Pub Date : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10117738
Keshav, Sangeeta Rani
The “Big Data” phrase describes to the management of a wide range of organized and unstructured data with increasing speed and quantity. These datasets are conventional, large, and difficult to maintain. However, these datasets are used within a number of companies to perform various tasks on them as well as for organizational purposes and to provide a summary of the data currently being used. More precise and accurate business judgments can be make as a result of the growing volume of big data, which is now more affordable and available. The objective of this research paper is to demonstrate how to identify and use only the most significant and important data to be used in a follow-up investigation, help other researchers perform additional analysis, take into account only a limited number of data, ensuring that the study will always provide the best results. Although there are other methods and tools to extract data with certain filters. MongoDB uses the NoSQL model as the basis for query processing. To obtain data from a large data collection, query processing is used and it will continue to play an important role in future research and strategies for this work. The behaviour of extraction of data from Big Data and query processing on the bases input parameters that are going to use in Machine Learning. This process also termed as Data Mining which will show the behaviour of mining data from large amount of combine data. This paper show the behaviour implementation of Mongo DB on required parameter and will produce the efficient result.
{"title":"Big Data Query Processing Approach UsingMongoDB","authors":"Keshav, Sangeeta Rani","doi":"10.1109/ICIPTM57143.2023.10117738","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10117738","url":null,"abstract":"The “Big Data” phrase describes to the management of a wide range of organized and unstructured data with increasing speed and quantity. These datasets are conventional, large, and difficult to maintain. However, these datasets are used within a number of companies to perform various tasks on them as well as for organizational purposes and to provide a summary of the data currently being used. More precise and accurate business judgments can be make as a result of the growing volume of big data, which is now more affordable and available. The objective of this research paper is to demonstrate how to identify and use only the most significant and important data to be used in a follow-up investigation, help other researchers perform additional analysis, take into account only a limited number of data, ensuring that the study will always provide the best results. Although there are other methods and tools to extract data with certain filters. MongoDB uses the NoSQL model as the basis for query processing. To obtain data from a large data collection, query processing is used and it will continue to play an important role in future research and strategies for this work. The behaviour of extraction of data from Big Data and query processing on the bases input parameters that are going to use in Machine Learning. This process also termed as Data Mining which will show the behaviour of mining data from large amount of combine data. This paper show the behaviour implementation of Mongo DB on required parameter and will produce the efficient result.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131799749","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10118192
R. Raman, T. Inbamalar, N. Pushpalatha, S. Meenakshi, Ashok Kumar, S. Razia, N. Gopinath
Arthritis is a bone disorder that includes swelling and pain in one or more joints. Everyone can develop osteoarthritis, but it grows more common as individuals get older. When arthritis deteriorates over time, it can lead to persistent pain, making it challenging to do daily tasks, and making activities like walking and climbing stairs painful and difficult. If arthritis is correctly identified and treated in its early stages, these consequences can be avoided. The goal of this project is to create two transfer learning models that, by spotting arthritis in its earliest stages, can lower the likelihood of acquiring chronic arthritis. For this purpose, Google served as the source of the images used in this study. After being purchased from Google, the data collection is preprocessed using three different methods. Image scaling, noise reduction, and image enhancement are a few of the pre-processing approaches. The transfer learning models are trained and assessed using this preprocessed dataset. In this work, two distinct transfer learning models are established. The models include SegNet and ENet. On a graph, the outcomes for the performances of both models are displayed. The training data from the first few epochs of the ENet model and SegNet model are also used in the analysis. The models' final accuracy and loss values are then assessed. In the end, it was discovered that the SegNet model had a lower loss value and more accuracy than the other. The model created in this study can be utilised as a preliminary test for arthritis when a person exhibits moderate arthritis symptoms because the final accuracy of the model is higher than or equal to 95%.
{"title":"Transfer Learning for Hand Arthritis Prediction from X-Ray Images","authors":"R. Raman, T. Inbamalar, N. Pushpalatha, S. Meenakshi, Ashok Kumar, S. Razia, N. Gopinath","doi":"10.1109/ICIPTM57143.2023.10118192","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10118192","url":null,"abstract":"Arthritis is a bone disorder that includes swelling and pain in one or more joints. Everyone can develop osteoarthritis, but it grows more common as individuals get older. When arthritis deteriorates over time, it can lead to persistent pain, making it challenging to do daily tasks, and making activities like walking and climbing stairs painful and difficult. If arthritis is correctly identified and treated in its early stages, these consequences can be avoided. The goal of this project is to create two transfer learning models that, by spotting arthritis in its earliest stages, can lower the likelihood of acquiring chronic arthritis. For this purpose, Google served as the source of the images used in this study. After being purchased from Google, the data collection is preprocessed using three different methods. Image scaling, noise reduction, and image enhancement are a few of the pre-processing approaches. The transfer learning models are trained and assessed using this preprocessed dataset. In this work, two distinct transfer learning models are established. The models include SegNet and ENet. On a graph, the outcomes for the performances of both models are displayed. The training data from the first few epochs of the ENet model and SegNet model are also used in the analysis. The models' final accuracy and loss values are then assessed. In the end, it was discovered that the SegNet model had a lower loss value and more accuracy than the other. The model created in this study can be utilised as a preliminary test for arthritis when a person exhibits moderate arthritis symptoms because the final accuracy of the model is higher than or equal to 95%.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133229986","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10118329
R. Mohandas, Aishwarya Vh, Akshatha Shree S, A. S, Khushi J
The extension of transportation networks has sped up the speed of our lives. Car crashes cause a significant measure of death, property harm, and inestimable time, which is a significant worldwide medical condition. It is viewed as one of the essential executioners in the advanced world. The plan of a savvy mishap identification, area following, and cautioning framework that can detect mishaps as they happen is shrouded in this article. To find the mishap's definite area, a GPS device is utilized. The Worldwide Framework for Versatile (GSM) module sends a notification message that remembers a connection to the mishap's area for a Google guide to the nearby emergency clinic and police control focus. They can do whatever it may take to facilitate the salvage exertion by visiting the connection to find where the mishap is in the area.
{"title":"Implementation of Accident Detection and Reporting System Using IOT","authors":"R. Mohandas, Aishwarya Vh, Akshatha Shree S, A. S, Khushi J","doi":"10.1109/ICIPTM57143.2023.10118329","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10118329","url":null,"abstract":"The extension of transportation networks has sped up the speed of our lives. Car crashes cause a significant measure of death, property harm, and inestimable time, which is a significant worldwide medical condition. It is viewed as one of the essential executioners in the advanced world. The plan of a savvy mishap identification, area following, and cautioning framework that can detect mishaps as they happen is shrouded in this article. To find the mishap's definite area, a GPS device is utilized. The Worldwide Framework for Versatile (GSM) module sends a notification message that remembers a connection to the mishap's area for a Google guide to the nearby emergency clinic and police control focus. They can do whatever it may take to facilitate the salvage exertion by visiting the connection to find where the mishap is in the area.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"364 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121380583","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10118005
R. Chowdary, C. Priyadarsini, V. J. Reddy, P. Devi, A. Chandrakanth, T. N. Aditya
This paper proposes an EH-WSN multi-hop (MH) cluster routing protocol (Energy-balanced MH cluster routing, EBMCR) to obtain solar energy, to achieve network energy balance during intra-cluster transmission and inter-cluster transmission. The main contributions of this paper are as the protocol balances the energy consumption (EC) of cluster head (C-H)nodes in different units by dividing the network area, calculates the number of nodes in each unit according to mathematical derivation, and minimizes the total EC of Tdata, improve the HEED C-H selection method, select the node with high energy distribution and neighbor distribution weight in the unit as the C-H, and effectively balance the EC of the nodes in the cluster, based on the PSO algorithm, the inter-cluster routing strategy is designed to improve the energy efficiency of Tdata, ensure the energy balance of nodes on the transmission path, and avoid nodes with lower energy being selected as routing nodes.
{"title":"Solar Powered Sensors for Efficient Routing without Power Constraints","authors":"R. Chowdary, C. Priyadarsini, V. J. Reddy, P. Devi, A. Chandrakanth, T. N. Aditya","doi":"10.1109/ICIPTM57143.2023.10118005","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10118005","url":null,"abstract":"This paper proposes an EH-WSN multi-hop (MH) cluster routing protocol (Energy-balanced MH cluster routing, EBMCR) to obtain solar energy, to achieve network energy balance during intra-cluster transmission and inter-cluster transmission. The main contributions of this paper are as the protocol balances the energy consumption (EC) of cluster head (C-H)nodes in different units by dividing the network area, calculates the number of nodes in each unit according to mathematical derivation, and minimizes the total EC of Tdata, improve the HEED C-H selection method, select the node with high energy distribution and neighbor distribution weight in the unit as the C-H, and effectively balance the EC of the nodes in the cluster, based on the PSO algorithm, the inter-cluster routing strategy is designed to improve the energy efficiency of Tdata, ensure the energy balance of nodes on the transmission path, and avoid nodes with lower energy being selected as routing nodes.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121557367","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10118353
L. T, Tammineni Sreelatha, S. Chaudhary, R. Mapari, Janardhan Saikumar, Harshal Patil
In this analysis, the brain tumour is described through an experimental diagnostic procedure. For the identification of brain tumours, the magnetic resonance picture is called. 2% of the body weight is absorbed by the human brain. For the MRI-based brain tumour diagnosis, The CT scan image typically favours magnetic resonance images. While in multiple segmentation approaches occur, the water source is helpful to identify the zone of special concern. Of importance. The map of the horizontal and vertical areas reveals a highly successful and realistic approach.
{"title":"Brain tumour edge detection by segmentation technique","authors":"L. T, Tammineni Sreelatha, S. Chaudhary, R. Mapari, Janardhan Saikumar, Harshal Patil","doi":"10.1109/ICIPTM57143.2023.10118353","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10118353","url":null,"abstract":"In this analysis, the brain tumour is described through an experimental diagnostic procedure. For the identification of brain tumours, the magnetic resonance picture is called. 2% of the body weight is absorbed by the human brain. For the MRI-based brain tumour diagnosis, The CT scan image typically favours magnetic resonance images. While in multiple segmentation approaches occur, the water source is helpful to identify the zone of special concern. Of importance. The map of the horizontal and vertical areas reveals a highly successful and realistic approach.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128577902","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10118132
Neeti Pal, Omdev Dahiya
Recommender System was widely used in commercial websites for the past few years. These systems track past activities of customers and recommend them the relevant items. The emergence of E-learning activities over a few decades develops a variety of E-learning content available for virtual learning environments (VLE). A large amount of learning objects is present in E-learning repositories. Dealing with problems of the diversity of data, Educational Recommender System (ERS) plays a vital role in the educational sector. Educational recommender systems track the learners' past activities, know the users' preferences, assist the educators and learners, provide relevant content to learners, and enhance their learning outcomes. A personalized recommender system will intensify the learners' interest in particular content and reduce the course dropout rate. The recommender system makes the decision-making process for choosing the appropriate content easy for learners. ERS uses various approaches and technologies for assisting the learners' and helps them to run their learning process smoothly. Collaborative filtering, Content-based, and knowledge-based are the basic techniques of recommender systems. The research shows that a combination of these approaches will give more effective and efficient results. This mixing of approaches refers to the hybridization techniques. Traditional approaches with deep learning networks will improve the recommendations and provide results with higher accuracy. This paper provides how E-learning support recommender systems produce recommendations using different techniques. The technical results of recommender techniques help to find the best approach for making a recommender system in the future.
{"title":"Analysis of Educational Recommender System Techniques for Enhancing Student's Learning Outcomes","authors":"Neeti Pal, Omdev Dahiya","doi":"10.1109/ICIPTM57143.2023.10118132","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10118132","url":null,"abstract":"Recommender System was widely used in commercial websites for the past few years. These systems track past activities of customers and recommend them the relevant items. The emergence of E-learning activities over a few decades develops a variety of E-learning content available for virtual learning environments (VLE). A large amount of learning objects is present in E-learning repositories. Dealing with problems of the diversity of data, Educational Recommender System (ERS) plays a vital role in the educational sector. Educational recommender systems track the learners' past activities, know the users' preferences, assist the educators and learners, provide relevant content to learners, and enhance their learning outcomes. A personalized recommender system will intensify the learners' interest in particular content and reduce the course dropout rate. The recommender system makes the decision-making process for choosing the appropriate content easy for learners. ERS uses various approaches and technologies for assisting the learners' and helps them to run their learning process smoothly. Collaborative filtering, Content-based, and knowledge-based are the basic techniques of recommender systems. The research shows that a combination of these approaches will give more effective and efficient results. This mixing of approaches refers to the hybridization techniques. Traditional approaches with deep learning networks will improve the recommendations and provide results with higher accuracy. This paper provides how E-learning support recommender systems produce recommendations using different techniques. The technical results of recommender techniques help to find the best approach for making a recommender system in the future.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129255553","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10117946
A. K. Agarwal, Meenakshi Kaul, Saurabh Chandra, Shailender Singh, Adit Gupta
This study looks at the link between organizational justice as seen by employees, job conscientiousness, and social responsibility in the context of private bank employees. The study's cross-sectional design method looked at workers with less than one year of experience. Participants answered standardized questionnaires to assess their views on social responsibility, job conscientiousness, and organizational justice. Regression analysis is done on the data. Social responsibility, work ethics, and organizational fairness. According to our findings, substantial link between organizational justice and social responsibility and job conscientiousness. These results led the study's authors to advise bank managers to modify their management procedures in order to lessen emotions of authoritarianism and to take proactive measures to improve employee productivity in the long term.
{"title":"The Influence of Fair Treatment in the Workplace on Employee Diligence and Corporate Social Responsibility: A Viewpoint from the Banking Industry","authors":"A. K. Agarwal, Meenakshi Kaul, Saurabh Chandra, Shailender Singh, Adit Gupta","doi":"10.1109/ICIPTM57143.2023.10117946","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10117946","url":null,"abstract":"This study looks at the link between organizational justice as seen by employees, job conscientiousness, and social responsibility in the context of private bank employees. The study's cross-sectional design method looked at workers with less than one year of experience. Participants answered standardized questionnaires to assess their views on social responsibility, job conscientiousness, and organizational justice. Regression analysis is done on the data. Social responsibility, work ethics, and organizational fairness. According to our findings, substantial link between organizational justice and social responsibility and job conscientiousness. These results led the study's authors to advise bank managers to modify their management procedures in order to lessen emotions of authoritarianism and to take proactive measures to improve employee productivity in the long term.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126186149","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10118194
V. V. Chellam, S. Praveenkumar, Suryansh Talukdar, Veera Talukdar, Sanjiv Kumar Jain, Ankur Gupta
Although blockchain technology was first created to manage financial ledgers, it has lately found use in a wide range of industries, including healthcare. Research innovation in this area will be boosted by the sharing of healthcare data. Nevertheless, patients who disclose their medical records face several privacy and security concerns. Here, the authors propose a blockchain-dependent system architectural design to demonstrate the prospect of blockchain technology in supporting (i) personal and examined medical data exchange and (ii) medical data access authorization processing.
{"title":"Development of a Blockchain-based Platform to Simplify the Sharing of Patient Data","authors":"V. V. Chellam, S. Praveenkumar, Suryansh Talukdar, Veera Talukdar, Sanjiv Kumar Jain, Ankur Gupta","doi":"10.1109/ICIPTM57143.2023.10118194","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10118194","url":null,"abstract":"Although blockchain technology was first created to manage financial ledgers, it has lately found use in a wide range of industries, including healthcare. Research innovation in this area will be boosted by the sharing of healthcare data. Nevertheless, patients who disclose their medical records face several privacy and security concerns. Here, the authors propose a blockchain-dependent system architectural design to demonstrate the prospect of blockchain technology in supporting (i) personal and examined medical data exchange and (ii) medical data access authorization processing.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114479787","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10117728
K. V. Ramana, S. Arulkumar, Asmita Marathe, Kedir Beshir, V. Jaiganesh, K. Tamilselvi, M. Sudhakar
Our main focus was on creating a Two directional power converter for a standalone photo-voltaic energy-generating technology as well as technology energy control when a lead-acid energy storage device is used to control the energy supply. We utilized a light bulb as the load to evaluate the effectiveness of the directional power converter developed as part of our project as well as the functionality of energy control technologies. The suggested technology was composed of an energy control technology, a lead-acid battery, a bulb, a two-directional buck-boost converter, an utmost power point tracking controller, and these components. An energy control technique was developed to grow the rate at which the Photo-voltaic power producing technology consumed energy. The circuits are intended to charge the battery between upper and lower voltage limits, as well as to continuously check the battery's state of charge and add or release current as necessary. The bidirectional buck-boost converter's ability to function as a charge controller on its own, along with the use of particular BUCK and BOOST converter properties to optimize the home application, is the primary distinction between the method used in the proposed technology and other techniques used in the past. The battery is charged and discharged using a bidirectional dc-dc converter. Measurement data are employed to support the viability of a photovoltaic air conditioning technology.
{"title":"Design and Implementation of Renewable Energy Applications Based Bi-Directional Buck-Boost Converter","authors":"K. V. Ramana, S. Arulkumar, Asmita Marathe, Kedir Beshir, V. Jaiganesh, K. Tamilselvi, M. Sudhakar","doi":"10.1109/ICIPTM57143.2023.10117728","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10117728","url":null,"abstract":"Our main focus was on creating a Two directional power converter for a standalone photo-voltaic energy-generating technology as well as technology energy control when a lead-acid energy storage device is used to control the energy supply. We utilized a light bulb as the load to evaluate the effectiveness of the directional power converter developed as part of our project as well as the functionality of energy control technologies. The suggested technology was composed of an energy control technology, a lead-acid battery, a bulb, a two-directional buck-boost converter, an utmost power point tracking controller, and these components. An energy control technique was developed to grow the rate at which the Photo-voltaic power producing technology consumed energy. The circuits are intended to charge the battery between upper and lower voltage limits, as well as to continuously check the battery's state of charge and add or release current as necessary. The bidirectional buck-boost converter's ability to function as a charge controller on its own, along with the use of particular BUCK and BOOST converter properties to optimize the home application, is the primary distinction between the method used in the proposed technology and other techniques used in the past. The battery is charged and discharged using a bidirectional dc-dc converter. Measurement data are employed to support the viability of a photovoltaic air conditioning technology.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121281220","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 : 2023-02-22DOI: 10.1109/ICIPTM57143.2023.10118290
Narendra Kumar Jha, P. Shukla
Plants are one of the core components of human life and its surrounding environment. Various diseases not only diminish the ecological relevance of plants and the products they produce but also have an impact on their economic value. The main goal of this study is to identify plant kinds and design a suitable and effective method for judging a plant's healthiness based on pictures of its leaves in order to give a workable system for an instant and economical solution to this problem. The analysis of both biotic and abiotic elements that affect a plant's general health is known as plant pathology. Farmers must identify the issue quickly in order to take appropriate measures and stop additional losses. Consequently, it is recommended for this study to use a Deep Convolutional Neural Network (DCNN) to categorise damaged leaves. A genuine dataset of 4503 images of the 12 diverse tree leaves that were gathered at the “Shri Mata Vaishno Devi University in Katra, J&K, India”, is used to verify this work. Both healthy and unhealthy leaf photos are taken in the dataset that belongs to the 12 different plants type. The result found after testing the model was quite good. The suggested DCNN model will have greater classification accuracy and able to classify the plant type of the leaves as well as the model can also predict whether the leaf is healthy or unhealthy.
植物是人类生命及其周围环境的核心组成部分之一。各种病害不仅降低了植物及其产品的生态价值，而且影响了它们的经济价值。本研究的主要目的是对植物种类进行识别，并设计一种适合的、有效的基于叶片图片的植物健康状况判断方法，从而为快速、经济地解决这一问题提供一个可行的系统。对影响植物整体健康的生物和非生物元素的分析被称为植物病理学。农民必须迅速发现问题，以便采取适当的措施，防止更多的损失。因此，本研究建议使用深度卷积神经网络(DCNN)对受损叶片进行分类。一个真实的数据集，包含4503张12种不同树叶的图像，这些图像是在“印度查查克什米尔Katra的Shri Mata Vaishno Devi大学”收集的，用于验证这项工作。健康和不健康的叶子照片都在属于12种不同植物类型的数据集中拍摄。经过测试，发现该模型效果良好。建议的DCNN模型具有更高的分类精度，能够对叶子的植物类型进行分类，并且可以预测叶子是健康的还是不健康的。
{"title":"Classification and Health Prediction in Plants Using Deep Convolutional Neural Networks","authors":"Narendra Kumar Jha, P. Shukla","doi":"10.1109/ICIPTM57143.2023.10118290","DOIUrl":"https://doi.org/10.1109/ICIPTM57143.2023.10118290","url":null,"abstract":"Plants are one of the core components of human life and its surrounding environment. Various diseases not only diminish the ecological relevance of plants and the products they produce but also have an impact on their economic value. The main goal of this study is to identify plant kinds and design a suitable and effective method for judging a plant's healthiness based on pictures of its leaves in order to give a workable system for an instant and economical solution to this problem. The analysis of both biotic and abiotic elements that affect a plant's general health is known as plant pathology. Farmers must identify the issue quickly in order to take appropriate measures and stop additional losses. Consequently, it is recommended for this study to use a Deep Convolutional Neural Network (DCNN) to categorise damaged leaves. A genuine dataset of 4503 images of the 12 diverse tree leaves that were gathered at the “Shri Mata Vaishno Devi University in Katra, J&K, India”, is used to verify this work. Both healthy and unhealthy leaf photos are taken in the dataset that belongs to the 12 different plants type. The result found after testing the model was quite good. The suggested DCNN model will have greater classification accuracy and able to classify the plant type of the leaves as well as the model can also predict whether the leaf is healthy or unhealthy.","PeriodicalId":178817,"journal":{"name":"2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122916364","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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