Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776387
Mitali Patil, Harsha Kalmath, Khushboo Chamedia, Shreya Pandey, Shilpa Deshpande, N. Kurkure, G. Misra
Cloud computing technology in recent years has seen rapid growth with a number of institutions and organizations adopting it, for its scalable, extensible and rapidly available services. Many scientific institutions over the years have been executing high performance jobs on traditional high-performance computing (HPC) clusters, but the ever-increasing use of resources calls for optimizing the existing infrastructure to deliver better ubiquitous services. This paper presents the implementation of OpenStack cloud computing platform for executing scientific applications at IISER, Pune. This platform additionally can be tailored to serve the institute's need and requirements. The paper also analyses and discusses the effectiveness of our deployment method, concluding with some feasible scenarios that are achievable to make the cloud scalable and heterogeneous.
{"title":"OpenStack Cloud Deployment for Scientific Applications","authors":"Mitali Patil, Harsha Kalmath, Khushboo Chamedia, Shreya Pandey, Shilpa Deshpande, N. Kurkure, G. Misra","doi":"10.1109/CCGE50943.2021.9776387","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776387","url":null,"abstract":"Cloud computing technology in recent years has seen rapid growth with a number of institutions and organizations adopting it, for its scalable, extensible and rapidly available services. Many scientific institutions over the years have been executing high performance jobs on traditional high-performance computing (HPC) clusters, but the ever-increasing use of resources calls for optimizing the existing infrastructure to deliver better ubiquitous services. This paper presents the implementation of OpenStack cloud computing platform for executing scientific applications at IISER, Pune. This platform additionally can be tailored to serve the institute's need and requirements. The paper also analyses and discusses the effectiveness of our deployment method, concluding with some feasible scenarios that are achievable to make the cloud scalable and heterogeneous.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125838826","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776410
Niteesh Kumar, Pranav P, Vishal Nirney, G. V.
Headways in deep learning has enabled the creation of fraudulent digital content with ease. This fraudulent digital content created is entirely indistinguishable from the original digital content. This close identicalness has what it takes to cause havoc. This fraudulent digital content, popularly known as deepfakes having the potential to change the truth and decay faith, can leave impressions on a large scale and even our daily lives. Deepfake is composed of two words, the first being deep: deep learning and the second being fake: fake digital content. Artificial intelligence forming the nucleus of any deepfake formulation technology empowers it to dodge most of the deepfake detection techniques through learning. This ability of deepfakes to learn and elude detection technologies is a matter of significant concern. In this research work, we focus on our efforts towards the detection of deepfake images. We follow two approaches for deepfake image detection, and the first is to build a custom CNN based deep learning network to detect deepfake images, and the second is to use the concept of transfer learning.
{"title":"Deepfake Image Detection using CNNs and Transfer Learning","authors":"Niteesh Kumar, Pranav P, Vishal Nirney, G. V.","doi":"10.1109/CCGE50943.2021.9776410","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776410","url":null,"abstract":"Headways in deep learning has enabled the creation of fraudulent digital content with ease. This fraudulent digital content created is entirely indistinguishable from the original digital content. This close identicalness has what it takes to cause havoc. This fraudulent digital content, popularly known as deepfakes having the potential to change the truth and decay faith, can leave impressions on a large scale and even our daily lives. Deepfake is composed of two words, the first being deep: deep learning and the second being fake: fake digital content. Artificial intelligence forming the nucleus of any deepfake formulation technology empowers it to dodge most of the deepfake detection techniques through learning. This ability of deepfakes to learn and elude detection technologies is a matter of significant concern. In this research work, we focus on our efforts towards the detection of deepfake images. We follow two approaches for deepfake image detection, and the first is to build a custom CNN based deep learning network to detect deepfake images, and the second is to use the concept of transfer learning.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"113 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133351012","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776419
Harsh D Shah, Vinayak Tupe, Amit Rathod, Sohel Shaikh, Nilesh J. Uke
Virtual Tour can be created stored in some MB's or GB's and can be accessed by a user from any corner of the world having a strong internet connection. Many colleges have represented their campus in digital format so many student's can have an idea how college campus looks. The way of representing virtual tour of most of the colleges are the same using a 360-degree virtual tour which are the 2D images stitched together to form a long continuous image. But our virtual has real objects that are represented in a 3D Gaming environment. We have combined the idea of 3D Gaming and 360-degree images to create an actual campus environment where user can move around. We have used First Person Perspective Approach which results in when the user controls it he feels that he is walking on a real college campus. For this, we have developed our 3D Model using as popular open-source modelling tool Blender2.8. And for giving a taste of gaming we are exporting our model into the web using the Babylon.js library which is new in the market but provides all assets to develop a 3D game. So are represent our virtual in a unique way where a user has all control and can roam inside the college campus smoothly.
{"title":"A Progressive Web App for Virtual Campus Tour","authors":"Harsh D Shah, Vinayak Tupe, Amit Rathod, Sohel Shaikh, Nilesh J. Uke","doi":"10.1109/CCGE50943.2021.9776419","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776419","url":null,"abstract":"Virtual Tour can be created stored in some MB's or GB's and can be accessed by a user from any corner of the world having a strong internet connection. Many colleges have represented their campus in digital format so many student's can have an idea how college campus looks. The way of representing virtual tour of most of the colleges are the same using a 360-degree virtual tour which are the 2D images stitched together to form a long continuous image. But our virtual has real objects that are represented in a 3D Gaming environment. We have combined the idea of 3D Gaming and 360-degree images to create an actual campus environment where user can move around. We have used First Person Perspective Approach which results in when the user controls it he feels that he is walking on a real college campus. For this, we have developed our 3D Model using as popular open-source modelling tool Blender2.8. And for giving a taste of gaming we are exporting our model into the web using the Babylon.js library which is new in the market but provides all assets to develop a 3D game. So are represent our virtual in a unique way where a user has all control and can roam inside the college campus smoothly.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134233580","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776479
Swati V. Patel, Satyen Parikh, Savan H. Patel
In India, specifically in North Gujarat region most of the farmers are small or marginal farmers who don't have a much hectors of land. In that case famers cannot effort their own tube wells to irrigate their crops. To come up with this situation they are sharing one tube well and paying to tube well owner for the water they used this culture is called Shared Tube well culture. The adoption of smart irrigation system is automates the water conveying system to the harvests to guarantee every one of the crops ensure sufficient water for their healthy growth, to diminish the measure of water squandered in irrigation, and to limit the financial cost for the users.
{"title":"Irrigation to Smart Irrigation and Tube Well Users","authors":"Swati V. Patel, Satyen Parikh, Savan H. Patel","doi":"10.1109/CCGE50943.2021.9776479","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776479","url":null,"abstract":"In India, specifically in North Gujarat region most of the farmers are small or marginal farmers who don't have a much hectors of land. In that case famers cannot effort their own tube wells to irrigate their crops. To come up with this situation they are sharing one tube well and paying to tube well owner for the water they used this culture is called Shared Tube well culture. The adoption of smart irrigation system is automates the water conveying system to the harvests to guarantee every one of the crops ensure sufficient water for their healthy growth, to diminish the measure of water squandered in irrigation, and to limit the financial cost for the users.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114721432","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776418
Kuldeep Hule, Arjun Dashrath, Ashwin Gupta
In the last decade, the blockchain industry has solidified itself as one of the most secure forms of data storage. The emergence of extremely secure cryptocurrencies that have a plethora of advantages over regular internet banking has brought about a revolutionary change in the banking industry. The mobile payment users have skyrocketed with an estimated proximity mobile payment transaction user count of 1.31 billion in 2023. Therefore, there is a need for a cryptocurrency based unified payment interface (UPI) that would grant additional security and improve the transaction process drastically over the existing mobile payment system. We worked out on this aspect and proposed a scheme that would allow mobile devices to mine blocks themselves and generate their own transactions rather than depending on third-party services or bank servers.
{"title":"Self-Mining Blockchain Mobile Unified Payment Interface","authors":"Kuldeep Hule, Arjun Dashrath, Ashwin Gupta","doi":"10.1109/CCGE50943.2021.9776418","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776418","url":null,"abstract":"In the last decade, the blockchain industry has solidified itself as one of the most secure forms of data storage. The emergence of extremely secure cryptocurrencies that have a plethora of advantages over regular internet banking has brought about a revolutionary change in the banking industry. The mobile payment users have skyrocketed with an estimated proximity mobile payment transaction user count of 1.31 billion in 2023. Therefore, there is a need for a cryptocurrency based unified payment interface (UPI) that would grant additional security and improve the transaction process drastically over the existing mobile payment system. We worked out on this aspect and proposed a scheme that would allow mobile devices to mine blocks themselves and generate their own transactions rather than depending on third-party services or bank servers.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115801131","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776360
Vikas Rattan, Shikha Sharma, R. Mittal, Varun Malik
It is the dream of every student to attain an excellent career with decent remuneration. It will be an additional benefit if they get a high-profile job during their campus placement before they leave. The campus placement activities with the right resources at the right time and with minimal cost are of the greatest benefit to undergraduates regardless of any stream viz. engineering, business, medical, or sciences. The scope of the paper is to prepare an automated model that predicts or analyzes the probability of students getting positioned in a company by salient parameters like academic performance in terms of CGPA, test marks, or other professional degree evaluations and another non-academic parameter such as gender. For this intention, one of the classification algorithms named Decision Tree and up sampling technique “Synthetic Minority Oversampling Technique” had been used. The outcome of this analysis shall lend a hand to the organization to propose an approach that enhances the performance of students to get a better job in the pre-final years.
{"title":"Applying SMOTE with Decision Tree Classifier for Campus Placement Prediction","authors":"Vikas Rattan, Shikha Sharma, R. Mittal, Varun Malik","doi":"10.1109/CCGE50943.2021.9776360","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776360","url":null,"abstract":"It is the dream of every student to attain an excellent career with decent remuneration. It will be an additional benefit if they get a high-profile job during their campus placement before they leave. The campus placement activities with the right resources at the right time and with minimal cost are of the greatest benefit to undergraduates regardless of any stream viz. engineering, business, medical, or sciences. The scope of the paper is to prepare an automated model that predicts or analyzes the probability of students getting positioned in a company by salient parameters like academic performance in terms of CGPA, test marks, or other professional degree evaluations and another non-academic parameter such as gender. For this intention, one of the classification algorithms named Decision Tree and up sampling technique “Synthetic Minority Oversampling Technique” had been used. The outcome of this analysis shall lend a hand to the organization to propose an approach that enhances the performance of students to get a better job in the pre-final years.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116251897","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776421
R. Mittal, A. Mittal, Arun Aggarwal
Indian m-health app Aarogya Setu has made a significant contribution in terms of contactability tracing and disease management during the initial days of the COVID-19 pandemic, with its contact tracking approach to infectious individuals and its health tips for eliminating new coronaviruses. The goal of this study is to forecast whether or not Indian consumers will continue to use this app. According to previous studies, the context or setting has a substantial impact on the customer's perceived value. The current study's unique setting is to investigate the parameters impacting Indians' ongoing use of the mobile mHealth app AarogyaSetu. An extended technology adoption model (TAM) has been proposed and tested to achieve this wide goal, with the addition of three additional constructs: social influence, health consciousness, and trust in the app developer.
{"title":"Modeling the Prediction of Continued Usage of COVID-19 mhealth App in India","authors":"R. Mittal, A. Mittal, Arun Aggarwal","doi":"10.1109/CCGE50943.2021.9776421","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776421","url":null,"abstract":"Indian m-health app Aarogya Setu has made a significant contribution in terms of contactability tracing and disease management during the initial days of the COVID-19 pandemic, with its contact tracking approach to infectious individuals and its health tips for eliminating new coronaviruses. The goal of this study is to forecast whether or not Indian consumers will continue to use this app. According to previous studies, the context or setting has a substantial impact on the customer's perceived value. The current study's unique setting is to investigate the parameters impacting Indians' ongoing use of the mobile mHealth app AarogyaSetu. An extended technology adoption model (TAM) has been proposed and tested to achieve this wide goal, with the addition of three additional constructs: social influence, health consciousness, and trust in the app developer.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128509869","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776474
Anitha. K Jyoti, Bhanu Prakash, Ramesh.L Dean, M. Marsaline beno
At present reduced energy consumption at industrial site has prominent importance in the economy of the industry. Finding the areas of the energy wastes at different levels and estimating cost effective recommendations are the research challenges. With reference to past three years, various issues presently available in the industry are collected for analysis. With reference to the collected information, suitable recommendations are suggested for saving energy through suitable recommendation without investment, Recommendations suggested with Investment and Recommendations suggested with implementation of renewable power
{"title":"Comparative Energy Performance Analysis at Dyes and Coating Industry","authors":"Anitha. K Jyoti, Bhanu Prakash, Ramesh.L Dean, M. Marsaline beno","doi":"10.1109/CCGE50943.2021.9776474","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776474","url":null,"abstract":"At present reduced energy consumption at industrial site has prominent importance in the economy of the industry. Finding the areas of the energy wastes at different levels and estimating cost effective recommendations are the research challenges. With reference to past three years, various issues presently available in the industry are collected for analysis. With reference to the collected information, suitable recommendations are suggested for saving energy through suitable recommendation without investment, Recommendations suggested with Investment and Recommendations suggested with implementation of renewable power","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128859671","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}
Modern day software applications are required to have high availability and performance capabilities to ensure highly productive features and a smooth user experience. It becomes increasingly difficult for organizations to innovate with rapid building, testing and deployment of systems in static, monolithic environments. In order to ascertain the development of resilient applications, Kubernetes is widely used for distributed systems for workload scalability and orchestration of containers. The management of the system using Kubernetes becomes progressively inconvenient with increasing size and complexity. In order to make the process of Kubernetes configuration simpler and faster, Helm charts are used to preconfigure applications and automate the processes of development, testing and production. This paper proposes a method to ease the deployment of the enterprise application in Kubernetes using Helm charts. Our study shows that deployment of Kubernetes resources is simplified using Helm such that applications can be defined as a set of components in the minikube Kubernetes cluster. The experimental results of the proposed method show that there is 6.185 times speed improvement in the deployment process by using Helm. This makes it extremely influential for DevOps teams to improve their cluster management.
{"title":"Creating Helm Charts to ease deployment of Enterprise Application and its related Services in Kubernetes","authors":"Shivani Gokhale, Reetika Poosarla, Sanjeevani Tikar, Swapnali Gunjawate, Aparna Hajare, Shilpa Deshpande, Sourabh Gupta, Kanchan Karve","doi":"10.1109/CCGE50943.2021.9776450","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776450","url":null,"abstract":"Modern day software applications are required to have high availability and performance capabilities to ensure highly productive features and a smooth user experience. It becomes increasingly difficult for organizations to innovate with rapid building, testing and deployment of systems in static, monolithic environments. In order to ascertain the development of resilient applications, Kubernetes is widely used for distributed systems for workload scalability and orchestration of containers. The management of the system using Kubernetes becomes progressively inconvenient with increasing size and complexity. In order to make the process of Kubernetes configuration simpler and faster, Helm charts are used to preconfigure applications and automate the processes of development, testing and production. This paper proposes a method to ease the deployment of the enterprise application in Kubernetes using Helm charts. Our study shows that deployment of Kubernetes resources is simplified using Helm such that applications can be defined as a set of components in the minikube Kubernetes cluster. The experimental results of the proposed method show that there is 6.185 times speed improvement in the deployment process by using Helm. This makes it extremely influential for DevOps teams to improve their cluster management.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129433225","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776433
Amruta S Suryawanshi, M. J. Khurjekar
Agriculture plays an important role by contributing to the economy of India. 75% of the population has agriculture as their major occupation and only source of income. There are various parts in the process of production where we need to pay more attention to the higher productivity of crops. Many farmers face loss in yields every year due to diseases affecting the crops. A fast and automated system to detect the diseases on crops in the early stage can be very helpful in such situations. Having such a vast variety of types of crops grown in India, we will focus on cotton and turmeric crops in the Marathwada region, Maharashtra, India. Our proposed system aims to develop an auto-guided drone that can take the images of crop leaves as input. These images will then be processed by applying Convolutional Neural Network (CNN) to detect the diseases which are affecting the crops. This system will also help mark the most affected regions of fields. By using this system, we can increase the productivity of the crop
{"title":"Aerial Imagery for Plant Disease Detection by Using Machine Learning of Typical Crops in Marathwada","authors":"Amruta S Suryawanshi, M. J. Khurjekar","doi":"10.1109/CCGE50943.2021.9776433","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776433","url":null,"abstract":"Agriculture plays an important role by contributing to the economy of India. 75% of the population has agriculture as their major occupation and only source of income. There are various parts in the process of production where we need to pay more attention to the higher productivity of crops. Many farmers face loss in yields every year due to diseases affecting the crops. A fast and automated system to detect the diseases on crops in the early stage can be very helpful in such situations. Having such a vast variety of types of crops grown in India, we will focus on cotton and turmeric crops in the Marathwada region, Maharashtra, India. Our proposed system aims to develop an auto-guided drone that can take the images of crop leaves as input. These images will then be processed by applying Convolutional Neural Network (CNN) to detect the diseases which are affecting the crops. This system will also help mark the most affected regions of fields. By using this system, we can increase the productivity of the crop","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129594301","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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