Pub Date : 2022-12-16DOI: 10.1109/SMART55829.2022.10047792
S. K. UmaMaheswaran, S. Deivasigamani, Kapil Joshi, Devvret Verma, Santhosh Kumar Rajamani, Dhyana Sharon Ross
One of its most serious diseases that may affect kids and teens is a cancerous tumor. Gliomas account for 85% to 90% of all recurrent System (CNS) cancers. An estimated 11,700 individuals get a glioma diagnosis per year. When a person has a benign brains or CNS cancer, their five - year survival is around 36% for women and approximately 34% for men. There are several distinct types of brain cancers, including benign, aggressive, endocrine, and other types. The average lifespan of people should really be increased by using appropriate treatment, scheduling, and precise diagnosis. Mri scan is the most effective method for finding tumour (MRI). An large quantity of picture data is produced by scanners. The surgeon looks over these pictures. Algorithms (ML) and intelligent systems (AI)-based automation classification systems have repeatedly beaten hand categorisation in high accuracy. Therefore., offering a system can perform classification and tracking using Deep Learning Techniques such as Fully Convolutional Systems (CNN), Knn (ANN), (Template matching), and Transfer Learning (TL) would be helpful to physicians everywhere.
{"title":"Computational Intelligence Approach to Improve The Classification Accuracy of Brain Tumor Detection","authors":"S. K. UmaMaheswaran, S. Deivasigamani, Kapil Joshi, Devvret Verma, Santhosh Kumar Rajamani, Dhyana Sharon Ross","doi":"10.1109/SMART55829.2022.10047792","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047792","url":null,"abstract":"One of its most serious diseases that may affect kids and teens is a cancerous tumor. Gliomas account for 85% to 90% of all recurrent System (CNS) cancers. An estimated 11,700 individuals get a glioma diagnosis per year. When a person has a benign brains or CNS cancer, their five - year survival is around 36% for women and approximately 34% for men. There are several distinct types of brain cancers, including benign, aggressive, endocrine, and other types. The average lifespan of people should really be increased by using appropriate treatment, scheduling, and precise diagnosis. Mri scan is the most effective method for finding tumour (MRI). An large quantity of picture data is produced by scanners. The surgeon looks over these pictures. Algorithms (ML) and intelligent systems (AI)-based automation classification systems have repeatedly beaten hand categorisation in high accuracy. Therefore., offering a system can perform classification and tracking using Deep Learning Techniques such as Fully Convolutional Systems (CNN), Knn (ANN), (Template matching), and Transfer Learning (TL) would be helpful to physicians everywhere.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"44 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":"124546557","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/SMART55829.2022.10047167
C. Gupta, Vipin Kumar, K. Kumar
Management of the supply chain is essential for running any kind of organisation in this paper, in which we provide an overview of the developments in supply chain management. Following a review of the difficulties involved in managing supply chains, we give alternate definitions and major concerns linked to supply chain management. We then talk about considerable supply chain management inefficiencies. An overview of current research efforts and a discussion of impending supply chain management difficulties are provided as a conclusion.
{"title":"A Study on the Applications of Supply Chain Management","authors":"C. Gupta, Vipin Kumar, K. Kumar","doi":"10.1109/SMART55829.2022.10047167","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047167","url":null,"abstract":"Management of the supply chain is essential for running any kind of organisation in this paper, in which we provide an overview of the developments in supply chain management. Following a review of the difficulties involved in managing supply chains, we give alternate definitions and major concerns linked to supply chain management. We then talk about considerable supply chain management inefficiencies. An overview of current research efforts and a discussion of impending supply chain management difficulties are provided as a conclusion.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"6 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":"115904408","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/SMART55829.2022.10047572
R. Jain
Water is the most widely consumed natural resource on the earth. Due to continuous use and unmindful wastage, the water table is declining. To protect this information of ground water potential is needed. Remote Sensing with Geographic Information System and Multi criteria decision analysis techniques is used. Analytical Hierarchy Process comes under Multi Criteria Decision Analysis and it is executed for defining weights for different criteria
{"title":"Groundwater Delineation Using RS and GIS for Gurgaon Region","authors":"R. Jain","doi":"10.1109/SMART55829.2022.10047572","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047572","url":null,"abstract":"Water is the most widely consumed natural resource on the earth. Due to continuous use and unmindful wastage, the water table is declining. To protect this information of ground water potential is needed. Remote Sensing with Geographic Information System and Multi criteria decision analysis techniques is used. Analytical Hierarchy Process comes under Multi Criteria Decision Analysis and it is executed for defining weights for different criteria","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"19 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":"128779373","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/SMART55829.2022.10047372
Hritik Gupta, A. Chaudhary, Anil Kumar
Java is still regarded as one of the most powerful programming languages available, because of its security and platform independence. It's hard to manage logs manually so to simplify and to make logging easy Apache released Apache log4j framework to manage logs generated by applications easily. This is imbued within the code so no extra hard work is required to access or deploy it. This paper is all about logg4j vulnerabilities visible in the log4j framework.
{"title":"Identification and Analysis of Log4j Vulnerability","authors":"Hritik Gupta, A. Chaudhary, Anil Kumar","doi":"10.1109/SMART55829.2022.10047372","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047372","url":null,"abstract":"Java is still regarded as one of the most powerful programming languages available, because of its security and platform independence. It's hard to manage logs manually so to simplify and to make logging easy Apache released Apache log4j framework to manage logs generated by applications easily. This is imbued within the code so no extra hard work is required to access or deploy it. This paper is all about logg4j vulnerabilities visible in the log4j framework.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"1 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":"129047853","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/SMART55829.2022.10046944
Atul Mathur, R. Dwivedi, Rajul Rastogi
Novel computational tools based on ML schemes are useful in knowing the complex brain functions and its diseases. It was found during the study that differentiation among various neurological disorders is not easy task due to similarities in symptoms. This paper significantly examines and compares performances of many ML based methods to diagnose neurological illness—emphasized on Alzheimer's disease, Parkinson's disease and schizophrenia. The article provides the overview of computational intelligence methods evaluates and diverse performance metrics used to predict neurological disorders from different type of data.
{"title":"A Survey of Machine Learning Based Approaches for Neurological Disorder Predictions","authors":"Atul Mathur, R. Dwivedi, Rajul Rastogi","doi":"10.1109/SMART55829.2022.10046944","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046944","url":null,"abstract":"Novel computational tools based on ML schemes are useful in knowing the complex brain functions and its diseases. It was found during the study that differentiation among various neurological disorders is not easy task due to similarities in symptoms. This paper significantly examines and compares performances of many ML based methods to diagnose neurological illness—emphasized on Alzheimer's disease, Parkinson's disease and schizophrenia. The article provides the overview of computational intelligence methods evaluates and diverse performance metrics used to predict neurological disorders from different type of data.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"103 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":"129301005","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/SMART55829.2022.10047622
D. Gritto, P. Muthulakshmi
Cloud computing is a service model that has evolved in its stature beyond its traditional bounds of infrastructure, platform and software as a service. As the surge in resource demand may hit the cloud service provider at any time, a ceaseless monitoring system is vital. The allocation of an appropriate virtual machine for the cloudlet i.e., the user workload and maintaining the work load equilibrium among the resources is the most challenging operation in the cloud environment. The proper utilization of the cloud resources can be ensured by selecting the right cloudlet scheduling and load balancing algorithm(s). The cloudlet scheduling algorithm selection is based on the combination of two or more Quality of Service (QoS) and performance metrics like makespan, throughput, cost, power consumption, virtual machine or resource utilization and load balancing etc. The load balancer module takes the responsibility of dispersing the cloudlets evenly among the virtual machines by considering various features like CPU utilization, number of processing elements, bandwidth, memory and the load limit of the virtual machines. In this paper, an effort has been made to comprehend the most persisting cloudlet scheduling and load balancing algorithms that have been proposed by the researchers. Compiling the load balancing technologies that are integrated with the contemporary cloud platforms such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) has also been prioritized. This study suggests a Priority Based Cloudlet Scheduling Algorithm (PBCSA) that schedules the cloudlet according to the user priority. The Min-Min scheduler is used to schedule the high priority cloudlets and the Max-Min scheduler is used to schedule the low priority cloudlets. The experimental findings reveals that, in the majority of scenarios, the proposed algorithm outperforms the Min-Min and Max-Min scheduling in terms of makespan and virtual machine utilization ratio.
云计算是一种服务模式，其地位已经超越了基础设施、平台和软件即服务的传统界限。由于资源需求的激增可能随时冲击云服务提供商，因此一个不间断的监控系统至关重要。为cloudlet分配适当的虚拟机(即用户工作负载和维护资源之间的工作负载平衡)是云环境中最具挑战性的操作。通过选择合适的云调度和负载均衡算法，可以保证云资源的合理利用。cloudlet调度算法的选择是基于两个或多个服务质量(QoS)和性能指标的组合，如makespan、吞吐量、成本、功耗、虚拟机或资源利用率和负载平衡等。负载平衡器模块通过考虑各种特性，如CPU利用率、处理元素的数量、带宽、内存和虚拟机的负载限制，负责在虚拟机中均匀地分散cloudlet。本文对研究人员提出的最持久的云调度和负载平衡算法进行了理解。编译与Amazon Web Services (AWS)、Microsoft Azure和谷歌cloud Platform (GCP)等当代云平台集成的负载平衡技术也已被优先考虑。本研究提出一种基于优先级的云调度算法(PBCSA)，根据用户优先级对云调度进行调度。Min-Min调度器用于调度高优先级的cloudlets, Max-Min调度器用于调度低优先级的cloudlets。实验结果表明，在大多数场景下，该算法在makespan和虚拟机利用率方面优于Min-Min和Max-Min调度。
{"title":"Scheduling Cloudlets in a Cloud Computing Environment: A Priority-based Cloudlet Scheduling Algorithm (PBCSA)","authors":"D. Gritto, P. Muthulakshmi","doi":"10.1109/SMART55829.2022.10047622","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047622","url":null,"abstract":"Cloud computing is a service model that has evolved in its stature beyond its traditional bounds of infrastructure, platform and software as a service. As the surge in resource demand may hit the cloud service provider at any time, a ceaseless monitoring system is vital. The allocation of an appropriate virtual machine for the cloudlet i.e., the user workload and maintaining the work load equilibrium among the resources is the most challenging operation in the cloud environment. The proper utilization of the cloud resources can be ensured by selecting the right cloudlet scheduling and load balancing algorithm(s). The cloudlet scheduling algorithm selection is based on the combination of two or more Quality of Service (QoS) and performance metrics like makespan, throughput, cost, power consumption, virtual machine or resource utilization and load balancing etc. The load balancer module takes the responsibility of dispersing the cloudlets evenly among the virtual machines by considering various features like CPU utilization, number of processing elements, bandwidth, memory and the load limit of the virtual machines. In this paper, an effort has been made to comprehend the most persisting cloudlet scheduling and load balancing algorithms that have been proposed by the researchers. Compiling the load balancing technologies that are integrated with the contemporary cloud platforms such as Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) has also been prioritized. This study suggests a Priority Based Cloudlet Scheduling Algorithm (PBCSA) that schedules the cloudlet according to the user priority. The Min-Min scheduler is used to schedule the high priority cloudlets and the Max-Min scheduler is used to schedule the low priority cloudlets. The experimental findings reveals that, in the majority of scenarios, the proposed algorithm outperforms the Min-Min and Max-Min scheduling in terms of makespan and virtual machine utilization ratio.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"76 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":"130696354","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/SMART55829.2022.10047067
Shivangi, Gulishta Khan, S. Ninoria
The Internet of Things (IoT) is a young technology that is rapidly evolving. because of importance of IoT within the destiny, it will be extremely important to create adequate security for IoT infrastructure. Via this existing article, the architecture of IoT and their security dimensions are addressed after presenting and exploring the securities and demanding scenarios of various IoT layers. The use of sensitive information that needs to be kept secret from third parties will increase as a result of the development of modern private technologies. In order to assess and mitigate many IoT privacy issues and support the design and deployment of cosy and touchy systems, present methodologies are neither sufficient nor powerful. This study suggests a data authentication architecture in this situation. In particular, there may be a drive toward adopting secure IoT architectures that rely on physically unreproducible capabilities and in-depth research to guarantee the privacy of retrieved IoT data.
{"title":"“Secure Architecture for Providing Data Authenticity in IoT Enabled Devices”","authors":"Shivangi, Gulishta Khan, S. Ninoria","doi":"10.1109/SMART55829.2022.10047067","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047067","url":null,"abstract":"The Internet of Things (IoT) is a young technology that is rapidly evolving. because of importance of IoT within the destiny, it will be extremely important to create adequate security for IoT infrastructure. Via this existing article, the architecture of IoT and their security dimensions are addressed after presenting and exploring the securities and demanding scenarios of various IoT layers. The use of sensitive information that needs to be kept secret from third parties will increase as a result of the development of modern private technologies. In order to assess and mitigate many IoT privacy issues and support the design and deployment of cosy and touchy systems, present methodologies are neither sufficient nor powerful. This study suggests a data authentication architecture in this situation. In particular, there may be a drive toward adopting secure IoT architectures that rely on physically unreproducible capabilities and in-depth research to guarantee the privacy of retrieved IoT data.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"16 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":"130281640","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/SMART55829.2022.10047402
A. K. Moharana, Daxa Vekariya
Dermatological issues are one of the most preventable diseases in the world. Although it is widespread, studying it is challenging because of the many layers of complexity introduced by the presence of colour, concealment, and hair. Diagnosing skin problems early is essential for effective therapy. The method for identifying and treating skin injury is based on the specialist's level of competence and experience. There needs to be pinpoint accuracy in the analysis. Success rates for clinical diagnostic and clinical therapeutic frameworks are improving with time as a result of cutting-edge developments in medicine and data science. Skin disease diagnosis has benefited from the application of AI calculations and the utilisation of the large quantity of information available in hospitals and clinics. For this study, we collated a large number of previous studies that analysed skin illnesses via the lens of AI-based classification strategies. In their previous studies, the specialists employed numerous frameworks, instruments, and calculations. A small number of frameworks have been developed that are capable of correctly identifying skin diseases with varying degrees of suggestive precision. Multiple models have used image processing and component extraction methods to
{"title":"Detection of Skin Diseases via Deep Learning using SVM Method","authors":"A. K. Moharana, Daxa Vekariya","doi":"10.1109/SMART55829.2022.10047402","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047402","url":null,"abstract":"Dermatological issues are one of the most preventable diseases in the world. Although it is widespread, studying it is challenging because of the many layers of complexity introduced by the presence of colour, concealment, and hair. Diagnosing skin problems early is essential for effective therapy. The method for identifying and treating skin injury is based on the specialist's level of competence and experience. There needs to be pinpoint accuracy in the analysis. Success rates for clinical diagnostic and clinical therapeutic frameworks are improving with time as a result of cutting-edge developments in medicine and data science. Skin disease diagnosis has benefited from the application of AI calculations and the utilisation of the large quantity of information available in hospitals and clinics. For this study, we collated a large number of previous studies that analysed skin illnesses via the lens of AI-based classification strategies. In their previous studies, the specialists employed numerous frameworks, instruments, and calculations. A small number of frameworks have been developed that are capable of correctly identifying skin diseases with varying degrees of suggestive precision. Multiple models have used image processing and component extraction methods to","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"21 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":"131200433","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/SMART55829.2022.10047734
Lakshmaiah Alluri, Hemant Jeevan Magadum
Cycle sharing and vehicle sharing and monitoring system is the solutions for managing and monitoring shared cycles or vehicle remotely for pollution free operation and facility available to public to travel in Smart City. Cycle or vehicle sharing is a kind of personal or public transport. Cycle or vehicle can be parked at the place provided nearer to the network of stations. With an IoT application on mobile phone, a user can find the availability of a Cycle or vehicle from a station, if it is available user can use it for a short ride, later it can be return to the any other nearby station. So developments of Cycle or vehicle sharing stations are more useful for common public transport through which connectivity can be established between the smart stations so that last minute rush can be avoided. Traffic density can be reduced and also provide last-mile connectivity. The paper proposes development of highly efficient integrated Shared cycles or vehicle monitoring system with GPRS remote control and remotely locking and unlocking based on user request. The project proposes usage of solar powered locking system with low carbon footprint.
{"title":"Shared Cycle and Vehicle Sharing and Monitoring System","authors":"Lakshmaiah Alluri, Hemant Jeevan Magadum","doi":"10.1109/SMART55829.2022.10047734","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10047734","url":null,"abstract":"Cycle sharing and vehicle sharing and monitoring system is the solutions for managing and monitoring shared cycles or vehicle remotely for pollution free operation and facility available to public to travel in Smart City. Cycle or vehicle sharing is a kind of personal or public transport. Cycle or vehicle can be parked at the place provided nearer to the network of stations. With an IoT application on mobile phone, a user can find the availability of a Cycle or vehicle from a station, if it is available user can use it for a short ride, later it can be return to the any other nearby station. So developments of Cycle or vehicle sharing stations are more useful for common public transport through which connectivity can be established between the smart stations so that last minute rush can be avoided. Traffic density can be reduced and also provide last-mile connectivity. The paper proposes development of highly efficient integrated Shared cycles or vehicle monitoring system with GPRS remote control and remotely locking and unlocking based on user request. The project proposes usage of solar powered locking system with low carbon footprint.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"28 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":"114081835","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/SMART55829.2022.10046805
D. K. Sinha, S. Reddy
Drought is considered one of the most terrifying disasters that humanity have ever experienced, and farmers all over the globe often deal with it. It may happen anywhere outside of the globe and is referred to as a “slow catastrophe” since it lasts for a long time, and perhaps even further if it chooses to be more severe. Drought affects also human lives but also crops, global economy, and power that farmers have ingested. During a disaster, seems to be at risk. Basic necessities like food are difficult to get, and market forces imbalance causes irritation to reach its height. There are a variety of things that may be done to prevent the dry, such as desalinating water, crop planning, rainfall gathering, and sprinkler, which can all help preserve water during dry spells. The primary answer to this problem would have been to analyse the environment and the potential results of it, that could aid in planning for the worst-case scenario. Soil predictions may also be very helpful in forecasting this scenario. In order to forecast how floods might be averted, the article combines meteorological and soil data. Deep learning methods will make it possible to determine with remarkable accuracy if the droughts will occur or not.
{"title":"Just Use a Perceptron to Anticipate Dry","authors":"D. K. Sinha, S. Reddy","doi":"10.1109/SMART55829.2022.10046805","DOIUrl":"https://doi.org/10.1109/SMART55829.2022.10046805","url":null,"abstract":"Drought is considered one of the most terrifying disasters that humanity have ever experienced, and farmers all over the globe often deal with it. It may happen anywhere outside of the globe and is referred to as a “slow catastrophe” since it lasts for a long time, and perhaps even further if it chooses to be more severe. Drought affects also human lives but also crops, global economy, and power that farmers have ingested. During a disaster, seems to be at risk. Basic necessities like food are difficult to get, and market forces imbalance causes irritation to reach its height. There are a variety of things that may be done to prevent the dry, such as desalinating water, crop planning, rainfall gathering, and sprinkler, which can all help preserve water during dry spells. The primary answer to this problem would have been to analyse the environment and the potential results of it, that could aid in planning for the worst-case scenario. Soil predictions may also be very helpful in forecasting this scenario. In order to forecast how floods might be averted, the article combines meteorological and soil data. Deep learning methods will make it possible to determine with remarkable accuracy if the droughts will occur or not.","PeriodicalId":431639,"journal":{"name":"2022 11th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"186 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":"121623440","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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