The faults in a power system may be of various nature and they may affect the stability of the power system by causing outage of the line, there by overloading other connected lines and also causing cascading effect in the system. In order to access the nature of fault and analyze the impact of the same in a power system, fault analysis is required to be carried out as the same will be useful for the system operation and to take quick decisions in securing the system. In this paper we discuss the various types of faults in EHV system that may occur in line or substation. These faults are identified by Numerical relays which use IEDs [Intelligent Electronic Device]. The faults identified includes symmetrical and unsymmetrical faults in power system. Further in this project, we have taken into consideration the theoretical and practical study of the fault analysis through Numerical relays. In case of occurrence of Transient faults, Auto re-closure works with dead time of 1 sec. Current, voltage, Breaker status (open, close) are graphically represented by Disturbance Recorder. Events are recorded by Event logger. The above mentioned project for faults and analysis of faults in line or substation were carried out at Power grid Corporation Limited, 400 / 230kv Sub-Station Shoolagiri.
{"title":"Power System Fault Detection and Analysis Using Numerical Relay in Power grid Corporation Limited, Shoolagiri","authors":"","doi":"10.46632/eae/2/1/21","DOIUrl":"https://doi.org/10.46632/eae/2/1/21","url":null,"abstract":"The faults in a power system may be of various nature and they may affect the stability of the power system by causing outage of the line, there by overloading other connected lines and also causing cascading effect in the system. In order to access the nature of fault and analyze the impact of the same in a power system, fault analysis is required to be carried out as the same will be useful for the system operation and to take quick decisions in securing the system. In this paper we discuss the various types of faults in EHV system that may occur in line or substation. These faults are identified by Numerical relays which use IEDs [Intelligent Electronic Device]. The faults identified includes symmetrical and unsymmetrical faults in power system. Further in this project, we have taken into consideration the theoretical and practical study of the fault analysis through Numerical relays. In case of occurrence of Transient faults, Auto re-closure works with dead time of 1 sec. Current, voltage, Breaker status (open, close) are graphically represented by Disturbance Recorder. Events are recorded by Event logger. The above mentioned project for faults and analysis of faults in line or substation were carried out at Power grid Corporation Limited, 400 / 230kv Sub-Station Shoolagiri.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"44 S207","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139146543","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}
This project presents a novel localization method for electric vehicles (EVs) charging through wireless power transmission (WPT) and solar based charging. With the proposed technique, the wireless charging system can self-determine the most efficient coil to transmit power at the EV’s position based on the proximity sensors activated by its wheels. To ensure optimal charging, our approach involves measurement of the transfer efficiency of individual transmission coil to determine the most efficient one to be used. This not only improves the charging performance, but also minimizes energy losses by autonomously activating only the coils with the highest transfer efficiencies. The results show that with the proposed system it is possible to detect the coil with maximum transmitting efficiency without the use of actual power transmission and comparison of the measured efficiency. This project also proves that with the proposed charger set-up, the position of the receiver coil can be detected almost instantly and get charge while moving in the road. This indeed saves energy and boosts the charging time. Here we also introduce the solar panel in the top of the EV which indeed saves energy and boosts the charging time in day time. The vehicle battery voltage and current data can be monitoring continuously and updated in online.
{"title":"Wireless Charging of Electric Vehicle While Moving with dual input Sources","authors":"","doi":"10.46632/eae/2/1/20","DOIUrl":"https://doi.org/10.46632/eae/2/1/20","url":null,"abstract":"This project presents a novel localization method for electric vehicles (EVs) charging through wireless power transmission (WPT) and solar based charging. With the proposed technique, the wireless charging system can self-determine the most efficient coil to transmit power at the EV’s position based on the proximity sensors activated by its wheels. To ensure optimal charging, our approach involves measurement of the transfer efficiency of individual transmission coil to determine the most efficient one to be used. This not only improves the charging performance, but also minimizes energy losses by autonomously activating only the coils with the highest transfer efficiencies. The results show that with the proposed system it is possible to detect the coil with maximum transmitting efficiency without the use of actual power transmission and comparison of the measured efficiency. This project also proves that with the proposed charger set-up, the position of the receiver coil can be detected almost instantly and get charge while moving in the road. This indeed saves energy and boosts the charging time. Here we also introduce the solar panel in the top of the EV which indeed saves energy and boosts the charging time in day time. The vehicle battery voltage and current data can be monitoring continuously and updated in online.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"27 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139168506","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}
The fingerprint vehicle starter project aims to increase the security of vehicles by using biometric authentication technology. Biometrics system can be used as a good and effective security option. An important and very reliable human identification method is fingerprint identification. Vehicle safety has become a serious problem as the frequency of crime has increased. Vehicle keys are a big concern these days since they are easily forgotten or lost when carried. At start, this technology lets the customer to authenticate by scanning their unique fingerprint. The system uses a fingerprint scanner to identify the authorized user of the vehicle, allowing them to start the engine. This project is designed to prevent car theft and improve user convenience, as drivers will not need to carry keys with them. The system allows multiple users to register as authorized users. When into monitoring mode, the system checks for users to scan. On scanning, the system checks if user is authorized user. The system is implemented using an Arduino microcontroller and a fingerprint sensor module, which communicate with the vehicle's ignition system. The project's success is evaluated based on its accuracy in identifying the authorized user and its reliability in preventing unauthorized access to the vehicle. This project has the potential to significantly improve vehicle security and enhance user experience. This provides safe and worry-free way to begin the engine or automobile. The fingerprint vehicle starter project aims to increase the security of vehicles by using biometric authentication technology. Biometrics system can be used as a good and effective security option. An important and very reliable human identification method is fingerprint Identification.
{"title":"Finger Print Sensing Vehicle Starter","authors":"","doi":"10.46632/eae/2/1/16","DOIUrl":"https://doi.org/10.46632/eae/2/1/16","url":null,"abstract":"The fingerprint vehicle starter project aims to increase the security of vehicles by using biometric authentication technology. Biometrics system can be used as a good and effective security option. An important and very reliable human identification method is fingerprint identification. Vehicle safety has become a serious problem as the frequency of crime has increased. Vehicle keys are a big concern these days since they are easily forgotten or lost when carried. At start, this technology lets the customer to authenticate by scanning their unique fingerprint. The system uses a fingerprint scanner to identify the authorized user of the vehicle, allowing them to start the engine. This project is designed to prevent car theft and improve user convenience, as drivers will not need to carry keys with them. The system allows multiple users to register as authorized users. When into monitoring mode, the system checks for users to scan. On scanning, the system checks if user is authorized user. The system is implemented using an Arduino microcontroller and a fingerprint sensor module, which communicate with the vehicle's ignition system. The project's success is evaluated based on its accuracy in identifying the authorized user and its reliability in preventing unauthorized access to the vehicle. This project has the potential to significantly improve vehicle security and enhance user experience. This provides safe and worry-free way to begin the engine or automobile. The fingerprint vehicle starter project aims to increase the security of vehicles by using biometric authentication technology. Biometrics system can be used as a good and effective security option. An important and very reliable human identification method is fingerprint Identification.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130598918","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}
A tool for individualized consumer pleasure is augmented reality, particularly when it comes to the interior and exterior of furniture. Customers truly want to be able to visualise how the products will appear in their homes or places of business. The consumer or user wants to visualise virtual content for interior design concepts in real time, which AR enables. This study suggests a novel method for integrating augmented reality (AR) technology into interior design, allowing users to share information about 3D virtual furniture and view it on a flexible, dynamic user interface. One way to think of augmented reality technology is as a blend of actual space and virtual items. In an AR environment, the user can observe and modify the virtual furniture in real-time on the screen.
{"title":"Novel Application of Furniture Product Using Augmented Reality","authors":"","doi":"10.46632/eae/2/1/17","DOIUrl":"https://doi.org/10.46632/eae/2/1/17","url":null,"abstract":"A tool for individualized consumer pleasure is augmented reality, particularly when it comes to the interior and exterior of furniture. Customers truly want to be able to visualise how the products will appear in their homes or places of business. The consumer or user wants to visualise virtual content for interior design concepts in real time, which AR enables. This study suggests a novel method for integrating augmented reality (AR) technology into interior design, allowing users to share information about 3D virtual furniture and view it on a flexible, dynamic user interface. One way to think of augmented reality technology is as a blend of actual space and virtual items. In an AR environment, the user can observe and modify the virtual furniture in real-time on the screen.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125988892","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}
P. Divya, Y. Dhamini, lekha Sharu, Suprajaa Sree Vishnu
The system proposed in this project uses an IoT-based ESP32 Node MCU and a heart rate sensor to detect heart attacks and monitor heart rate. The device has the ability to measure the user's heart rate in real-time and spot irregularities that might be signs of a possible heart attack. The proposed system also has the ability to upload the collected data to the cloud for additional processing and archiving. A Max 10300 heart rate sensor, an ESP32 Node MCU, and a microcontroller to process and analyse the gathered data make up the system. Wi-Fi connectivity is used by the system to send data to the cloud, which can both the patients' own and the healthcare professionals' access. The suggested system has a number of benefits, including continuous monitoring, real-time data processing, and automatic heart attack detection, all of which have the potential to save lives. A noteworthy development in the healthcare industry is the heart attack diagnosis and heart rate monitoring system employing the Internet of Things-based ESP32 Node MCU and Max 10300 heart rate sensor. For people who want to track their heart health in real-time and look for any potential irregularities, it provides a practical and affordable alternative. Healthcare professionals might also utilize the technology to remotely check the heart health of their patients and take emergency action
{"title":"Heart Attack Detection and Heart Rate Monitoring System Using IOT","authors":"P. Divya, Y. Dhamini, lekha Sharu, Suprajaa Sree Vishnu","doi":"10.46632/eae/2/1/19","DOIUrl":"https://doi.org/10.46632/eae/2/1/19","url":null,"abstract":"The system proposed in this project uses an IoT-based ESP32 Node MCU and a heart rate sensor to detect heart attacks and monitor heart rate. The device has the ability to measure the user's heart rate in real-time and spot irregularities that might be signs of a possible heart attack. The proposed system also has the ability to upload the collected data to the cloud for additional processing and archiving. A Max 10300 heart rate sensor, an ESP32 Node MCU, and a microcontroller to process and analyse the gathered data make up the system. Wi-Fi connectivity is used by the system to send data to the cloud, which can both the patients' own and the healthcare professionals' access. The suggested system has a number of benefits, including continuous monitoring, real-time data processing, and automatic heart attack detection, all of which have the potential to save lives. A noteworthy development in the healthcare industry is the heart attack diagnosis and heart rate monitoring system employing the Internet of Things-based ESP32 Node MCU and Max 10300 heart rate sensor. For people who want to track their heart health in real-time and look for any potential irregularities, it provides a practical and affordable alternative. Healthcare professionals might also utilize the technology to remotely check the heart health of their patients and take emergency action","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126251418","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}
In the last decade, researchers have been attracted by the drone and its antenna design. Few years back, drone was used only for surveillance but now drone is using in various filed i.e., weather forecasting, transportation, communication, search & rescue etc. Antennas are the most important part of drone or UAV. Designing of antennas for drone is the challenging task for the researchers without increasing the overall weight of drone. In this article, classification of drone as per their weight, altitude and applications, different types of antennas have been discussed with its challenge. Different antenna design has been discussed and compared with different parameters.
{"title":"Design of UAV Antennas and Challenges: Review","authors":"Jainwal Kapil, S. Vivek, Shrivastava Vineet","doi":"10.46632/eae/2/1/2","DOIUrl":"https://doi.org/10.46632/eae/2/1/2","url":null,"abstract":"In the last decade, researchers have been attracted by the drone and its antenna design. Few years back, drone was used only for surveillance but now drone is using in various filed i.e., weather forecasting, transportation, communication, search & rescue etc. Antennas are the most important part of drone or UAV. Designing of antennas for drone is the challenging task for the researchers without increasing the overall weight of drone. In this article, classification of drone as per their weight, altitude and applications, different types of antennas have been discussed with its challenge. Different antenna design has been discussed and compared with different parameters.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124059688","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}
Chepati Dhana Lakshmi, Gajjala Satish Kumar Reddy, Chukka Yaswanth Kumar, Chinta Mounika, T. Ravi Sekhar
Weeds compete with crops for water, nutrients, and sunshine, which is one of the most detrimental restraints on crop development. They also constitute a danger to agricultural output. The loss of worldwide productivity due to weeds and pests is likely to rise over the next few years. Using herbicide spray particularly in the field where the weeds are present is an efficient technique to manage the problem. For the weed control system to be properly deployed, weeds must be accurately and precisely detected. Traditional weed management techniques, however, take a long time and a lot of human resources, and they may have an adverse effect on the environment. To overcome this a model called Automatic weed management, a potential remedy that makes use of deep learning and machine learning approaches, has emerged to deal with these issues. This method increases agricultural productivity and reduces herbicides.
{"title":"Weed Identification in Agricultural Fields Using Machine Learning Techniques","authors":"Chepati Dhana Lakshmi, Gajjala Satish Kumar Reddy, Chukka Yaswanth Kumar, Chinta Mounika, T. Ravi Sekhar","doi":"10.46632/eae/2/1/14","DOIUrl":"https://doi.org/10.46632/eae/2/1/14","url":null,"abstract":"Weeds compete with crops for water, nutrients, and sunshine, which is one of the most detrimental restraints on crop development. They also constitute a danger to agricultural output. The loss of worldwide productivity due to weeds and pests is likely to rise over the next few years. Using herbicide spray particularly in the field where the weeds are present is an efficient technique to manage the problem. For the weed control system to be properly deployed, weeds must be accurately and precisely detected. Traditional weed management techniques, however, take a long time and a lot of human resources, and they may have an adverse effect on the environment. To overcome this a model called Automatic weed management, a potential remedy that makes use of deep learning and machine learning approaches, has emerged to deal with these issues. This method increases agricultural productivity and reduces herbicides.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"16 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125707392","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}
N. Supritha, Varshini S Kashyap, Swati Subray, S. Hegde, Vinay
The current global population is expected to reach 9.7 billion by 2050, which will put immense pressure on the food production system to meet the growing demand. However, the traditional farming system alone is not sufficient to meet this demand due to various limitations such as limited land availability, environmental factors, and inefficient use of resources. As a result, there is a real need for adapting new farming systems that can help stimulate plant growth faster and more efficiently. One such technique is Hydroponics, which is a soil-less method of growing plants using mineral nutrient solutions in a water solvent. Hydroponics has been proven to be more efficient than traditional farming systems, as it allows for higher crop yields in less time and with fewer resources. Therefore, creating awareness about this new farming technique and providing farmers with the necessary resources and support to implement it on their farms can help address the food production challenges. In addition to the farming technique, farmers are also facing issues related to intermediaries, who take a cut of their profits, resulting in losses for the farmers. To address this problem, a platform is being created to enable direct interaction between farmers and buyers By implementing this solution, farmers can increase their income, improve their standard of living, and contribute to the development of a sustainable and efficient food production system.
{"title":"Hydroponics – A smart farming and Implementation of Ecommerce website for farmers based on full stack","authors":"N. Supritha, Varshini S Kashyap, Swati Subray, S. Hegde, Vinay","doi":"10.46632/eae/2/1/11","DOIUrl":"https://doi.org/10.46632/eae/2/1/11","url":null,"abstract":"The current global population is expected to reach 9.7 billion by 2050, which will put immense pressure on the food production system to meet the growing demand. However, the traditional farming system alone is not sufficient to meet this demand due to various limitations such as limited land availability, environmental factors, and inefficient use of resources. As a result, there is a real need for adapting new farming systems that can help stimulate plant growth faster and more efficiently. One such technique is Hydroponics, which is a soil-less method of growing plants using mineral nutrient solutions in a water solvent. Hydroponics has been proven to be more efficient than traditional farming systems, as it allows for higher crop yields in less time and with fewer resources. Therefore, creating awareness about this new farming technique and providing farmers with the necessary resources and support to implement it on their farms can help address the food production challenges. In addition to the farming technique, farmers are also facing issues related to intermediaries, who take a cut of their profits, resulting in losses for the farmers. To address this problem, a platform is being created to enable direct interaction between farmers and buyers By implementing this solution, farmers can increase their income, improve their standard of living, and contribute to the development of a sustainable and efficient food production system.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115801820","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}
As target detection in remote sensing imaging depends on aircraft type recognition, it is essential in both civil and military applications. The job is made more difficult by the existence of fine-grained features, which can result in significant intra-class changes due to variations in size, posture, and angle, as well as modest inter class changes due to very similar subcategories. This kind of system can be helpful for military security as recognition of the type of aircraft is very critical to the decisions being made. There are several existing ways which uses methods like Radar System and Radio footprints, Speed etc., to detect type of Aircraft. Although these methods are massively costly and still cannot detect the type of Aircraft accurately. In this paper aircraft is detected using ResNet-50, Advance State of Art Object Detection Algorithm implementing in Anaconda tool with train accuracy is 98% & validate accuracy is 75%. A crucial area of artificial intelligence is object detection, which enables computer systems to perceive their surroundings by identifying things in visual pictures or movies. In case of any dangerous Aircraft, the system will have capability to raise alarm and Alert using Audio Sirens. The software requirement for this project is python, 3.6/anaconda, or newer and necessary python modules.
{"title":"Real Time Web-based System to Detect Military Aircraft Using RESNET-50 Algorithm","authors":"C. Venkata Sudhakar, Limbakar Deekshitha, Charan Kummari, Rauniyar Pintu Sah, Mahathi Kessamsetty","doi":"10.46632/eae/2/1/13","DOIUrl":"https://doi.org/10.46632/eae/2/1/13","url":null,"abstract":"As target detection in remote sensing imaging depends on aircraft type recognition, it is essential in both civil and military applications. The job is made more difficult by the existence of fine-grained features, which can result in significant intra-class changes due to variations in size, posture, and angle, as well as modest inter class changes due to very similar subcategories. This kind of system can be helpful for military security as recognition of the type of aircraft is very critical to the decisions being made. There are several existing ways which uses methods like Radar System and Radio footprints, Speed etc., to detect type of Aircraft. Although these methods are massively costly and still cannot detect the type of Aircraft accurately. In this paper aircraft is detected using ResNet-50, Advance State of Art Object Detection Algorithm implementing in Anaconda tool with train accuracy is 98% & validate accuracy is 75%. A crucial area of artificial intelligence is object detection, which enables computer systems to perceive their surroundings by identifying things in visual pictures or movies. In case of any dangerous Aircraft, the system will have capability to raise alarm and Alert using Audio Sirens. The software requirement for this project is python, 3.6/anaconda, or newer and necessary python modules.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114785287","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}
Rayavarapu V. Ch Sekhar Rao, P. Divya, K. Ram Mohan, M. Murali Krishna
Plants play an essential role in climate change, agriculture industry and a country’s economy. There by taking care of plants is very crucial. Just like humans, plants are affected by several disease caused by bacteria, fungi and virus. Identification of these disease timely and curing them is essential to prevent whole plant from destruction. Identification of the plant leaf diseases is the key to preventing the losses in the yield and quantity of the agricultural product. Most of the countries depend upon agriculture. Due to the factors like diseases, pest attacks and sudden change in whether condition, the productivity of crop decreases. The studies of the plant diseases mean the studies of visually observable patterns seen on the plants. It takes long time and difficult to detect a disease in a plant manually. Hence, Deep Learning is used for detection of plant diseases. For this approach, Convolution neural networks will be used for classification based on learning with some training samples of Plant leaves like wheat. The algorithm and method that are used here is convolution neural network (CNN) by using EfficientnetB3 architecture using the Python programming. Overall, the approach of training deep learning models on increasingly large and publicly available image datasets presents a clear path towards crop disease diagnosis on a massive global scale. Finally, the simulated result shows the disease of the plant and how much area it is affected.
{"title":"Development Of Deep Learning Model for Wheat Disease Identification and Classification","authors":"Rayavarapu V. Ch Sekhar Rao, P. Divya, K. Ram Mohan, M. Murali Krishna","doi":"10.46632/eae/2/1/12","DOIUrl":"https://doi.org/10.46632/eae/2/1/12","url":null,"abstract":"Plants play an essential role in climate change, agriculture industry and a country’s economy. There by taking care of plants is very crucial. Just like humans, plants are affected by several disease caused by bacteria, fungi and virus. Identification of these disease timely and curing them is essential to prevent whole plant from destruction. Identification of the plant leaf diseases is the key to preventing the losses in the yield and quantity of the agricultural product. Most of the countries depend upon agriculture. Due to the factors like diseases, pest attacks and sudden change in whether condition, the productivity of crop decreases. The studies of the plant diseases mean the studies of visually observable patterns seen on the plants. It takes long time and difficult to detect a disease in a plant manually. Hence, Deep Learning is used for detection of plant diseases. For this approach, Convolution neural networks will be used for classification based on learning with some training samples of Plant leaves like wheat. The algorithm and method that are used here is convolution neural network (CNN) by using EfficientnetB3 architecture using the Python programming. Overall, the approach of training deep learning models on increasingly large and publicly available image datasets presents a clear path towards crop disease diagnosis on a massive global scale. Finally, the simulated result shows the disease of the plant and how much area it is affected.","PeriodicalId":446446,"journal":{"name":"Electrical and Automation Engineering","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133711759","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：