Pub Date : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987395
V. Mohanavel, M. Tamilselvi, G. Ramkumar, R. Prabu, G. Anitha
Large bandwidth and more mobility are only two reasons why wireless and mobile networks are fast overtaking wired ones as the preferred mode of connectivity. Heterogeneous networks refer to systems that consist of many independent networks, each of which has its own unique set of protocols and characteristics. Due to their density and complexity, such dense small-cell heterogeneous networks currently consume a lot of power; thus, in order to tackle climate change, we require power information security. A Modified Deep Reinforcement Learning (MDRL) approach may offer an on-demand automated approach with short inference time for NP-hard network communication problems including radio resource distribution, identification, and battery preservation. We examine the DRL algorithm’s applicability to a multi-objective issue. A paradigm for hopeful nonlinear assistance that is founded on the entertainer paradigm and explores repeatedly for potential answers to the multiobjective issue we have given. Throughput and energy savings achieved by our algorithm are equivalent to those of currently used approaches, according to the findings of our tests.
{"title":"Deep Reinforcement Learning for Energy Efficient Routing and Throughput Maximization in Various Networks","authors":"V. Mohanavel, M. Tamilselvi, G. Ramkumar, R. Prabu, G. Anitha","doi":"10.1109/I-SMAC55078.2022.9987395","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987395","url":null,"abstract":"Large bandwidth and more mobility are only two reasons why wireless and mobile networks are fast overtaking wired ones as the preferred mode of connectivity. Heterogeneous networks refer to systems that consist of many independent networks, each of which has its own unique set of protocols and characteristics. Due to their density and complexity, such dense small-cell heterogeneous networks currently consume a lot of power; thus, in order to tackle climate change, we require power information security. A Modified Deep Reinforcement Learning (MDRL) approach may offer an on-demand automated approach with short inference time for NP-hard network communication problems including radio resource distribution, identification, and battery preservation. We examine the DRL algorithm’s applicability to a multi-objective issue. A paradigm for hopeful nonlinear assistance that is founded on the entertainer paradigm and explores repeatedly for potential answers to the multiobjective issue we have given. Throughput and energy savings achieved by our algorithm are equivalent to those of currently used approaches, according to the findings of our tests.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122588092","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987330
Raman Sandhiya, T. V. Mohana, B. Jothi, Juhie Agarwal, N. Kulshrestha, S. Sandhiya
According to studies, there are approximately 850 million poultry birds across India, with an average of 30 million farmers working in the sector. In other words, a poultry farm is a trustworthy and long-term way to make money in India. However, managing a poultry farm is labour intensive due to the need for constant surveillance and control over a wide range of environmental factors. The actual implementation of this is significantly more complicated, expensive, and time-consuming. The paper suggested a smart poultry system that tries to provide the solution for all the issues. The health of poultry birds heavily relies on environmental parameters, so variables like temperature and humidity are measured and monitored continuously. The website was made so that poultry keepers may get reliable information about their birds’ health and use that information to take the appropriate measures. Moreover, in the event of a crisis, such as a fire or the illness of a single bird, the owner will receive a notification. It is also possible to gather information about the poultry in the specified timespan. The Firebase cloud is used for wireless monitoring and managing the poultry system. The suggested automatic smart poultry system will make the birds healthy and it indirectly helps the owners to increase their profit with minimal human effort.
{"title":"IoT based Smart Poultry to Produce a Healthy Environment","authors":"Raman Sandhiya, T. V. Mohana, B. Jothi, Juhie Agarwal, N. Kulshrestha, S. Sandhiya","doi":"10.1109/I-SMAC55078.2022.9987330","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987330","url":null,"abstract":"According to studies, there are approximately 850 million poultry birds across India, with an average of 30 million farmers working in the sector. In other words, a poultry farm is a trustworthy and long-term way to make money in India. However, managing a poultry farm is labour intensive due to the need for constant surveillance and control over a wide range of environmental factors. The actual implementation of this is significantly more complicated, expensive, and time-consuming. The paper suggested a smart poultry system that tries to provide the solution for all the issues. The health of poultry birds heavily relies on environmental parameters, so variables like temperature and humidity are measured and monitored continuously. The website was made so that poultry keepers may get reliable information about their birds’ health and use that information to take the appropriate measures. Moreover, in the event of a crisis, such as a fire or the illness of a single bird, the owner will receive a notification. It is also possible to gather information about the poultry in the specified timespan. The Firebase cloud is used for wireless monitoring and managing the poultry system. The suggested automatic smart poultry system will make the birds healthy and it indirectly helps the owners to increase their profit with minimal human effort.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122993312","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987413
R. Krishnaswamy, A. Titus, G. Gengalakshmi., S. Srinivasan, J. Manikandan
Positron Emission Tomography (PET) is suggested for its high potential Deep Learning (DL) diagnostic imaging with a profound learning approach. The network training is done using clear images but reconstructing the low resolution images using Poisson operation. In training the Convolutional Neural Networks (CNN) at a default noise level, a major issue for their generic applicability is the noise level discrepancy. The noise level varies considerably in each iteration reduces the overall efficiency. The results and measured efficiency loss in different noise environments with various noise levels due to inadequate current trials is also presented. To fix this problem, a local linear fitting function is represented before improving the image quality. It indicates that the resulting approach is resilient to noise levels despite the network being educated at a fixed noise level. The proposed protocol is demonstrated to exceed traditional approaches based on total variance and penalty by mean and standard deviation via simulations and trials.
{"title":"Deep Learning Features Restoration and Regional Longitudinal Fitting of Computed Tomography Images using Convolution Neural Network","authors":"R. Krishnaswamy, A. Titus, G. Gengalakshmi., S. Srinivasan, J. Manikandan","doi":"10.1109/I-SMAC55078.2022.9987413","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987413","url":null,"abstract":"Positron Emission Tomography (PET) is suggested for its high potential Deep Learning (DL) diagnostic imaging with a profound learning approach. The network training is done using clear images but reconstructing the low resolution images using Poisson operation. In training the Convolutional Neural Networks (CNN) at a default noise level, a major issue for their generic applicability is the noise level discrepancy. The noise level varies considerably in each iteration reduces the overall efficiency. The results and measured efficiency loss in different noise environments with various noise levels due to inadequate current trials is also presented. To fix this problem, a local linear fitting function is represented before improving the image quality. It indicates that the resulting approach is resilient to noise levels despite the network being educated at a fixed noise level. The proposed protocol is demonstrated to exceed traditional approaches based on total variance and penalty by mean and standard deviation via simulations and trials.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126509895","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987348
Yihang Wang
In order to comprehensively improve the overall quality of project construction, this article should combine the data analysis of the Internet of Thing, integrate various factors, and actively implement a complete supervision and control system to ensure that the comprehensive level of the project can meet expectations. Pay attention to the business structure and application structure, and give play to the advantages of the intelligent framework application system. Apply the theory of "top-level design" to establish an overall framework of intelligent top-level design of engineering construction quality management with "one platform, multiple systems, seamless, and all-round" as the core; from business architecture, data architecture, application architecture, technical architecture, and security The overall architecture is discussed in five aspects including architecture, with data standards as a starting point, management methods as a booster, and an intelligent platform as an implementation carrier to realize "automatic data collection and real-time upload."
{"title":"Construction of an Intelligent Platform based on the Perspective of IoT Data Analysis","authors":"Yihang Wang","doi":"10.1109/I-SMAC55078.2022.9987348","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987348","url":null,"abstract":"In order to comprehensively improve the overall quality of project construction, this article should combine the data analysis of the Internet of Thing, integrate various factors, and actively implement a complete supervision and control system to ensure that the comprehensive level of the project can meet expectations. Pay attention to the business structure and application structure, and give play to the advantages of the intelligent framework application system. Apply the theory of \"top-level design\" to establish an overall framework of intelligent top-level design of engineering construction quality management with \"one platform, multiple systems, seamless, and all-round\" as the core; from business architecture, data architecture, application architecture, technical architecture, and security The overall architecture is discussed in five aspects including architecture, with data standards as a starting point, management methods as a booster, and an intelligent platform as an implementation carrier to realize \"automatic data collection and real-time upload.\"","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"55 26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133995814","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987277
S. Shete, Pranjal Jog, R. Kamalakannan, J. T. A. Raghesh, S. Manikandan, R. Kumawat
Developed nations have focused more on environmental degradation and climate change in response to rising concerns about meeting the needs of their citizens. The market for emission-free Electric Vehicles (EVs) is now a key area of international rivalry and progress. Rising concerns over high voltage hazards in EVs are a direct result of their increasing popularity. It is crucial to examine the problem diagnosis method of lithium-ion batteries (LIB) because the battery system is responsible for more than 30% of EV accidents. EV’s LIB has complicated fault types that are difficult to treat. Timely and efficient battery pack problem diagnosis is crucial for ensuring the real-time safety of EV function. With the help of neural network models like Multilayer Perceptron (MLP) and Radial Basis Function (RBF), this research demonstrates a technique for detecting and fixing EV battery problems. MATLAB is used to simulate the battery and generate the necessary data for the battery failure detection system. Accuracy is improved through pre-processing the data after it has been generated. Both models are trained and then put through tests to determine how well the models are performing. By contrasting the positive and negative metrics, the best model can be determined.
{"title":"Fault Diagnosis of Electric Vehicle’s Battery by Deploying Neural Network","authors":"S. Shete, Pranjal Jog, R. Kamalakannan, J. T. A. Raghesh, S. Manikandan, R. Kumawat","doi":"10.1109/I-SMAC55078.2022.9987277","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987277","url":null,"abstract":"Developed nations have focused more on environmental degradation and climate change in response to rising concerns about meeting the needs of their citizens. The market for emission-free Electric Vehicles (EVs) is now a key area of international rivalry and progress. Rising concerns over high voltage hazards in EVs are a direct result of their increasing popularity. It is crucial to examine the problem diagnosis method of lithium-ion batteries (LIB) because the battery system is responsible for more than 30% of EV accidents. EV’s LIB has complicated fault types that are difficult to treat. Timely and efficient battery pack problem diagnosis is crucial for ensuring the real-time safety of EV function. With the help of neural network models like Multilayer Perceptron (MLP) and Radial Basis Function (RBF), this research demonstrates a technique for detecting and fixing EV battery problems. MATLAB is used to simulate the battery and generate the necessary data for the battery failure detection system. Accuracy is improved through pre-processing the data after it has been generated. Both models are trained and then put through tests to determine how well the models are performing. By contrasting the positive and negative metrics, the best model can be determined.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122396770","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987279
M. Vanitha, C. S. Joice, M. Selvi, T. Archana, S. Kavitha
This paper proposes an Android mobile application that gives information about the real time location of the buses under the organization. ESP8266 Node MCU and GPS Module is used to get geographic coordinates and the vehicle location is updated to the application through the internet which would give the exact location of buses may help the users to plan their way to reach their destination on time. The RFID (Radio Frequency Identification)-based access control system can only be unlocked by those who have been authenticated. The service will then activate and authenticate the person as a result of this action. The RFID reads an ID number from an RFID tag and transfers the information to a database that can be accessed via an Android app. The Android platform necessitates open-source development, making it the most practical and user-friendly option. Human evolution has included the development of transportation systems. It is impossible to imagine life without automobiles. To accommodate the large population, the number of automobiles has been significantly increasing. This resulted in a rise in the number of accidents. The accident-prevention methods in use today are all static and outdated. Furthermore, no adequate accident detection mechanism exists.
{"title":"Secured IoT based Smart Vehicle Tracking System","authors":"M. Vanitha, C. S. Joice, M. Selvi, T. Archana, S. Kavitha","doi":"10.1109/I-SMAC55078.2022.9987279","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987279","url":null,"abstract":"This paper proposes an Android mobile application that gives information about the real time location of the buses under the organization. ESP8266 Node MCU and GPS Module is used to get geographic coordinates and the vehicle location is updated to the application through the internet which would give the exact location of buses may help the users to plan their way to reach their destination on time. The RFID (Radio Frequency Identification)-based access control system can only be unlocked by those who have been authenticated. The service will then activate and authenticate the person as a result of this action. The RFID reads an ID number from an RFID tag and transfers the information to a database that can be accessed via an Android app. The Android platform necessitates open-source development, making it the most practical and user-friendly option. Human evolution has included the development of transportation systems. It is impossible to imagine life without automobiles. To accommodate the large population, the number of automobiles has been significantly increasing. This resulted in a rise in the number of accidents. The accident-prevention methods in use today are all static and outdated. Furthermore, no adequate accident detection mechanism exists.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127842727","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987264
Uday Kulkarni, Sitanshu S Hallad, A. Patil, Tanvi Bhujannavar, Satwik Kulkarni, S. Meena
Deep Neural Networks (DNNs) have been an important and fast-developing tool used for computer vision, and artificial intelligence. Since these algorithms are widely used for image classification, they are bound to a few issues, creating a need for the DNN models to be optimized. The need for optimization is created due to computational complexity, the number of parameters and model size. Pruning techniques have been employed to mitigate this issue in DNNs, one of these techniques is Filter pruning. There are huge numbers of methods under Filter pruning that have been proposed and each one of them is based on specific sub-objectives. In this paper, we aim to represent different types of pruning methods in a summarized way and conclude on a method that is most efficient in delivering pruned model. The conclusion is stated after trying the methods in a common environment of data set and computational system.
{"title":"A Survey on Filter Pruning Techniques for Optimization of Deep Neural Networks","authors":"Uday Kulkarni, Sitanshu S Hallad, A. Patil, Tanvi Bhujannavar, Satwik Kulkarni, S. Meena","doi":"10.1109/I-SMAC55078.2022.9987264","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987264","url":null,"abstract":"Deep Neural Networks (DNNs) have been an important and fast-developing tool used for computer vision, and artificial intelligence. Since these algorithms are widely used for image classification, they are bound to a few issues, creating a need for the DNN models to be optimized. The need for optimization is created due to computational complexity, the number of parameters and model size. Pruning techniques have been employed to mitigate this issue in DNNs, one of these techniques is Filter pruning. There are huge numbers of methods under Filter pruning that have been proposed and each one of them is based on specific sub-objectives. In this paper, we aim to represent different types of pruning methods in a summarized way and conclude on a method that is most efficient in delivering pruned model. The conclusion is stated after trying the methods in a common environment of data set and computational system.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128025154","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987293
B Surendiran, K. Dhanasekaran, A. Tamizhselvi
Recently Quantum Computing has gained much attention in the field of data science and computational problem solving. It is expected that the quantum machine learning will help researchers to find solutions for many complex problems in areas such as weather forecasting, data science, computational biology, energy management, secure communication, and many others. This paper presents a study on quantum machine learning techniques, challenges and applications of these techniques in climate change prediction, and weather forecasting towards future research in Quantum Machine Learning and Quantum Computing. It also discusses the latest developments and trends in Quantum machine Learning and presents practical examples to understand how Quantum Machine Learning considerably improves the performances of existing machine learning approaches.
{"title":"A Study on Quantum Machine Learning for Accurate and Efficient Weather Prediction","authors":"B Surendiran, K. Dhanasekaran, A. Tamizhselvi","doi":"10.1109/I-SMAC55078.2022.9987293","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987293","url":null,"abstract":"Recently Quantum Computing has gained much attention in the field of data science and computational problem solving. It is expected that the quantum machine learning will help researchers to find solutions for many complex problems in areas such as weather forecasting, data science, computational biology, energy management, secure communication, and many others. This paper presents a study on quantum machine learning techniques, challenges and applications of these techniques in climate change prediction, and weather forecasting towards future research in Quantum Machine Learning and Quantum Computing. It also discusses the latest developments and trends in Quantum machine Learning and presents practical examples to understand how Quantum Machine Learning considerably improves the performances of existing machine learning approaches.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128697339","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987366
J. Mahale, S. Degadwala, Dhairya Vyas
India is mostly a farming country. Agriculture is vital to the Indian economy and humanity’s destiny. Agriculture also employs a sizable portion of the workforce. 70% of India’s rural population relies on agricultural activity for their livelihood. Crop output forecasting is one of the most sought-after and difficult tasks that any government can do. Any farmer wants to know how much crop production they might expect in the near future. Traditionally, while calculating yields, the farmer’s expertise of the crop and land was taken into account. Machine Learning algorithms can be used to extract accuracy as well as previously unknown patterns or information from massive datasets. As a result, crop output projections will help farmers choose the best crop for their farms. They could also generate a larger profit as a result of this. Multiple attribute selection techniques for crop prediction, as well as the Machine Learning methodology, are discussed in this work. This research study will discuss about the future path of agricultural output prediction systems near the end of the programme.
{"title":"Crop Prediction System based on Soil and Weather Characteristics","authors":"J. Mahale, S. Degadwala, Dhairya Vyas","doi":"10.1109/I-SMAC55078.2022.9987366","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987366","url":null,"abstract":"India is mostly a farming country. Agriculture is vital to the Indian economy and humanity’s destiny. Agriculture also employs a sizable portion of the workforce. 70% of India’s rural population relies on agricultural activity for their livelihood. Crop output forecasting is one of the most sought-after and difficult tasks that any government can do. Any farmer wants to know how much crop production they might expect in the near future. Traditionally, while calculating yields, the farmer’s expertise of the crop and land was taken into account. Machine Learning algorithms can be used to extract accuracy as well as previously unknown patterns or information from massive datasets. As a result, crop output projections will help farmers choose the best crop for their farms. They could also generate a larger profit as a result of this. Multiple attribute selection techniques for crop prediction, as well as the Machine Learning methodology, are discussed in this work. This research study will discuss about the future path of agricultural output prediction systems near the end of the programme.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117093713","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 : 2022-11-10DOI: 10.1109/I-SMAC55078.2022.9987356
Suganya T, V. Rajendran, P. Mangaiyarkarasi
Medical electronic implants can basically work on the well-being and personal satisfaction of individuals. These plugs are usually fueled by batteries, which as a rule have a limited lifespan and as a result need to be replaced occasionally using surgery. In the latter, subcutaneous sun-based cells, which can generate energy by retaining the light transmitted by the skin, can be developed as an economic force to control medical electronic insertions in the body. This paper is to develop an Improved Maximum Power Point Tracking (IMPPT) controller aimed at an equivalent skin model with battery-less cardiac pacemaker. In the proposed methodology, the equivalent skin model with battery-less cardiac pacemaker is designed and analyzed. The Photovoltaic cellis utilized to power the cardiac pacemaker for design a battery-less cardiac pacemaker. After that, the PV is connected with the equivalent circuit model. The PV may be affected due to environmental conditions which will be solved by the MPPT controller. Artificial Intelligence (AI) technique is developed to maintain the stability operation by avoiding environmental conditions. Here, the Arithmetic Optimization Algorithm (AOA) can be utilized towards manage the MPPT controller. The proposed battery-less cardiac pacemaker is designed and executed in MATLAB/Simulink, and its performance is evaluated in terms of maximum power, maximum voltage, maximum current, irradiance, input power of pacemaker, and output power of pacemaker.
{"title":"Analysis of Equivalent Skin Model with Battery-Less Cardiac Pacemaker using Improved MPPT Controller","authors":"Suganya T, V. Rajendran, P. Mangaiyarkarasi","doi":"10.1109/I-SMAC55078.2022.9987356","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987356","url":null,"abstract":"Medical electronic implants can basically work on the well-being and personal satisfaction of individuals. These plugs are usually fueled by batteries, which as a rule have a limited lifespan and as a result need to be replaced occasionally using surgery. In the latter, subcutaneous sun-based cells, which can generate energy by retaining the light transmitted by the skin, can be developed as an economic force to control medical electronic insertions in the body. This paper is to develop an Improved Maximum Power Point Tracking (IMPPT) controller aimed at an equivalent skin model with battery-less cardiac pacemaker. In the proposed methodology, the equivalent skin model with battery-less cardiac pacemaker is designed and analyzed. The Photovoltaic cellis utilized to power the cardiac pacemaker for design a battery-less cardiac pacemaker. After that, the PV is connected with the equivalent circuit model. The PV may be affected due to environmental conditions which will be solved by the MPPT controller. Artificial Intelligence (AI) technique is developed to maintain the stability operation by avoiding environmental conditions. Here, the Arithmetic Optimization Algorithm (AOA) can be utilized towards manage the MPPT controller. The proposed battery-less cardiac pacemaker is designed and executed in MATLAB/Simulink, and its performance is evaluated in terms of maximum power, maximum voltage, maximum current, irradiance, input power of pacemaker, and output power of pacemaker.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116146981","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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