Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009396
K. Dixit, Arti Badhoutiya
Floating photovoltaic (FPV) systems are a new technology that can be used to generate electricity on water bodies. It is crucial to assess the current state and future expectations for technological advancements for solar power generation with value-added solutions, particularly since floating photovoltaic systems have facilities that float on the surface.India, which has a high consumption for energy and a dearth of urban waste land for solar photovoltaic plants, can capture solar energy through the use of floating PV plant technology. To achieve sustainable objectives the establishment of floating solar plants, or solar arrays above floating structures on water bodies, is regularly encouraged by the government.India is among the blessed countries that have around 400 rivers, which are vital to enhancing the livelihood of a sizable population. This paper includes present scenario of solar energy in India along with other leading countries predicting the futuristic possibilities to utilize solar energy in wide. Discussions include the layout of solar cells, connections, power delivery, potential environmental effects, and coastal power management. The configuration of FPV's along with its positive and negative sides are briefly explained here.
{"title":"Emergence of Floating Solar Module Energy Generating Technology","authors":"K. Dixit, Arti Badhoutiya","doi":"10.1109/ICECA55336.2022.10009396","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009396","url":null,"abstract":"Floating photovoltaic (FPV) systems are a new technology that can be used to generate electricity on water bodies. It is crucial to assess the current state and future expectations for technological advancements for solar power generation with value-added solutions, particularly since floating photovoltaic systems have facilities that float on the surface.India, which has a high consumption for energy and a dearth of urban waste land for solar photovoltaic plants, can capture solar energy through the use of floating PV plant technology. To achieve sustainable objectives the establishment of floating solar plants, or solar arrays above floating structures on water bodies, is regularly encouraged by the government.India is among the blessed countries that have around 400 rivers, which are vital to enhancing the livelihood of a sizable population. This paper includes present scenario of solar energy in India along with other leading countries predicting the futuristic possibilities to utilize solar energy in wide. Discussions include the layout of solar cells, connections, power delivery, potential environmental effects, and coastal power management. The configuration of FPV's along with its positive and negative sides are briefly explained here.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130363243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009182
K. Nandhini, G. Thailambal
Drug Target Interaction (DTI) prediction is an important factor is drug discovery and repositioning (DDR) since it detects the response of a drug over a target protein. The Coronavirus disease 2019 (COVID-19) disease created groups of deadly pneumonia with clinical appearance mostly similar to SARS-CoV. The precise diagnosis of COVID-19 clinical outcome is more challenging, since the diseases has various forms with varying structures. So predicting the interactions between various drugs with the SARS-CoV target protein is very crucial need in these days, which may leads to discovery of new drugs for the deadly disease. Recently, Deep learning (DL) techniques have been applied by the researches for DTI prediction. Since CNN is one of the major DL models which has the ability to create predictive feature vectors or embeddings, CNN-OSBO encoder-decoder architecture for DTI prediction of Covid-19 targets has been designed Given the input drug and Covid-19 target pair of data, they are fed into the Convolution Neural Networks (CNN) with Opposition based Satin Bowerbird Optimizer (OSBO) encoder modules, separately. Here OSBO is utilized for regulating the hyper parameters (HPs) of CNN layers. Both the encoded data are then embedded to create a binding module. Finally the CNN Decoder module predicts the interaction of drugs over the Covid-19 targets by returning an affinity or interaction score. Experimental results state that DTI prediction using CNN+OSBO achieves better accuracy results when compared with the existing techniques.
{"title":"CNN-OSBO Encoder-Decoder Architecture for Drug-Target Interaction (DTI) Prediction of Covid-19 Targets","authors":"K. Nandhini, G. Thailambal","doi":"10.1109/ICECA55336.2022.10009182","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009182","url":null,"abstract":"Drug Target Interaction (DTI) prediction is an important factor is drug discovery and repositioning (DDR) since it detects the response of a drug over a target protein. The Coronavirus disease 2019 (COVID-19) disease created groups of deadly pneumonia with clinical appearance mostly similar to SARS-CoV. The precise diagnosis of COVID-19 clinical outcome is more challenging, since the diseases has various forms with varying structures. So predicting the interactions between various drugs with the SARS-CoV target protein is very crucial need in these days, which may leads to discovery of new drugs for the deadly disease. Recently, Deep learning (DL) techniques have been applied by the researches for DTI prediction. Since CNN is one of the major DL models which has the ability to create predictive feature vectors or embeddings, CNN-OSBO encoder-decoder architecture for DTI prediction of Covid-19 targets has been designed Given the input drug and Covid-19 target pair of data, they are fed into the Convolution Neural Networks (CNN) with Opposition based Satin Bowerbird Optimizer (OSBO) encoder modules, separately. Here OSBO is utilized for regulating the hyper parameters (HPs) of CNN layers. Both the encoded data are then embedded to create a binding module. Finally the CNN Decoder module predicts the interaction of drugs over the Covid-19 targets by returning an affinity or interaction score. Experimental results state that DTI prediction using CNN+OSBO achieves better accuracy results when compared with the existing techniques.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115209285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009541
R. Vijaya Saraswathi, Ravi Varma Chunchu, Sushma Kunchala, Mahankali Varun, Tejashwini Begari, Saidivya Bodduru
As different users provide different reviews for a product/service, it has become increasingly difficult for common people to understand the customer reviews found on various apps or websites. People are sometimes too lazy to read reviews on various subjects all the way through before making a judgement, despite the fact that they can take time. Even if they wanted to, people cannot read every line of a review. As a result, a text summary model would greatly simplify this process. The purpose of a text summary is to draw out the most significant data from a long document and leave out any that are superfluous or uninteresting. This text summarizer will automatically produce a useful summary from reviews using LSTM. Sentences from the input text will be separated and converted into vectors. A material summary is a process of reducing a large body of text while preserving its original context. The summary should read easily. In this project, our goal is to create a model that accepts reviews of foods as input and outputs a summary of the review. This helps the people who are ordering the food if they want to know about the food that they are looking for.
{"title":"A LSTM based Deep Learning Model for Text Summarization","authors":"R. Vijaya Saraswathi, Ravi Varma Chunchu, Sushma Kunchala, Mahankali Varun, Tejashwini Begari, Saidivya Bodduru","doi":"10.1109/ICECA55336.2022.10009541","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009541","url":null,"abstract":"As different users provide different reviews for a product/service, it has become increasingly difficult for common people to understand the customer reviews found on various apps or websites. People are sometimes too lazy to read reviews on various subjects all the way through before making a judgement, despite the fact that they can take time. Even if they wanted to, people cannot read every line of a review. As a result, a text summary model would greatly simplify this process. The purpose of a text summary is to draw out the most significant data from a long document and leave out any that are superfluous or uninteresting. This text summarizer will automatically produce a useful summary from reviews using LSTM. Sentences from the input text will be separated and converted into vectors. A material summary is a process of reducing a large body of text while preserving its original context. The summary should read easily. In this project, our goal is to create a model that accepts reviews of foods as input and outputs a summary of the review. This helps the people who are ordering the food if they want to know about the food that they are looking for.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115551527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009628
P. S. Kumar, S. Sudha, P. Das, D. Pradeep, S. J, K. Vijaipriya
Fruits are an excellent source of nutrients and minerals. They have a high concentration of antioxidants and flavonoids, which are beneficial to one's health. Pomegranates have a high potential in preventing cell damage, boosting our immunity, helping with smooth digestion, fighting type-2 diabetes, keeping vital parameters in check and are seen to be effective inthe prevention of cancers. India is considered the largest producer of excellent varieties of pomegranates and thus the quality analysis in the export operation of pomegranates is highly concerned. Grading of pomegranates is very necessary for post-harvest management and is performed based on the external appearance like attractive colours, texture, size and shape which decides the standard of the fruit. Manual grading can be done which requires human operation and consumes more time. Hence quality assessment of pomegranates can be done using Machine Learning(ML) which is highly efficient. The process of feature extraction yields accurate results and can be done quickly. ML technology improves accuracy and efficiency and has improved user experience. The review paper proposes an efficient ML approach for pomegranate quality analysis using Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP) feature extraction methods. K-Nearest Neighbour (KNN) and Naive Bayes (NB) algorithms are implemented in the designed model using both sets of feature extractors and the result illustrates that the LBP + NB model performs with better efficiency and greater accuracy.
{"title":"Pomegranate Quality Analysis and Classification Using Feature Extraction and Machine Learning","authors":"P. S. Kumar, S. Sudha, P. Das, D. Pradeep, S. J, K. Vijaipriya","doi":"10.1109/ICECA55336.2022.10009628","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009628","url":null,"abstract":"Fruits are an excellent source of nutrients and minerals. They have a high concentration of antioxidants and flavonoids, which are beneficial to one's health. Pomegranates have a high potential in preventing cell damage, boosting our immunity, helping with smooth digestion, fighting type-2 diabetes, keeping vital parameters in check and are seen to be effective inthe prevention of cancers. India is considered the largest producer of excellent varieties of pomegranates and thus the quality analysis in the export operation of pomegranates is highly concerned. Grading of pomegranates is very necessary for post-harvest management and is performed based on the external appearance like attractive colours, texture, size and shape which decides the standard of the fruit. Manual grading can be done which requires human operation and consumes more time. Hence quality assessment of pomegranates can be done using Machine Learning(ML) which is highly efficient. The process of feature extraction yields accurate results and can be done quickly. ML technology improves accuracy and efficiency and has improved user experience. The review paper proposes an efficient ML approach for pomegranate quality analysis using Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP) feature extraction methods. K-Nearest Neighbour (KNN) and Naive Bayes (NB) algorithms are implemented in the designed model using both sets of feature extractors and the result illustrates that the LBP + NB model performs with better efficiency and greater accuracy.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114785620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009511
Jeethu Philip, Venkata Nagaraju Thatha, M. Harshini, I. Haritha, Shruti Patil, B. Veerasekhar Reddy
Recently COVID-19 has become the most discussed topic in different social media platforms like Twitter, Facebook, Instagram etc. As time moves on, lot of messages and videos are posted in social media. As expected, most of the public followed these messages and becomes panic because of lack of information, misinformation about COVID-19 and its impact. This research study proposes a Twitter sentiment analysisbased on the most popular vaccines Covaxin, Covishield, and Pfizer. Most of the people expressed their feelings about vaccines in the twitter. Twitter API authentication is used here to extract the tweets. These extracted tweets are difficult to analyze, hence pre-processing has been done i.e., unstructured data is converted into structured format. After completion of preprocessing, the data is further classified by using Naïve Bayes algorithm. This algorithm performs data classification and divides it into three major classes as positive, negative, and neutral. The result shows that the covaxin yields 48.36% positive, 35.6% negative, and 16.04% neutral, Covishield yields 44.25% positive, 39.67% negative, and 16.08% neutral, Pfizer yields 42.95% positive, 39.45% negative, and 17.6% neutral sentiment.
{"title":"Classification of Covid-19 Vaccines tweets using Naïve Bayes Classification","authors":"Jeethu Philip, Venkata Nagaraju Thatha, M. Harshini, I. Haritha, Shruti Patil, B. Veerasekhar Reddy","doi":"10.1109/ICECA55336.2022.10009511","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009511","url":null,"abstract":"Recently COVID-19 has become the most discussed topic in different social media platforms like Twitter, Facebook, Instagram etc. As time moves on, lot of messages and videos are posted in social media. As expected, most of the public followed these messages and becomes panic because of lack of information, misinformation about COVID-19 and its impact. This research study proposes a Twitter sentiment analysisbased on the most popular vaccines Covaxin, Covishield, and Pfizer. Most of the people expressed their feelings about vaccines in the twitter. Twitter API authentication is used here to extract the tweets. These extracted tweets are difficult to analyze, hence pre-processing has been done i.e., unstructured data is converted into structured format. After completion of preprocessing, the data is further classified by using Naïve Bayes algorithm. This algorithm performs data classification and divides it into three major classes as positive, negative, and neutral. The result shows that the covaxin yields 48.36% positive, 35.6% negative, and 16.04% neutral, Covishield yields 44.25% positive, 39.67% negative, and 16.08% neutral, Pfizer yields 42.95% positive, 39.45% negative, and 17.6% neutral sentiment.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115788526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009347
M. Devi, V. Jyothi, D. Nagajyothi
Automatic pet feeder system is designed which is used to take care of pets such as cat and dog. The pet feeder system can deliver food, water and monitor the motion of the pet. This machine is equipped with a different embedded components which is helpful to feed food and dispense water without any human intervention. Unfortunately, due to their hectic schedules and limited time at work, they have neglected their pets and have left them hungry. This project mainly designed for people for saving their time and energy by feeding their pets on time and monitoring through the designated application. The monitoring has been done because of internet connection has been provided through the gadget so that the user can observe the pet's feeding on the corresponding Thing speak cloud. The Arduino UNO and the server motor are among the machine's novel components, which are employed in a bottle that may endure for a week with electrical connections. The purpose of this is to feed food for pets automatically based on amount of food available and also on time. Consequently, most of this pet feeders on the market are operated manually, and these feeders not even use IoT methods. Users may use this Pet Feeder automatically, eliminating the need to worry about their dogs. Those who love pets will be loving to select this type of machine for their pets at home. By using this type of machine consumer will also be less concerned about leaving their pets for small period, such as when returning to their hometown or working full-time. Finally, especially in the mechanical business, it is an excellent technique to increase and employ top and local users. This is quite helpful for the people who has pet, and it uses latest technology where it encourages Internet of things along with Embedded system as it can be applicable for local industrial petting upgrading.
{"title":"IoT and Cloud-based Automated Pet Care System","authors":"M. Devi, V. Jyothi, D. Nagajyothi","doi":"10.1109/ICECA55336.2022.10009347","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009347","url":null,"abstract":"Automatic pet feeder system is designed which is used to take care of pets such as cat and dog. The pet feeder system can deliver food, water and monitor the motion of the pet. This machine is equipped with a different embedded components which is helpful to feed food and dispense water without any human intervention. Unfortunately, due to their hectic schedules and limited time at work, they have neglected their pets and have left them hungry. This project mainly designed for people for saving their time and energy by feeding their pets on time and monitoring through the designated application. The monitoring has been done because of internet connection has been provided through the gadget so that the user can observe the pet's feeding on the corresponding Thing speak cloud. The Arduino UNO and the server motor are among the machine's novel components, which are employed in a bottle that may endure for a week with electrical connections. The purpose of this is to feed food for pets automatically based on amount of food available and also on time. Consequently, most of this pet feeders on the market are operated manually, and these feeders not even use IoT methods. Users may use this Pet Feeder automatically, eliminating the need to worry about their dogs. Those who love pets will be loving to select this type of machine for their pets at home. By using this type of machine consumer will also be less concerned about leaving their pets for small period, such as when returning to their hometown or working full-time. Finally, especially in the mechanical business, it is an excellent technique to increase and employ top and local users. This is quite helpful for the people who has pet, and it uses latest technology where it encourages Internet of things along with Embedded system as it can be applicable for local industrial petting upgrading.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115799093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009202
B. V., Gowsika N, A. P., P. P, S. Raja
Coronavirus (COVID-19) is an infectious illness due to serious respiratory trouble. It is impacted numerous humans and has asserted the living expectancy of a greater number of persons from all over the planet. The maturation period of this virus, on typically about 5–6 days but it might also be up to 2 weeks. Throughout this period, the individual may not feel any indications but could still be transmissible. A person could develop this disease if he/ she inhales the virus while a diseased person/ virus carrier within close vicinity sneezes or coughs otherwise tapping an infected place in addition to afterward again his/ her eyes, nose or mouth. To prevent this, the region of the COVID-19 patient must be decontaminated with virucidal disinfectants, such as and 0.05% sodium hypochlorite (NaClO) and ethanol-based products (at least 70%) an optional technique used is UV light sterilization. Ultraviolet (UV) sterilization technology is used to help reduce micro-organisms that can remain on surfaces after basic sprinkling to the minimum amount. The proposed work has established an UV robot or UV bot to perform decontamination in an operating room or in-patients room. Three 19.3-watt UV lights are positioned in a 360-degree circle on the UV bot platform. It used an integrated system based on a microprocessor and a metal frame to aid in navigation in a fixed path to avoid barriers. In addition, a sanitizer dispenser is also included to clean the viral organisms, which is spread through the water droplets of the patient.
{"title":"An Automated Patient Bed Cleaner Using UV Rays","authors":"B. V., Gowsika N, A. P., P. P, S. Raja","doi":"10.1109/ICECA55336.2022.10009202","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009202","url":null,"abstract":"Coronavirus (COVID-19) is an infectious illness due to serious respiratory trouble. It is impacted numerous humans and has asserted the living expectancy of a greater number of persons from all over the planet. The maturation period of this virus, on typically about 5–6 days but it might also be up to 2 weeks. Throughout this period, the individual may not feel any indications but could still be transmissible. A person could develop this disease if he/ she inhales the virus while a diseased person/ virus carrier within close vicinity sneezes or coughs otherwise tapping an infected place in addition to afterward again his/ her eyes, nose or mouth. To prevent this, the region of the COVID-19 patient must be decontaminated with virucidal disinfectants, such as and 0.05% sodium hypochlorite (NaClO) and ethanol-based products (at least 70%) an optional technique used is UV light sterilization. Ultraviolet (UV) sterilization technology is used to help reduce micro-organisms that can remain on surfaces after basic sprinkling to the minimum amount. The proposed work has established an UV robot or UV bot to perform decontamination in an operating room or in-patients room. Three 19.3-watt UV lights are positioned in a 360-degree circle on the UV bot platform. It used an integrated system based on a microprocessor and a metal frame to aid in navigation in a fixed path to avoid barriers. In addition, a sanitizer dispenser is also included to clean the viral organisms, which is spread through the water droplets of the patient.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115128118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009361
K. Varshini, Nakka Swathi, Maram Sadhvik Reddy, J. Priyanka
Agriculture plays a vital role in the economics and provides food and fabrics. Usage of pesticides should be reduced as it is harmful to humankind as well as environment. Most the farmers are using pesticides to kill the insects. This paper describes different ways to reduce pesticides to kill the insects. Light traps could solve this problem by attracting the insects that are not killed even when the pesticides are used. This paper also explains how to minimize pesticides as well as flying insects. Most of the flying insects may escape while s praying the liquid type pesticides, whereas these insects will be attracted towards ultra violet lights during the knights and there by this research work is initiated to attract cretin type of flying insects. Solar energy is used to energize the light automatically during the dark and the same light will be de-energized automatically in early morning. The embedded system designed with 89c2051 microcontroller is programmed to read the solar panel voltage continuously and depending up on these voltage levels light will be controlled automatically to attract more types of insects, here the light is designed with two different LED's, UV LED's and white high-glow LEDs are used and these lights will be energized one bunch after another bunch with a time delay of 5 minutes each. This study also measures the parameters like moisture and temperature by using FSP8266 module. A Wi-Fi controller application is used in the mobile to read different parameter values and these values are also dis played by using the LCD attached to the kit. This model is ecofriendly and more useful to farmer. Solar insect trap is one of the techniques used to trap the insects but the technique provided is not of higher maintenance, battery backup and ESP8266 Wi-Fi module is not included and different parameters like moisture, temperature is not detected in the existing technique.
{"title":"Microcontroller based Smart Agriculture System","authors":"K. Varshini, Nakka Swathi, Maram Sadhvik Reddy, J. Priyanka","doi":"10.1109/ICECA55336.2022.10009361","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009361","url":null,"abstract":"Agriculture plays a vital role in the economics and provides food and fabrics. Usage of pesticides should be reduced as it is harmful to humankind as well as environment. Most the farmers are using pesticides to kill the insects. This paper describes different ways to reduce pesticides to kill the insects. Light traps could solve this problem by attracting the insects that are not killed even when the pesticides are used. This paper also explains how to minimize pesticides as well as flying insects. Most of the flying insects may escape while s praying the liquid type pesticides, whereas these insects will be attracted towards ultra violet lights during the knights and there by this research work is initiated to attract cretin type of flying insects. Solar energy is used to energize the light automatically during the dark and the same light will be de-energized automatically in early morning. The embedded system designed with 89c2051 microcontroller is programmed to read the solar panel voltage continuously and depending up on these voltage levels light will be controlled automatically to attract more types of insects, here the light is designed with two different LED's, UV LED's and white high-glow LEDs are used and these lights will be energized one bunch after another bunch with a time delay of 5 minutes each. This study also measures the parameters like moisture and temperature by using FSP8266 module. A Wi-Fi controller application is used in the mobile to read different parameter values and these values are also dis played by using the LCD attached to the kit. This model is ecofriendly and more useful to farmer. Solar insect trap is one of the techniques used to trap the insects but the technique provided is not of higher maintenance, battery backup and ESP8266 Wi-Fi module is not included and different parameters like moisture, temperature is not detected in the existing technique.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115532130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009599
G. B, S. B. V., Vishveshvaran R
India's economy is heavily reliant on agriculture, which is also a significant source of crop production. The livelihood of a sizable portion of India's population depends on yield production. Agriculture-related problems are a current primary concern in the modern era. The primary challenge for agricultural growth is the need to maintain the wellbeing of the plants and the crops. One industry that significantly affects people's lives and the state of the economy is agriculture. Poor management leads to the loss of agricultural products. The most delicate plant leaves are the first to show symptoms of sickness. The use of equipment to anticipate disease has proven to be quicker, less expensive, and more reliable than farmers' traditional method of manual observation. Most often, disease symptoms are visible on the leaves, stems, and fruits. The crop's productivity is impacted by a number of factors. Climate change, insect infestations, and numerous plant diseases are some of the contributing reasons. An automatic detection system is intended to pick up illness signs as they emerge or progress. In the paper, a method for using deep learning and image processing to detect illnesses in leaves is revealed.
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Pub Date : 2022-12-01DOI: 10.1109/ICECA55336.2022.10009497
M. Patil, M. Chawhan
Clustering in MANET provides greater efficiency in terms of energy and mobility of the node. It has better stability and scalability of the nodes in the network, as energy and mobility of node is the key parameter for the nodes in the network. Cluster Head (CH) selection and Cluster maintenance are the two perspectives for clustering in MANET. CH is the vital node in the network to collect the data from the member nodes. CH requires more energy when compared to other nodes in the cluster. It calculates the distance of the nodes and energy of the node in the cluster by the ration of energy and distance based on sector design. If energy of the cluster head is less than threshold value, the reclustering occurs and again a CH is elected. There are different geometries of the clustering, and Fan shaped clustering approach is proposed in this paper. This clustering scheme result is expected in terms of Quality of Service (QOS) parameters. QOS parameters have been evaluated with fan shaped clustering and without fan shaped clustering. QOS parameters such as throughput, packet delivery ratio, path loss etc. are validated on the NS2 Simulation Platform. It extends the network life in terms of energy throughput, delay and Packet Delivery Ratio.
{"title":"Improvement of QoS Parameters using FAN Shaped Clustering Method","authors":"M. Patil, M. Chawhan","doi":"10.1109/ICECA55336.2022.10009497","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009497","url":null,"abstract":"Clustering in MANET provides greater efficiency in terms of energy and mobility of the node. It has better stability and scalability of the nodes in the network, as energy and mobility of node is the key parameter for the nodes in the network. Cluster Head (CH) selection and Cluster maintenance are the two perspectives for clustering in MANET. CH is the vital node in the network to collect the data from the member nodes. CH requires more energy when compared to other nodes in the cluster. It calculates the distance of the nodes and energy of the node in the cluster by the ration of energy and distance based on sector design. If energy of the cluster head is less than threshold value, the reclustering occurs and again a CH is elected. There are different geometries of the clustering, and Fan shaped clustering approach is proposed in this paper. This clustering scheme result is expected in terms of Quality of Service (QOS) parameters. QOS parameters have been evaluated with fan shaped clustering and without fan shaped clustering. QOS parameters such as throughput, packet delivery ratio, path loss etc. are validated on the NS2 Simulation Platform. It extends the network life in terms of energy throughput, delay and Packet Delivery Ratio.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124872748","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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