focuses only on the simulation of the main parameters involved in the battery monitoring system.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"48 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":"124413288","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/ICEARS56392.2023.10085608
Chairma Lakshmi K R, Gnanasekaran Thangavel, Kalai Chelvan V, Aadithya V, Julian Devapiriyam R K
In metropolitan areas, there is an uneven distribution of sunlight due to building structures, pollution, etc. The solar panel can perform optimally under standard testing conditions only. Due to the dynamic solar irradiation and environmental temperature variation, the solar panel can't operate optimally. As a result of temperature changes, solar panels lose up to 10% of their efficiency. This article aims to improve solar panel efficiency by reducing the solar panel’s temperature using acrylic optical filters. In this research, an Experimental investigation was conducted with a 20 W solar panel. Transparent acrylic box filters with a coolant setup are used to increase the efficiency of the solar panel. Transparent colour optical filters reduce the unwanted infrared radiation from solar irradiation. Through the use of optical acrylic filters surmounted on top of the solar panel, the PV panel’s output power increased by reducing the solar panel temperature. As a result, the temperature of the solar panel reduces which enriches its efficiency of the solar panel. A comparative Analysis of solar panel efficiency and power is carried out with and without coolant in the optical acrylic filters. From the experimental results, it can be concluded that the pink-coloured acrylic sheet with water coolant performed most efficiently when compared to other colours There was an approximately 11% increase in the panel efficiency.
{"title":"A Study of the Effect of Optical Filters on the Performance of Solar Panel","authors":"Chairma Lakshmi K R, Gnanasekaran Thangavel, Kalai Chelvan V, Aadithya V, Julian Devapiriyam R K","doi":"10.1109/ICEARS56392.2023.10085608","DOIUrl":"https://doi.org/10.1109/ICEARS56392.2023.10085608","url":null,"abstract":"In metropolitan areas, there is an uneven distribution of sunlight due to building structures, pollution, etc. The solar panel can perform optimally under standard testing conditions only. Due to the dynamic solar irradiation and environmental temperature variation, the solar panel can't operate optimally. As a result of temperature changes, solar panels lose up to 10% of their efficiency. This article aims to improve solar panel efficiency by reducing the solar panel’s temperature using acrylic optical filters. In this research, an Experimental investigation was conducted with a 20 W solar panel. Transparent acrylic box filters with a coolant setup are used to increase the efficiency of the solar panel. Transparent colour optical filters reduce the unwanted infrared radiation from solar irradiation. Through the use of optical acrylic filters surmounted on top of the solar panel, the PV panel’s output power increased by reducing the solar panel temperature. As a result, the temperature of the solar panel reduces which enriches its efficiency of the solar panel. A comparative Analysis of solar panel efficiency and power is carried out with and without coolant in the optical acrylic filters. From the experimental results, it can be concluded that the pink-coloured acrylic sheet with water coolant performed most efficiently when compared to other colours There was an approximately 11% increase in the panel efficiency.","PeriodicalId":338611,"journal":{"name":"2023 Second International Conference on Electronics and Renewable Systems (ICEARS)","volume":"51 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":"114779599","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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