Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10046704
Khyati, Ashendra Kumar Saxena
In this paper, an EOQ model is developed to construct the optimal ordering policies for the inventory system which have the deteriorating items follows the two-parameter Weibull distribution. The demand parameter is considered as time dependent demand and shortages are allowed in this study. In order to determine the best values for the order quantity, total cost, and replenishment time, the problem was analytically solved.
{"title":"An EOQ Model for Deteriorating Items with Time Dependent Demand","authors":"Khyati, Ashendra Kumar Saxena","doi":"10.1109/SMART55829.2022.10046704","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046704","url":null,"abstract":"In this paper, an EOQ model is developed to construct the optimal ordering policies for the inventory system which have the deteriorating items follows the two-parameter Weibull distribution. The demand parameter is considered as time dependent demand and shortages are allowed in this study. In order to determine the best values for the order quantity, total cost, and replenishment time, the problem was analytically solved.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115902224","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047207
Pallavi Shetty, M. Kumar, Tushar Vyas, Angulakshmi M, A. Gehlot, Kumud Pant
Utilizing digital technology to control technical processes reduces the need for physical labor and increases worker productivity. The optimization of automated specified conditions based on digital technologies is one of the primary avenues of progress in information technology. Among the key areas of study nowadays is improving the data dependability of controllers. The creation of procedures for data The use of network technology for storing, processing, and moving data is a result of the significant growth in the flow of data in the present information and globalization era. As a consequence, the trustworthiness of the data in this network security is becoming a bigger issue. Increasing data dependability based on security is a pressing issue nowadays. Developed around the turn of the century, blockchain technology offers a fresh method for protecting data in network security. Blockchain prioritizes the inclusion of a cryptographically chain in its architecture. This work focused on enhancing cryptographic methods and cryptographic strength evaluation using blockchain-based processes. The blockchain engine has been used to enhance the contemporary RSA6 cryptographic technique, and the D RSA6 algorithms has been created. Analyses and tests have been done on the D RSA6 algorithm's cryptographic security. It has been shown that the best method for improving the correctness of network system data is the designed algorithm D RSA6. The approach, which is based on combining cryptographic methods with blockchain technology, increases tolerance for cryptocurrencies by a factor of two. This enables you to improve the data's dependability.
{"title":"Application of Cryptographic Methods to Blockchain Technology to Increase Data Reliability","authors":"Pallavi Shetty, M. Kumar, Tushar Vyas, Angulakshmi M, A. Gehlot, Kumud Pant","doi":"10.1109/SMART55829.2022.10047207","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047207","url":null,"abstract":"Utilizing digital technology to control technical processes reduces the need for physical labor and increases worker productivity. The optimization of automated specified conditions based on digital technologies is one of the primary avenues of progress in information technology. Among the key areas of study nowadays is improving the data dependability of controllers. The creation of procedures for data The use of network technology for storing, processing, and moving data is a result of the significant growth in the flow of data in the present information and globalization era. As a consequence, the trustworthiness of the data in this network security is becoming a bigger issue. Increasing data dependability based on security is a pressing issue nowadays. Developed around the turn of the century, blockchain technology offers a fresh method for protecting data in network security. Blockchain prioritizes the inclusion of a cryptographically chain in its architecture. This work focused on enhancing cryptographic methods and cryptographic strength evaluation using blockchain-based processes. The blockchain engine has been used to enhance the contemporary RSA6 cryptographic technique, and the D RSA6 algorithms has been created. Analyses and tests have been done on the D RSA6 algorithm's cryptographic security. It has been shown that the best method for improving the correctness of network system data is the designed algorithm D RSA6. The approach, which is based on combining cryptographic methods with blockchain technology, increases tolerance for cryptocurrencies by a factor of two. This enables you to improve the data's dependability.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117026405","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047757
Tarandeep Kaur Bhatia, Sona Tyagi, Aayushman Gusain, K. Sharma
Unmanned aerial vehicle (UAV) systems have gained extensive attention as open up new possibilities for special forces and military observations. However, research challenges and new solutions for the operation of UAVs need to be understood in better way so as develop adaptable and adjustable UAVs. In present piece of review, we report advantages of multiple UAV systems, classification of various types of Ad-Hoc networks, challenges in Ad-Hoc networks, routing protocols of Flying Ad-Hoc Network (FANET), and mobility models of FANETS. The review mainly focusses on important FANET design concerns. Moreover, comparison of FANET Ad-Hoc network has been made with Vehicular Ad-Hoc network as well as Mobile Ad-Hoc network in terms of speed, density and energy consumption etc. The information provided in this review will help the reader to understand the intricacies of UAV systems.
{"title":"A Study on the Flying Ad-hoc Networks: Related Challenges, Routing Protocols and Mobility Models","authors":"Tarandeep Kaur Bhatia, Sona Tyagi, Aayushman Gusain, K. Sharma","doi":"10.1109/SMART55829.2022.10047757","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047757","url":null,"abstract":"Unmanned aerial vehicle (UAV) systems have gained extensive attention as open up new possibilities for special forces and military observations. However, research challenges and new solutions for the operation of UAVs need to be understood in better way so as develop adaptable and adjustable UAVs. In present piece of review, we report advantages of multiple UAV systems, classification of various types of Ad-Hoc networks, challenges in Ad-Hoc networks, routing protocols of Flying Ad-Hoc Network (FANET), and mobility models of FANETS. The review mainly focusses on important FANET design concerns. Moreover, comparison of FANET Ad-Hoc network has been made with Vehicular Ad-Hoc network as well as Mobile Ad-Hoc network in terms of speed, density and energy consumption etc. The information provided in this review will help the reader to understand the intricacies of UAV systems.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114742130","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047040
Supriya Kumari, Neeraj Kumari, Nuparam
Agriculture is very important in India since it is a growing nation. Nearly six-in-ten individuals living in rural areas of India rely on farming for their livelihood. As one of the world's most popular produce items, tomatoes play a vital role in many people's daily meals. Therefore, identifying and classifying any diseases a tomato plant may have is essential for preventing substantial loss in tomato quantity and production. Such problems are addressed using cutting-edge tech by employing a broad range of approaches and techniques, such as image processing. As with many other plants, a tomato plant's leaves are the first to exhibit signs of a disease. Four steps were used in the research to narrow down the potential illness types. There are four steps total: data cleansing/preprocessing, leaf segmentation, feature extraction, and classification. First, we utilise picture preprocessing to get rid of any distracting backgrounds, and then we use image segmentation to single out the areas of the leaf that took the brunt of the impact. It is possible to employ the supervised, complex machine learning method known as a Convolutional Neural Network (CNN) to find solutions to classification and regression issues. If the user has reached this stage, they should seek help. Diseases have the most devastating impact on plant life. This research demonstrates how image processing may be used to detect flaws in tomato plants by examining images of the affected leaves.
{"title":"Plant Leaf Disease Identification using Machine Learning","authors":"Supriya Kumari, Neeraj Kumari, Nuparam","doi":"10.1109/SMART55829.2022.10047040","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047040","url":null,"abstract":"Agriculture is very important in India since it is a growing nation. Nearly six-in-ten individuals living in rural areas of India rely on farming for their livelihood. As one of the world's most popular produce items, tomatoes play a vital role in many people's daily meals. Therefore, identifying and classifying any diseases a tomato plant may have is essential for preventing substantial loss in tomato quantity and production. Such problems are addressed using cutting-edge tech by employing a broad range of approaches and techniques, such as image processing. As with many other plants, a tomato plant's leaves are the first to exhibit signs of a disease. Four steps were used in the research to narrow down the potential illness types. There are four steps total: data cleansing/preprocessing, leaf segmentation, feature extraction, and classification. First, we utilise picture preprocessing to get rid of any distracting backgrounds, and then we use image segmentation to single out the areas of the leaf that took the brunt of the impact. It is possible to employ the supervised, complex machine learning method known as a Convolutional Neural Network (CNN) to find solutions to classification and regression issues. If the user has reached this stage, they should seek help. Diseases have the most devastating impact on plant life. This research demonstrates how image processing may be used to detect flaws in tomato plants by examining images of the affected leaves.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"03 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127176722","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10046772
Ranjana Sharma, S. Bharadwaj, Sarthika Dutt, Mayank Tomar
In the present scenarios, we can observe how the world is changing with computers, and the thing which plays the best role is ‘Robots’. So, in this article, we have mentioned how robots will change the world with new technologies and a newly introduced concept by the present engineers: Robotic Process Automation. RPA is the technology that is replacing humans with computers or programmed bots to mimic human actions to perform several tasks. There is currently little scholarly literature on the issue. As a result, the goal of this paper is to analyze how the academic community defines RPA and how far it has been researched in the literature in terms of the status, trends, and application of RPA. There is also a discussion of the distinction between RPA and business process management. To that goal, the Web of Science and Scopus databases were used to conduct a systematic literature review (SLR). The article summarises the results of an SLR on RPA, providing a review of RPA ideas and practical implementations, as well as the benefits of its adoption in various industries.
在目前的场景中，我们可以观察到世界是如何随着计算机而变化的，而扮演最好角色的是“机器人”。因此，在本文中，我们提到了机器人将如何通过新技术和当前工程师引入的新概念来改变世界:机器人过程自动化。RPA是一种用计算机或编程机器人代替人类来模仿人类行为来执行多项任务的技术。目前关于这个问题的学术文献很少。因此，本文的目的是分析学术界如何定义RPA，以及在RPA的现状、趋势和应用方面，文献中对RPA的研究程度。本文还讨论了RPA和业务流程管理之间的区别。为此，我们使用Web of Science和Scopus数据库进行了系统的文献综述(SLR)。本文总结了基于RPA的单反研究的结果，提供了RPA思想和实际实现的回顾，以及在各个行业中采用RPA的好处。
{"title":"Robotic Advancements in Business Process Automation using Artificial Intelligence: An Investigative Study","authors":"Ranjana Sharma, S. Bharadwaj, Sarthika Dutt, Mayank Tomar","doi":"10.1109/SMART55829.2022.10046772","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046772","url":null,"abstract":"In the present scenarios, we can observe how the world is changing with computers, and the thing which plays the best role is ‘Robots’. So, in this article, we have mentioned how robots will change the world with new technologies and a newly introduced concept by the present engineers: Robotic Process Automation. RPA is the technology that is replacing humans with computers or programmed bots to mimic human actions to perform several tasks. There is currently little scholarly literature on the issue. As a result, the goal of this paper is to analyze how the academic community defines RPA and how far it has been researched in the literature in terms of the status, trends, and application of RPA. There is also a discussion of the distinction between RPA and business process management. To that goal, the Web of Science and Scopus databases were used to conduct a systematic literature review (SLR). The article summarises the results of an SLR on RPA, providing a review of RPA ideas and practical implementations, as well as the benefits of its adoption in various industries.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194962","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047508
Yogesh Kumaran S, Sunanda Das
Beginning in 2020, Covid has increased as a result of a burst put on by a respiratory infection with a substantial peaking fatality rate. The unforeseen occurrence and unchecked global spread of the COVID-19 illness highlight the limitations of current healthcare systems in responding to emergencies affecting public wellness. In these conditions, innovative developments like public blockchain and intelligent systems (AI) have emerged as possible treatments for the covid epidemic. In particular, block chain may help with early identification to combat pandemics. With the measures put in place to prevent infection by wearing masks, social seclusion with a 6m radius, routine testing, and two vaccine doses. This system includes mask measurement, people identification, temp sensors, information tracking, in-person interaction locating, and the current state of a user's medical chart. With the development of technology and increased smartphone usage, illnesses may be tracked and their spread controlled. Considering that the expansion of the business sector's rehabilitation and its continued broad distribution of Covid, it is more crucial to adhere to the instructions to avoid contamination.
{"title":"Ethereum and Intelligent Systems Technologies for COVID-19","authors":"Yogesh Kumaran S, Sunanda Das","doi":"10.1109/SMART55829.2022.10047508","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047508","url":null,"abstract":"Beginning in 2020, Covid has increased as a result of a burst put on by a respiratory infection with a substantial peaking fatality rate. The unforeseen occurrence and unchecked global spread of the COVID-19 illness highlight the limitations of current healthcare systems in responding to emergencies affecting public wellness. In these conditions, innovative developments like public blockchain and intelligent systems (AI) have emerged as possible treatments for the covid epidemic. In particular, block chain may help with early identification to combat pandemics. With the measures put in place to prevent infection by wearing masks, social seclusion with a 6m radius, routine testing, and two vaccine doses. This system includes mask measurement, people identification, temp sensors, information tracking, in-person interaction locating, and the current state of a user's medical chart. With the development of technology and increased smartphone usage, illnesses may be tracked and their spread controlled. Considering that the expansion of the business sector's rehabilitation and its continued broad distribution of Covid, it is more crucial to adhere to the instructions to avoid contamination.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128192018","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047282
Nuparam Chauhan, R. Shukla, A. Sengar, Anurag Gupta
Now a day agriculture is very important in India since it is a growing nation. But generally the crop production attained by farmers would be much below the optimal production. It is very important to correctly detecting and identifying the crop diseases to enhance the profit of the formers and the stakeholder. The main reason for the crop production gap is due to the lack of essential soil nutrients and irrigation in the agricultural farms. To escalate the crop production, it is essential to balance the chemical elements or nutrients present in the soil with varying parameters of soil like the pH and soil moisture. Crop productivity can be increased to optimum level by efficient soil nutrient management. In case of Nutrient deficiencies, visual symptoms will appear on the leaf. This paper put forwards a method to identify the nutrient deficiencies of plants by making use of visual symptoms appearing on the leaves by Classification. Eight types of deficiencies i.e. N, P, K, Ca, B, Zn and Mg will be studied. The proposed study consists of creation and pre¬processing of a set of images consisting of nutrient deficient and healthy leaves, feature extraction and by using Random Forest performing multi class classification of nutrient deficient leaves. Evaluation of tomato leaf from the dataset focuses on recognizing the visual detection and indications of nutritional deficiencies. The proposed architecture achieves the 98.30% accuracy with the model size of 9.20 MB.
现在农业对印度来说非常重要，因为它是一个发展中的国家。但一般来说，农民获得的作物产量将远远低于最优产量。正确检测和识别作物病害对提高作物种植户和利益相关者的利益具有重要意义。造成作物生产缺口的主要原因是农业农场缺乏必需的土壤养分和灌溉。为了提高作物产量，必须平衡土壤中存在的化学元素或营养物质与不同的土壤参数，如pH值和土壤水分。通过有效的土壤养分管理，可以将作物生产力提高到最佳水平。在营养缺乏的情况下，叶子会出现视觉症状。本文提出了一种利用叶片视觉症状分类识别植物营养缺乏症的方法。将研究8种类型的缺陷，即N, P, K, Ca, B, Zn和Mg。本研究主要包括对营养不足和健康叶片图像进行生成和预处理、特征提取以及利用随机森林对营养不足叶片进行多类分类。从数据集对番茄叶片的评估侧重于识别视觉检测和营养缺乏的迹象。模型大小为9.20 MB，准确率为98.30%。
{"title":"Classification of Nutritional Deficiencies in Cabbage Leave Using Random Forest","authors":"Nuparam Chauhan, R. Shukla, A. Sengar, Anurag Gupta","doi":"10.1109/SMART55829.2022.10047282","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047282","url":null,"abstract":"Now a day agriculture is very important in India since it is a growing nation. But generally the crop production attained by farmers would be much below the optimal production. It is very important to correctly detecting and identifying the crop diseases to enhance the profit of the formers and the stakeholder. The main reason for the crop production gap is due to the lack of essential soil nutrients and irrigation in the agricultural farms. To escalate the crop production, it is essential to balance the chemical elements or nutrients present in the soil with varying parameters of soil like the pH and soil moisture. Crop productivity can be increased to optimum level by efficient soil nutrient management. In case of Nutrient deficiencies, visual symptoms will appear on the leaf. This paper put forwards a method to identify the nutrient deficiencies of plants by making use of visual symptoms appearing on the leaves by Classification. Eight types of deficiencies i.e. N, P, K, Ca, B, Zn and Mg will be studied. The proposed study consists of creation and pre¬processing of a set of images consisting of nutrient deficient and healthy leaves, feature extraction and by using Random Forest performing multi class classification of nutrient deficient leaves. Evaluation of tomato leaf from the dataset focuses on recognizing the visual detection and indications of nutritional deficiencies. The proposed architecture achieves the 98.30% accuracy with the model size of 9.20 MB.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127235160","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047345
Pankaj Saraswat, Suman Saini
Identification of numbers has gained excitement recently. Despite the fact that several learning focused categorization approaches are proposed for mnist dataset validation, the precision and processing time may still be improved. Dealing with a disease as an early union is rather common. Swarm approaches like Swarm Optimization seriously evaluate this unfavorable element (PSO). A novel approach using neural network models with convolutions is intended to address the limitations of traditional Soc (CNN). Clo is created by modifying the artificial neural network with the use of luck and analogous learnt optimized particle swarms (CNN-SOLPSO). This adaption is provided for the steadily growing population of the over. This projected enhancer shows increased efficacy when compared to other unconventional methods and expects the best characteristics from that wellbeing assessment. The Holdout library of transcribed digits is used to construct and evaluate the computation contained in the proposed model. the severely deformed, unpredictable, and manually produced pictures of digits that help compensate its Imagenet dataset database. The major objective of this effort is to contribute to an appropriate approach to digital by focusing on greater precision and better computations. Using Bas 2018b, it is possible to choose parameters for Training unshakable quality and drop capacity, Validate refinement and loss measurements, and Identify velocities with defect rate and completion moment.
{"title":"Orthogonal Schemes for Handwritten Digits Recognizing from Image Data","authors":"Pankaj Saraswat, Suman Saini","doi":"10.1109/SMART55829.2022.10047345","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047345","url":null,"abstract":"Identification of numbers has gained excitement recently. Despite the fact that several learning focused categorization approaches are proposed for mnist dataset validation, the precision and processing time may still be improved. Dealing with a disease as an early union is rather common. Swarm approaches like Swarm Optimization seriously evaluate this unfavorable element (PSO). A novel approach using neural network models with convolutions is intended to address the limitations of traditional Soc (CNN). Clo is created by modifying the artificial neural network with the use of luck and analogous learnt optimized particle swarms (CNN-SOLPSO). This adaption is provided for the steadily growing population of the over. This projected enhancer shows increased efficacy when compared to other unconventional methods and expects the best characteristics from that wellbeing assessment. The Holdout library of transcribed digits is used to construct and evaluate the computation contained in the proposed model. the severely deformed, unpredictable, and manually produced pictures of digits that help compensate its Imagenet dataset database. The major objective of this effort is to contribute to an appropriate approach to digital by focusing on greater precision and better computations. Using Bas 2018b, it is possible to choose parameters for Training unshakable quality and drop capacity, Validate refinement and loss measurements, and Identify velocities with defect rate and completion moment.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127462770","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047473
Sónia, Vincent Balu
The cultivation of edible plants is a major component of Indian agriculture. The topsoil amount of food impacts the quality of the produce. Our country is made up mostly of fertile regions with various types of soil. The two types of soil food are macro nutrition & micronutrition. whether the use of fertilisers will raise the crop's quality. This fertiliser has the ability to produce both rich and low yields in the plant. The quantity of fertiliser used is a key determinant of the yield's fullness. The plant health level is tested using the suggested Sensor smart phone, which also aids in determining how much fertiliser should be applied. It accurately assesses the fertiliser amount and is known to the farmers. To increase soil health, highly anticipated sensors are deployed. This practical recommended approach improves the rancher's knowledge of fertiliser usage.
{"title":"Soil Nutrients Monitoring and Analyzing System using Internet of Things","authors":"Sónia, Vincent Balu","doi":"10.1109/SMART55829.2022.10047473","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047473","url":null,"abstract":"The cultivation of edible plants is a major component of Indian agriculture. The topsoil amount of food impacts the quality of the produce. Our country is made up mostly of fertile regions with various types of soil. The two types of soil food are macro nutrition & micronutrition. whether the use of fertilisers will raise the crop's quality. This fertiliser has the ability to produce both rich and low yields in the plant. The quantity of fertiliser used is a key determinant of the yield's fullness. The plant health level is tested using the suggested Sensor smart phone, which also aids in determining how much fertiliser should be applied. It accurately assesses the fertiliser amount and is known to the farmers. To increase soil health, highly anticipated sensors are deployed. This practical recommended approach improves the rancher's knowledge of fertiliser usage.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124825421","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 : 2022-12-16DOI: 10.1109/SMART55829.2022.10047280
S. Likhitha, R. Baskar
Using the Convolutional Neural Network (CNN) algorithm to perform unique classification of skin cancer and evaluating the performance of the SVM approach. n this research work, skin cancer detection has been carried out using algorithms such as CNN and SVM and the accuracy was determined for the same. Two groups are statistically analyzed with the sample size 20 for both the groups, with a pretest g power of 80%. When the CNN algorithm's performance is examined, it is found that the accuracy is 95.03% for CNN and 93.04% for the SVM algorithm. The sample size will be computed using the mean, standard deviation, and standard error, as well as the independent samples test if the significance is less than one. According to the statistical data, the algorithm's accuracy (0.490), specificity (0.009), and p>0.05 significant values are all p0.05. The result shows that CNN algorithm's accuracy was better than SVM algorithm for skin cancer detection.
{"title":"Skin Cancer Classification using CNN in Comparison with Support Vector Machine for Better Accuracy","authors":"S. Likhitha, R. Baskar","doi":"10.1109/SMART55829.2022.10047280","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047280","url":null,"abstract":"Using the Convolutional Neural Network (CNN) algorithm to perform unique classification of skin cancer and evaluating the performance of the SVM approach. n this research work, skin cancer detection has been carried out using algorithms such as CNN and SVM and the accuracy was determined for the same. Two groups are statistically analyzed with the sample size 20 for both the groups, with a pretest g power of 80%. When the CNN algorithm's performance is examined, it is found that the accuracy is 95.03% for CNN and 93.04% for the SVM algorithm. The sample size will be computed using the mean, standard deviation, and standard error, as well as the independent samples test if the significance is less than one. According to the statistical data, the algorithm's accuracy (0.490), specificity (0.009), and p>0.05 significant values are all p0.05. The result shows that CNN algorithm's accuracy was better than SVM algorithm for skin cancer detection.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124492930","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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