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/ICECA55336.2022.10009182
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/ICECA55336.2022.10009181
Rajeshree Parsingbhai Vasava, Hetal A. Joshiara
“lung diseases are now considered as one of the fatal diseases across the globe. However, early detection of lung disease may help in providing earlier treatment since most cases of lung diseases are only detected after they have progressed to advanced stage. Today's healthcare system relies on the recent technological advancements. Lung sound analysis plays a crucial role in the diagnosis of lung disease. Further, the successful navigation of medical system requires the ability to acquire new information and utilize it in new contexts. To perform classification, this research work presents several transfer learning strategies, including ALEXNET, VGGNET, and RES NET for analyzing the lung sounds. To complement the techniques, a Transfer learning model that incorporates a Modified RESNET with a Mel spectrogram of lung sound signals are used to perform classification. These transfer learning models perform efficiently in classifying the lung sounds, which can be later used to diagnose respiratory diseases. This research study analyzes several transfer learning methods and discuss their benefits and drawbacks in identifying four distinct types of lung sounds. Finally, the further research directions on the identification of lung sounds are discussed.”
{"title":"Lung Sounds Identification based On Transfer Learning Approaches : A Review","authors":"Rajeshree Parsingbhai Vasava, Hetal A. Joshiara","doi":"10.1109/ICECA55336.2022.10009181","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009181","url":null,"abstract":"“lung diseases are now considered as one of the fatal diseases across the globe. However, early detection of lung disease may help in providing earlier treatment since most cases of lung diseases are only detected after they have progressed to advanced stage. Today's healthcare system relies on the recent technological advancements. Lung sound analysis plays a crucial role in the diagnosis of lung disease. Further, the successful navigation of medical system requires the ability to acquire new information and utilize it in new contexts. To perform classification, this research work presents several transfer learning strategies, including ALEXNET, VGGNET, and RES NET for analyzing the lung sounds. To complement the techniques, a Transfer learning model that incorporates a Modified RESNET with a Mel spectrogram of lung sound signals are used to perform classification. These transfer learning models perform efficiently in classifying the lung sounds, which can be later used to diagnose respiratory diseases. This research study analyzes several transfer learning methods and discuss their benefits and drawbacks in identifying four distinct types of lung sounds. Finally, the further research directions on the identification of lung sounds are discussed.”","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"23 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":"128909535","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/ICECA55336.2022.10009562
K. M. Kumar, M. Rashmi
Electric vehicles are the best way to avoid the pollution in the environment. Various types of motors are available for this application and the selection of motor is customized based on the speed-torque requirement of the vehicle. Permanent Magnet Synchronous Motors (PMSM) are more suitable for electric vehicles due to fast dynamic response, higher efficiency and ease of control at both low speed and high speeds. These motors are prone to mechanical and electrical faults. Open circuit fault and inter-turn short circuits are the electrical faults. 30 to 40% of the electrical faults are due to short circuiting of windings. Inter-turn short circuit fault is dangerous and prolonged faults leads lead to line to ground fault. To ensure the reliability and safety of the electric vehicles, these faults have to be taken care. Early estimation of winding faults is very essential. This paper focuses on modeling and analysis of PMSM motor during normal operation and inter-turn short circuit fault. A novel and simple model during inter-turn short circuit fault is proposed. The simulation results for various fault percentages in A-phase windings are presented in this paper.
{"title":"Modeling and Analysis of Interturn Short Circuit Fault in PMSM Motor for Electric Vehicle Applications","authors":"K. M. Kumar, M. Rashmi","doi":"10.1109/ICECA55336.2022.10009562","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009562","url":null,"abstract":"Electric vehicles are the best way to avoid the pollution in the environment. Various types of motors are available for this application and the selection of motor is customized based on the speed-torque requirement of the vehicle. Permanent Magnet Synchronous Motors (PMSM) are more suitable for electric vehicles due to fast dynamic response, higher efficiency and ease of control at both low speed and high speeds. These motors are prone to mechanical and electrical faults. Open circuit fault and inter-turn short circuits are the electrical faults. 30 to 40% of the electrical faults are due to short circuiting of windings. Inter-turn short circuit fault is dangerous and prolonged faults leads lead to line to ground fault. To ensure the reliability and safety of the electric vehicles, these faults have to be taken care. Early estimation of winding faults is very essential. This paper focuses on modeling and analysis of PMSM motor during normal operation and inter-turn short circuit fault. A novel and simple model during inter-turn short circuit fault is proposed. The simulation results for various fault percentages in A-phase windings are presented in this paper.","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":"130825870","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/ICECA55336.2022.10009575
Anuj Kumar Goel
Due to the growing demand and wide application of microdevices, there is an increase in the demand of microgrippers that can perfectly carry and place the microparts in MEMS Devices. In this paper, grippers are designed in micro dimensions for micro and nano devices. The piezoelectric actuation is used for analyses of designed precise microgrippers. Different piezoelectric materials such as PZT5A, PZT7, Barium Titanate, Barium Sodium Niobate, and Lithium Niobate are modelled and analysed in terms of displacement of arms with stress observation at the actuator ends. PZT5A proves the best material for microgripping effect. COMSOL Multiphysics is the FEA tool used for the design and analysis of microdevices.
{"title":"Comparative Analysis of Different Piezoelectric materials in Design of Microgrippers","authors":"Anuj Kumar Goel","doi":"10.1109/ICECA55336.2022.10009575","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009575","url":null,"abstract":"Due to the growing demand and wide application of microdevices, there is an increase in the demand of microgrippers that can perfectly carry and place the microparts in MEMS Devices. In this paper, grippers are designed in micro dimensions for micro and nano devices. The piezoelectric actuation is used for analyses of designed precise microgrippers. Different piezoelectric materials such as PZT5A, PZT7, Barium Titanate, Barium Sodium Niobate, and Lithium Niobate are modelled and analysed in terms of displacement of arms with stress observation at the actuator ends. PZT5A proves the best material for microgripping effect. COMSOL Multiphysics is the FEA tool used for the design and analysis of microdevices.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"1 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":"130080880","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/ICECA55336.2022.10009502
Mohd Javeed Mehdi, Suram Purna Sai Chandra, M. Sravya, Gooty Hamsitha, Veggilapu Sai Krishna
Accidents are more common in mountainous areas, and as a result, more people lose their lives. The roads in this are a are curved and steep, making it difficult for drivers to see vehicles on the other side. Most accidents occur in hill stations, according to the report (i.e., 13% of all accidents). Because of this, we came up with the concept of utilizing embedded systems technology to solve the problem at hand. A model for reducing the number of accidents in hill stations is proposed in this research. Hair bend pin curves, valley points, and vehicle skidding are the three most common accident sites in the mountains. Our proposed system is created utilizing an Arduino Uno board with IR sensors and Ultrasonic (UR) sensors, and we are proposing to fix it at these dangerous spots. On either side of the road's hairpin bend, IR sensors detect vehicle movement and relay that information to a traffic module on the other side. The valley point has a UR sensor, which detects vehicles approaching the valley point and sounds an alert with buzzers. The primary goal of the proposed model is to reduce the death rate in mountainous stations by preventing accidents.
{"title":"Pre-Crash Sensing and Warning System in Hill Station","authors":"Mohd Javeed Mehdi, Suram Purna Sai Chandra, M. Sravya, Gooty Hamsitha, Veggilapu Sai Krishna","doi":"10.1109/ICECA55336.2022.10009502","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009502","url":null,"abstract":"Accidents are more common in mountainous areas, and as a result, more people lose their lives. The roads in this are a are curved and steep, making it difficult for drivers to see vehicles on the other side. Most accidents occur in hill stations, according to the report (i.e., 13% of all accidents). Because of this, we came up with the concept of utilizing embedded systems technology to solve the problem at hand. A model for reducing the number of accidents in hill stations is proposed in this research. Hair bend pin curves, valley points, and vehicle skidding are the three most common accident sites in the mountains. Our proposed system is created utilizing an Arduino Uno board with IR sensors and Ultrasonic (UR) sensors, and we are proposing to fix it at these dangerous spots. On either side of the road's hairpin bend, IR sensors detect vehicle movement and relay that information to a traffic module on the other side. The valley point has a UR sensor, which detects vehicles approaching the valley point and sounds an alert with buzzers. The primary goal of the proposed model is to reduce the death rate in mountainous stations by preventing accidents.","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":"129960683","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/ICECA55336.2022.10009602
A. Elakkiya, K. Surya, Konduru Venkatesh, S. Aakash
Deep learning is revolutionary when used to transcribe spoken language into text that computers can read with the same intent as human readers. The fundamental idea is to give intelligent systems with human language as data that may be utilized in various domains. A speech-to-text synthesizer is a piece of software that can convert an audio file into text using Digital Signal Processing (DSP) algorithms that analyze and process the speech signal in the audio file. The objective of Speech To Text (STT) is to convert audio input from a user or computer into readable text. The STT is proposed to be transformed using the Hidden Markov Model (HMM) method. The development of a speech-to-text synthesizer will be a tremendous advantage for the visually handicapped and will make reading lengthy texts much easier.
{"title":"Implementation of Speech to Text Conversion Using Hidden Markov Model","authors":"A. Elakkiya, K. Surya, Konduru Venkatesh, S. Aakash","doi":"10.1109/ICECA55336.2022.10009602","DOIUrl":"https://doi.org/10.1109/ICECA55336.2022.10009602","url":null,"abstract":"Deep learning is revolutionary when used to transcribe spoken language into text that computers can read with the same intent as human readers. The fundamental idea is to give intelligent systems with human language as data that may be utilized in various domains. A speech-to-text synthesizer is a piece of software that can convert an audio file into text using Digital Signal Processing (DSP) algorithms that analyze and process the speech signal in the audio file. The objective of Speech To Text (STT) is to convert audio input from a user or computer into readable text. The STT is proposed to be transformed using the Hidden Markov Model (HMM) method. The development of a speech-to-text synthesizer will be a tremendous advantage for the visually handicapped and will make reading lengthy texts much easier.","PeriodicalId":356949,"journal":{"name":"2022 6th International Conference on Electronics, Communication and Aerospace Technology","volume":"25 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":"128152899","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/ICECA55336.2022.10009497
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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