Pub Date : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088416
Saswati Sahoo, Sushruta Mishra
Nowadays, the number of brain tumor cases among people is increasing globally across the world due to several reasons such as obesity, overweight, excess levels of stress in life, exposure to ionizing radiation, and many more. In previous years, many investigators have provided a range of solutions and effective tools for the identification and categorization of brain tumors. Nevertheless, the existing developed models for brain tumor identification and categorization have diverse limitations such as minimal accuracy and precision values. In this paper, the authors developed a novel model for the comparative analysis of the Progressive Growing-Generative Adversarial Network (PGGAN) with other data augmentation techniques for brain tumor classification. Because of the availability of finite datasets, the brain tumor classification algorithm along with the convolutional neural networks (CNNs) must be enhanced to be more competent for brain tumor classification and identification in real-time diagnosis. The outcome of the proposed model demonstrates that PGGAN delivers higher accuracy, as well as precision, and the Recall with the F1 score is 99.22%, 98.11%, 98.66%, and 97.45%, respectively. In the future, the developed model performance could be measured with other data augmentation techniques for larger datasets for performance constraints computations for further study and implementation of the model for real-time diagnosis of the patients.
{"title":"A Comparative Analysis of PGGAN with Other Data Augmentation Technique for Brain Tumor Classification","authors":"Saswati Sahoo, Sushruta Mishra","doi":"10.1109/ASSIC55218.2022.10088416","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088416","url":null,"abstract":"Nowadays, the number of brain tumor cases among people is increasing globally across the world due to several reasons such as obesity, overweight, excess levels of stress in life, exposure to ionizing radiation, and many more. In previous years, many investigators have provided a range of solutions and effective tools for the identification and categorization of brain tumors. Nevertheless, the existing developed models for brain tumor identification and categorization have diverse limitations such as minimal accuracy and precision values. In this paper, the authors developed a novel model for the comparative analysis of the Progressive Growing-Generative Adversarial Network (PGGAN) with other data augmentation techniques for brain tumor classification. Because of the availability of finite datasets, the brain tumor classification algorithm along with the convolutional neural networks (CNNs) must be enhanced to be more competent for brain tumor classification and identification in real-time diagnosis. The outcome of the proposed model demonstrates that PGGAN delivers higher accuracy, as well as precision, and the Recall with the F1 score is 99.22%, 98.11%, 98.66%, and 97.45%, respectively. In the future, the developed model performance could be measured with other data augmentation techniques for larger datasets for performance constraints computations for further study and implementation of the model for real-time diagnosis of the patients.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"38 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122122355","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 : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088377
Mahesh Kumar Morampudi, Nagamani Gonthina, Dinesh Reddy, K. S. Rao
Programming Skills play a crucial role in any computer engineering student's life to apply the concepts in solving any real world problem as well to crack a secure job in the dream company. To achieve this they should assess their performance in programming, analyze and improve their skills regularly. Many students are even undergoing mental stress and depression and even attempting suicides out of the stress if the considered scores and performance are not met. With the help of analyzing the programming skills one can enhance their scores and performance on a regular basis, introspect and can deliberately practice for better improvement. This reduces the stress, anxiety and depression on students' minds in securing good scores in their academics and in building their career to achieve the goal. This analysis helps even professors to improvise the teaching and learning outcomes of students and increase their performance in whichever field they are working in. We made a comparison of different machine learning algorithms based on 200 classification instances. This analysis helped us in analyzing the statistics of students' performance.
{"title":"Analyzing Student Performance in Programming Education Using Classification Techniques","authors":"Mahesh Kumar Morampudi, Nagamani Gonthina, Dinesh Reddy, K. S. Rao","doi":"10.1109/ASSIC55218.2022.10088377","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088377","url":null,"abstract":"Programming Skills play a crucial role in any computer engineering student's life to apply the concepts in solving any real world problem as well to crack a secure job in the dream company. To achieve this they should assess their performance in programming, analyze and improve their skills regularly. Many students are even undergoing mental stress and depression and even attempting suicides out of the stress if the considered scores and performance are not met. With the help of analyzing the programming skills one can enhance their scores and performance on a regular basis, introspect and can deliberately practice for better improvement. This reduces the stress, anxiety and depression on students' minds in securing good scores in their academics and in building their career to achieve the goal. This analysis helps even professors to improvise the teaching and learning outcomes of students and increase their performance in whichever field they are working in. We made a comparison of different machine learning algorithms based on 200 classification instances. This analysis helped us in analyzing the statistics of students' performance.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122611595","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 : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088354
Binu P. K, Thejas Menon, Javed Harees
True random number generation is essential for modern and future security and cryptography. This paper surveys five existing methods of using audio and video to generate numbers, and compares their hardware, software, and randomness to find the best method for TRNG. The entropy of each method is compared, and the randomness of each method can be found. Each paper generates random numbers by utilizing the inherent noise created by transitioning analogue data to digital data, unlike other TRNG methods which use the conditions of internal hardware, erroneous data from wireless networks, or other non-noise-based methods.
{"title":"Survey On Using Audio Video for True Random Number Generation","authors":"Binu P. K, Thejas Menon, Javed Harees","doi":"10.1109/ASSIC55218.2022.10088354","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088354","url":null,"abstract":"True random number generation is essential for modern and future security and cryptography. This paper surveys five existing methods of using audio and video to generate numbers, and compares their hardware, software, and randomness to find the best method for TRNG. The entropy of each method is compared, and the randomness of each method can be found. Each paper generates random numbers by utilizing the inherent noise created by transitioning analogue data to digital data, unlike other TRNG methods which use the conditions of internal hardware, erroneous data from wireless networks, or other non-noise-based methods.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124541389","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 : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088328
D. D. Priya, A. Kiran, P. Purushotham
Internet of Things devices collect and share data (IoT). Internet connections and emerging technologies like IoT offer privacy and security challenges, and this trend is anticipated to develop quickly. Internet of Things intrusions are everywhere. Businesses are investing more to detect these threats. Institutes choose accurate testing and verification procedures. In recent years, IoT utilisation has increasingly risen in healthcare. Where IoT applications gained popular among technologists. IoT devices' energy limits and scalability raise privacy and security problems. Experts struggle to make IoT devices more safe and private. This paper provides a machine-learning-based IDS for IoT network threats (ML-IDS). This study aims to implement ML-supervised IDS for IoT. We're going with a centralised, lightweight IDS. Here, we compare seven popular categorization techniques on three data sets. The decision tree algorithm shows the best intrusion detection results.
{"title":"Lightweight Intrusion Detection System(L-IDS) for the Internet of Things","authors":"D. D. Priya, A. Kiran, P. Purushotham","doi":"10.1109/ASSIC55218.2022.10088328","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088328","url":null,"abstract":"Internet of Things devices collect and share data (IoT). Internet connections and emerging technologies like IoT offer privacy and security challenges, and this trend is anticipated to develop quickly. Internet of Things intrusions are everywhere. Businesses are investing more to detect these threats. Institutes choose accurate testing and verification procedures. In recent years, IoT utilisation has increasingly risen in healthcare. Where IoT applications gained popular among technologists. IoT devices' energy limits and scalability raise privacy and security problems. Experts struggle to make IoT devices more safe and private. This paper provides a machine-learning-based IDS for IoT network threats (ML-IDS). This study aims to implement ML-supervised IDS for IoT. We're going with a centralised, lightweight IDS. Here, we compare seven popular categorization techniques on three data sets. The decision tree algorithm shows the best intrusion detection results.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115786627","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 : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088391
Deepak Sharma, Anurag Saxena, Z. Ali, Neeraj Yadav
In wireless power transfer, does not require the flow of electrons in any material like conductor. In this process electrical energy is originated from the transmission line. It uses a wearable antenna like textile or cloths. The most important applications of the wearable antenna are Wi-Fi or WLAN. on simulating the design the S11 result of textile antenna gives one resonant frequency at 5.24 GHz. The thickness of the textile material is 1mm with dielectric constant 1.7. The transfer of electrical energy wirelessly is too difficult But with the help of receiver antenna makes it possible. Circuit with the feedback upon the frequency of the input voltage are also known as filters. Band pass filter is used in this because it passes the particular frequency range. After that bridge rectifier is utilized which converts radio frequency signal (AC) into DC signal.
{"title":"Rectification of Electrical Energy Using Band Pass Filter","authors":"Deepak Sharma, Anurag Saxena, Z. Ali, Neeraj Yadav","doi":"10.1109/ASSIC55218.2022.10088391","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088391","url":null,"abstract":"In wireless power transfer, does not require the flow of electrons in any material like conductor. In this process electrical energy is originated from the transmission line. It uses a wearable antenna like textile or cloths. The most important applications of the wearable antenna are Wi-Fi or WLAN. on simulating the design the S11 result of textile antenna gives one resonant frequency at 5.24 GHz. The thickness of the textile material is 1mm with dielectric constant 1.7. The transfer of electrical energy wirelessly is too difficult But with the help of receiver antenna makes it possible. Circuit with the feedback upon the frequency of the input voltage are also known as filters. Band pass filter is used in this because it passes the particular frequency range. After that bridge rectifier is utilized which converts radio frequency signal (AC) into DC signal.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125027409","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 : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088302
Deepa U. Mishra, Preeti Jain
The advent of the “Smartgrid” is a result of the new trend of managing the increasing power demand by harnessing the potential of distributed energy resources (DER) within the current low voltage distribution framework. Even while the distribution networks benefit greatly from the Smartgrid, the integration problems with renewable and synchronous DERs have rendered protection jobs inherently difficult. When compared to synchronous DERs, which can endure fault current up to 10 times, renewable DERs' dynamic producing behaviour, which is restricted to carrying fault current up to 2–3 times the rated current, creates a clear distinction between the two in terms of operating circumstances. As a result of these factors, the accompanying security challenges become even more difficult. Because the magnitude of fault current varies according to mode, there is a significant variation in the amount of fault current between islanded and grid-connected modes. As a result, it is necessary to develop an accurate and dependable approach that can operate in both modes and fulfil the Smartgrid's protection needs without being influenced by harmonics associated with power electronic interface devices and non-linear loads. In this context, a protection strategy for the Smartgrid has been presented that is based on the joint framework of discrete wavelet transform (DWT) and Bagged decision tree based data-mining approach.
{"title":"A Reliable Protection Scheme for Smartgrid Based On Wavelet Transform and Ensemble Classifier","authors":"Deepa U. Mishra, Preeti Jain","doi":"10.1109/ASSIC55218.2022.10088302","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088302","url":null,"abstract":"The advent of the “Smartgrid” is a result of the new trend of managing the increasing power demand by harnessing the potential of distributed energy resources (DER) within the current low voltage distribution framework. Even while the distribution networks benefit greatly from the Smartgrid, the integration problems with renewable and synchronous DERs have rendered protection jobs inherently difficult. When compared to synchronous DERs, which can endure fault current up to 10 times, renewable DERs' dynamic producing behaviour, which is restricted to carrying fault current up to 2–3 times the rated current, creates a clear distinction between the two in terms of operating circumstances. As a result of these factors, the accompanying security challenges become even more difficult. Because the magnitude of fault current varies according to mode, there is a significant variation in the amount of fault current between islanded and grid-connected modes. As a result, it is necessary to develop an accurate and dependable approach that can operate in both modes and fulfil the Smartgrid's protection needs without being influenced by harmonics associated with power electronic interface devices and non-linear loads. In this context, a protection strategy for the Smartgrid has been presented that is based on the joint framework of discrete wavelet transform (DWT) and Bagged decision tree based data-mining approach.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122046293","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 : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088329
Arpan Maity, Ritobina Ghosh, Shidhu Bhadra
In the field of Computer Science, proper storage and analysis of data is one of the most trending topics. The development of modern tools and techniques, has come down as a blessing for this. But along with the blessing, comes the curse of being easily attacked and the privacy of the data being vulnerable. The attackers and the hackers are becoming very smart and with their modern equipment, they can break into any system. For this several methods have been developed to save the privacy of our data. Out of these methods, the symmetric key method and the asymmetric key method are the most popular ones. Though both of the methods are powerful enough, they come with their own set of disadvantages. In this research work, an approach has been taken, where the combination of both the above spoken methods are used, making use of the advantages of both the methods, where both of them are also cancelling out each others disadvantages. The results confirmed that the accuracy, efficiency and the security of the algorithms are good enough, so that it can be used to deal with real world problems.
{"title":"Image Encryption Using RSA and Advanced Caesar Cipher Method","authors":"Arpan Maity, Ritobina Ghosh, Shidhu Bhadra","doi":"10.1109/ASSIC55218.2022.10088329","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088329","url":null,"abstract":"In the field of Computer Science, proper storage and analysis of data is one of the most trending topics. The development of modern tools and techniques, has come down as a blessing for this. But along with the blessing, comes the curse of being easily attacked and the privacy of the data being vulnerable. The attackers and the hackers are becoming very smart and with their modern equipment, they can break into any system. For this several methods have been developed to save the privacy of our data. Out of these methods, the symmetric key method and the asymmetric key method are the most popular ones. Though both of the methods are powerful enough, they come with their own set of disadvantages. In this research work, an approach has been taken, where the combination of both the above spoken methods are used, making use of the advantages of both the methods, where both of them are also cancelling out each others disadvantages. The results confirmed that the accuracy, efficiency and the security of the algorithms are good enough, so that it can be used to deal with real world problems.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123987265","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 : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088412
Uday Bhanu Ghosh, Rohan Sharma
This work proposes to channelize the conventional longitudinal behavior of sound which diverges in every direction after its generation to a beam like behavior seen in transverse waves, which is already conceived in a device named as parametric speaker. On top of this, using technologies such as AI, self-learning, and decision-making capabilities can be endorsed in the hardware-based device, exhausting its full capabilities. The goal of the proposed work is to provide an invisible screening and privacy to the individuals in public and semi-public areas associated with verbal mode of communication. The underlying work focuses on using the unconventional behavior of sound, possessing beam like properties produced through Artificial means by interference and Superposition principle, applicable to sound which is constructed by Parametric Speaker also known as directional Speaker. The following work in this paper attempts to showcase the possibilities of using and harnessing this specific sound properties with sophisticated technologies such as ML and Deep Learning to create semi private areas in public spaces which can not only help people within different age groups (mostly elderly population) but can also help people who are handicapped (such as visually impared people who can only receive information through auditory channels), the scope of the proposed work is not only limited to impared people but, also to general population, with the objective to increase the conventional information transfer system into personalized data delivery service through voice and speech.
{"title":"Machine Intelligence Enabled Parametric Speaker: An Invention Towards Experience Sound","authors":"Uday Bhanu Ghosh, Rohan Sharma","doi":"10.1109/ASSIC55218.2022.10088412","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088412","url":null,"abstract":"This work proposes to channelize the conventional longitudinal behavior of sound which diverges in every direction after its generation to a beam like behavior seen in transverse waves, which is already conceived in a device named as parametric speaker. On top of this, using technologies such as AI, self-learning, and decision-making capabilities can be endorsed in the hardware-based device, exhausting its full capabilities. The goal of the proposed work is to provide an invisible screening and privacy to the individuals in public and semi-public areas associated with verbal mode of communication. The underlying work focuses on using the unconventional behavior of sound, possessing beam like properties produced through Artificial means by interference and Superposition principle, applicable to sound which is constructed by Parametric Speaker also known as directional Speaker. The following work in this paper attempts to showcase the possibilities of using and harnessing this specific sound properties with sophisticated technologies such as ML and Deep Learning to create semi private areas in public spaces which can not only help people within different age groups (mostly elderly population) but can also help people who are handicapped (such as visually impared people who can only receive information through auditory channels), the scope of the proposed work is not only limited to impared people but, also to general population, with the objective to increase the conventional information transfer system into personalized data delivery service through voice and speech.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129659952","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}
Nowadays microwave communities are working on the design and development of the dual band, triple band & wide band antennas with partial ground. The customers prefer compact devices for WLAN, Bluetooth, PCS, and WiMAX applications, which are frequently used in tablets, medical instruments, smart phones, portable laptops and handheld electronic gadgets. The proposed antenna is consisting of a partial ground and slotted circular patch with line feed. The Triple bandwidth of proposed antenna is 45.77%, 69.20% and 12.69% suitable for triple band application.
{"title":"Semi Circle Slotted Triangular Shape Antenna Using Flexible Material","authors":"Deepak Sharma, Vinod Kumar Singh, Anupam Vyas, Neetendra Kumar, Rajesh Kumar Dwivedi","doi":"10.1109/ASSIC55218.2022.10088293","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088293","url":null,"abstract":"Nowadays microwave communities are working on the design and development of the dual band, triple band & wide band antennas with partial ground. The customers prefer compact devices for WLAN, Bluetooth, PCS, and WiMAX applications, which are frequently used in tablets, medical instruments, smart phones, portable laptops and handheld electronic gadgets. The proposed antenna is consisting of a partial ground and slotted circular patch with line feed. The Triple bandwidth of proposed antenna is 45.77%, 69.20% and 12.69% suitable for triple band application.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129136068","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 : 2022-11-19DOI: 10.1109/ASSIC55218.2022.10088408
N. Sirisha, Pasunoori Devi, P. Purushotham, D. SaiSri, Vemuri Laxmi
Agriculture is one field that has a big impact on people's lives and their economic situation. Poor management is the cause of agricultural losses. Farmers' lack of knowledge about disease leads to reduced yields. Farmer helpline call-centers are accessible, although they do not provide assistance 24 hours a day, seven days a week, and communication might be problematic at times. Farmers who are unable to effectively describe disease over the phone require an investigation of the afflicted leaf area. Since photographs and videos of crops provide a better view of the crop and agricultural scientists can provide a better way to fix difficulties related to healthy crop, farmers have not been informed. Because to advancements in technology, equipment are now capable of recognizing and detecting plant illnesses. Recognizing disease early on can help to speed up treatment and reduce the impact on harvest. As a result, the focus of this research is on employing image processing to identify plant diseases.
{"title":"Leaf Disease Identification and Remedy Recommendation System","authors":"N. Sirisha, Pasunoori Devi, P. Purushotham, D. SaiSri, Vemuri Laxmi","doi":"10.1109/ASSIC55218.2022.10088408","DOIUrl":"https://doi.org/10.1109/ASSIC55218.2022.10088408","url":null,"abstract":"Agriculture is one field that has a big impact on people's lives and their economic situation. Poor management is the cause of agricultural losses. Farmers' lack of knowledge about disease leads to reduced yields. Farmer helpline call-centers are accessible, although they do not provide assistance 24 hours a day, seven days a week, and communication might be problematic at times. Farmers who are unable to effectively describe disease over the phone require an investigation of the afflicted leaf area. Since photographs and videos of crops provide a better view of the crop and agricultural scientists can provide a better way to fix difficulties related to healthy crop, farmers have not been informed. Because to advancements in technology, equipment are now capable of recognizing and detecting plant illnesses. Recognizing disease early on can help to speed up treatment and reduce the impact on harvest. As a result, the focus of this research is on employing image processing to identify plant diseases.","PeriodicalId":441406,"journal":{"name":"2022 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122253341","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：