S. Abiraj, D. Eeswar Samhithan, B. Sanjai Kumar, Y. Venkatesh
The needs of search and rescue teams in numerous ways reflect the requirements of the military. They both work in perilous situations, they need to discover ways to gather data while keeping personnel out of hurt, and they are both seeking out for individuals. So, this Robot Commands in manual mode using a Smartphone, Wireless cam for Real-time Broadcast, PIR and Metal detection sensors, GPS & GSM modules, ultrasonic sensor, Gas & Fire sensor, temperature and humidity sensor, Acid gun, RFID and Relay switch, In this wireless sensor networks (WSN) is an Encrypted Network and infrastructure-less wireless networks to Screening physical or natural conditions, such as vibrations, pressures,movement, or toxins and to agreeably transmit their information retrieved by using IOT Server.
{"title":"A Robot for Combat and Calamities with Encrypted WSN","authors":"S. Abiraj, D. Eeswar Samhithan, B. Sanjai Kumar, Y. Venkatesh","doi":"10.3233/apc210293","DOIUrl":"https://doi.org/10.3233/apc210293","url":null,"abstract":"The needs of search and rescue teams in numerous ways reflect the requirements of the military. They both work in perilous situations, they need to discover ways to gather data while keeping personnel out of hurt, and they are both seeking out for individuals. So, this Robot Commands in manual mode using a Smartphone, Wireless cam for Real-time Broadcast, PIR and Metal detection sensors, GPS & GSM modules, ultrasonic sensor, Gas & Fire sensor, temperature and humidity sensor, Acid gun, RFID and Relay switch, In this wireless sensor networks (WSN) is an Encrypted Network and infrastructure-less wireless networks to Screening physical or natural conditions, such as vibrations, pressures,movement, or toxins and to agreeably transmit their information retrieved by using IOT Server.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131889431","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. Duraichi, K. Arun Kumar, N. Lokesh Sathya, S. Lokesh
Vehicle robbery and unknown car thefts has become a intense issue around the nation. Many culprits use unapproved vehicles to perform numerous illegal activities and leave the vehicles. The utmost reason for accidents is due to the vehicles driven by unknown users, who perform reckless and inexperienced driving without the speed limit will cause many accidents that increases the death rate. Our goal is to make a system which will allow the person who have authorized license. For this purpose, we plan to install an automated system in the vehicle to introduce smart license verification technology. Various techniques and technologies are being explained to detect the details of the driver, and also Various vehicle thefts are being done in spite of various surveillance cameras are set down to keep an eye on the activities and various technologies are being implemented to diminish the vehicle robbery. So, we proposed the system with the concept of deep learning. As compared to normal detection techniques deep learning collects N number of input samples and compares it with the database details. After the authentication process the engine mechanism starts, if not authorized it gives a buzzer sound and vehicle doesn’t start until the details of registered person is authenticated.
{"title":"Automobile Authentication and Tracking System","authors":"N. Duraichi, K. Arun Kumar, N. Lokesh Sathya, S. Lokesh","doi":"10.3233/apc210271","DOIUrl":"https://doi.org/10.3233/apc210271","url":null,"abstract":"Vehicle robbery and unknown car thefts has become a intense issue around the nation. Many culprits use unapproved vehicles to perform numerous illegal activities and leave the vehicles. The utmost reason for accidents is due to the vehicles driven by unknown users, who perform reckless and inexperienced driving without the speed limit will cause many accidents that increases the death rate. Our goal is to make a system which will allow the person who have authorized license. For this purpose, we plan to install an automated system in the vehicle to introduce smart license verification technology. Various techniques and technologies are being explained to detect the details of the driver, and also Various vehicle thefts are being done in spite of various surveillance cameras are set down to keep an eye on the activities and various technologies are being implemented to diminish the vehicle robbery. So, we proposed the system with the concept of deep learning. As compared to normal detection techniques deep learning collects N number of input samples and compares it with the database details. After the authentication process the engine mechanism starts, if not authorized it gives a buzzer sound and vehicle doesn’t start until the details of registered person is authenticated.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132074420","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 today’s growing cloud world, where users are continuously demanding a large number of services or resources at the same time, cloud providers aim to meet their needs while maintaining service quality, an ideal QoS-based resource provisioning is required. In the consideration of the quality-of-service parameters, it is essential to place a greater emphasis on the scalability attribute, which aids in the design of complex resource provisioning frameworks. This study aims to determine how much work is done in light of scalability as the most important QoS attribute. We first conducted a detailed survey on similar QoS-based resource provisioning proposed frameworks/techniques in this article, which discusses QoS parameters with increasingly growing cloud usage expectations. Second, this paper focuses on scalability as the main QOS characteristic, with types, issues, review questions and research gaps discussed in detail, revealing that less work has been performed thus far. We will try to address scalability and resource provisioning problems with our proposed advance scalable QoS-based resource provisioning framework by integrating new modules resource scheduler, load balancer, resource tracker, and cloud user budget tracker in the resource provisioning process. Cloud providers can easily achieve scalability of resources while performing resource provisioning by integrating the working specialty of these sub modules.
{"title":"Analysis and Design of Advance Scalable QoS Based Resource Provisioning Framework","authors":"P. Shelke, Rekha Shahapurkar","doi":"10.3233/apc210187","DOIUrl":"https://doi.org/10.3233/apc210187","url":null,"abstract":"In today’s growing cloud world, where users are continuously demanding a large number of services or resources at the same time, cloud providers aim to meet their needs while maintaining service quality, an ideal QoS-based resource provisioning is required. In the consideration of the quality-of-service parameters, it is essential to place a greater emphasis on the scalability attribute, which aids in the design of complex resource provisioning frameworks. This study aims to determine how much work is done in light of scalability as the most important QoS attribute. We first conducted a detailed survey on similar QoS-based resource provisioning proposed frameworks/techniques in this article, which discusses QoS parameters with increasingly growing cloud usage expectations. Second, this paper focuses on scalability as the main QOS characteristic, with types, issues, review questions and research gaps discussed in detail, revealing that less work has been performed thus far. We will try to address scalability and resource provisioning problems with our proposed advance scalable QoS-based resource provisioning framework by integrating new modules resource scheduler, load balancer, resource tracker, and cloud user budget tracker in the resource provisioning process. Cloud providers can easily achieve scalability of resources while performing resource provisioning by integrating the working specialty of these sub modules.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133343876","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 rising global population and economic growth, combined with rapid urbanization, will result in a significant increase in energy demand. To solve this problem in the coming years, the world will need significantly more resources, primarily cleanly produced electricity. On the other hand, electricity demand is rising at twice the rate of overall energy consumption, and is expected to more than double by 2040. So, in order to meet the energy demands, the proposed approach includes a concept of a new Vertical Axis Wind Turbine (VAWT) design that generates power from moving vehicles and further integrated with PV for increased power generation. Seasonal variations can be accommodated by the related hybrid scheme. Using a charge controller, the produced power can be stabilized to a 12V output. The generated energy can be stored in batteries or supplied to the grid, acting as an energy storage device for society. The power that has been stored can be used in the future or during non-windy seasons.
{"title":"Enhancement of Power Generation in Highway Using Wind Energy Conversion System Integrated with PV","authors":"Kiruba.K, Deepika.D, Jaitha.G, Madhuja.S","doi":"10.3233/apc210300","DOIUrl":"https://doi.org/10.3233/apc210300","url":null,"abstract":"The rising global population and economic growth, combined with rapid urbanization, will result in a significant increase in energy demand. To solve this problem in the coming years, the world will need significantly more resources, primarily cleanly produced electricity. On the other hand, electricity demand is rising at twice the rate of overall energy consumption, and is expected to more than double by 2040. So, in order to meet the energy demands, the proposed approach includes a concept of a new Vertical Axis Wind Turbine (VAWT) design that generates power from moving vehicles and further integrated with PV for increased power generation. Seasonal variations can be accommodated by the related hybrid scheme. Using a charge controller, the produced power can be stabilized to a 12V output. The generated energy can be stored in batteries or supplied to the grid, acting as an energy storage device for society. The power that has been stored can be used in the future or during non-windy seasons.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132863146","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}
Dr. Pallavi Katkar, Ashwini R Pawar, S. Zalte, Suhas Katkar
A sensor network can be defined an assembly of sensor nodes which associated by all together to complete particular detailed task. These sensor nodes are mostly in huge amounts also compactly installed moreover in the network area or very near to it. Sensor networks can be worked for several sectors such that: environmental monitoring, home, health care, Industries, military, and habitat. Failure of network is unavoidable in wireless sensor networks because of unfriendly location and non-reachable placement. Hence, it is needed that network faults are discovered in time and proper methods are engaged to bear network task. So, it is important to deliver fault forbearing systems for spread sensor applications. Numerous new work in this field yield severely different methodologies to talking the fault tolerance concern in routing. In this propose review and equate present fault tolerant practices to provision for sensor applications.
{"title":"Node Failure Management to Improve the Performance of Wireless Sensor Networks","authors":"Dr. Pallavi Katkar, Ashwini R Pawar, S. Zalte, Suhas Katkar","doi":"10.3233/apc210233","DOIUrl":"https://doi.org/10.3233/apc210233","url":null,"abstract":"A sensor network can be defined an assembly of sensor nodes which associated by all together to complete particular detailed task. These sensor nodes are mostly in huge amounts also compactly installed moreover in the network area or very near to it. Sensor networks can be worked for several sectors such that: environmental monitoring, home, health care, Industries, military, and habitat. Failure of network is unavoidable in wireless sensor networks because of unfriendly location and non-reachable placement. Hence, it is needed that network faults are discovered in time and proper methods are engaged to bear network task. So, it is important to deliver fault forbearing systems for spread sensor applications. Numerous new work in this field yield severely different methodologies to talking the fault tolerance concern in routing. In this propose review and equate present fault tolerant practices to provision for sensor applications.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115662827","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}
S. Deepa, Amala Nihila.A, Prabhavathi.J, Meenatchi.M, Varsha.M.J
This project describes a supermarket automation trolley based on an RFID reader. The trolley is equipped with an RFID reader and an electronic hardware system to make the transaction more convenient. The RFID card, whose price is set into the reader, is used to correct those items that are above a certain number. The value of the item is added to the sales bill and shown on the LCD monitor when the item is shown in front of the reader. The trolley car is programmed in such some way that it’ll move consistent with the user command. It additionally has the supply for removing the things from the trolley car wherever price is aloof from the overall cost. The user can view their bill through IOT along with the number of items purchased and total bill amount. The user can also pay the bill using his card provided and the system will give an alert if the total amount exceeds the amount in the card. The system will also suggest the user whether the purchased product is suitable for their health condition or not through IOT app provided to the user.
{"title":"Shopping Wagon: A Smart Shopping System Using RFID for Shopping Malls","authors":"S. Deepa, Amala Nihila.A, Prabhavathi.J, Meenatchi.M, Varsha.M.J","doi":"10.3233/apc210281","DOIUrl":"https://doi.org/10.3233/apc210281","url":null,"abstract":"This project describes a supermarket automation trolley based on an RFID reader. The trolley is equipped with an RFID reader and an electronic hardware system to make the transaction more convenient. The RFID card, whose price is set into the reader, is used to correct those items that are above a certain number. The value of the item is added to the sales bill and shown on the LCD monitor when the item is shown in front of the reader. The trolley car is programmed in such some way that it’ll move consistent with the user command. It additionally has the supply for removing the things from the trolley car wherever price is aloof from the overall cost. The user can view their bill through IOT along with the number of items purchased and total bill amount. The user can also pay the bill using his card provided and the system will give an alert if the total amount exceeds the amount in the card. The system will also suggest the user whether the purchased product is suitable for their health condition or not through IOT app provided to the user.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116207261","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}
V. Annapoorani, J. Banupriya, P. Navaraja, V. Chinnammal
Abstract of our paper’s major intent is to manage power and to share the solar load power to grid system by using smart grid technologies that is called as Demand Side Management (DSM). This paper gives the idea of modernized delivery system of electricity in which it observes, safeguards and adjusts accordingly with the energy that is used in home. The objective of the work is when the renewable resources are plentiful and electricity becomes affordable, time-of-use pricing, which allows customers to move some of their energy use to consistent and convenient moment of the day.
{"title":"A New Tariff Based Energy Saving and Sharing Scheme from Renewable Energy Using Smart Grid","authors":"V. Annapoorani, J. Banupriya, P. Navaraja, V. Chinnammal","doi":"10.3233/apc210270","DOIUrl":"https://doi.org/10.3233/apc210270","url":null,"abstract":"Abstract of our paper’s major intent is to manage power and to share the solar load power to grid system by using smart grid technologies that is called as Demand Side Management (DSM). This paper gives the idea of modernized delivery system of electricity in which it observes, safeguards and adjusts accordingly with the energy that is used in home. The objective of the work is when the renewable resources are plentiful and electricity becomes affordable, time-of-use pricing, which allows customers to move some of their energy use to consistent and convenient moment of the day.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125131711","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}
Emotion awareness is one of the most important subjects in the field of affective computing. Using nonverbal behavioral methods such as recognition of facial expression, verbal behavioral method, recognition of speech emotion, or physiological signals-based methods such as recognition of emotions based on electroencephalogram (EEG) can predict human emotion. However, it is notable that data obtained from either nonverbal or verbal behaviors are indirect emotional signals suggesting brain activity. Unlike the nonverbal or verbal actions, EEG signals are reported directly from the human brain cortex and thus may be more effective in representing the inner emotional states of the brain. Consequently, when used to measure human emotion, the use of EEG data can be more accurate than data on behavior. For this reason, the identification of human emotion from EEG signals has become a very important research subject in current emotional brain-computer interfaces (BCIs) aimed at inferring human emotional states based on the EEG signals recorded. In this paper, a hybrid deep learning approach has proposed using CNN and a long short-term memory (LSTM) algorithm is investigated for the purpose of automatic classification of epileptic disease from EEG signals. The signals have been processed by CNN for feature extraction from runtime environment while LSTM has used for classification of entire data. Finally, system demonstrates each EEG data file as normal or epileptic disease. In this research to describes a state of art for effective epileptic disease detection prediction and classification using hybrid deep learning algorithms. This research demonstrates a collaboration of CNN and LSTM for entire classification of EEG signals in numerous existing systems.
{"title":"A Review on BCI Emotions Classification for EEG Signals Using Deep Learning","authors":"Puja A. Chavan, S. Desai","doi":"10.3233/apc210241","DOIUrl":"https://doi.org/10.3233/apc210241","url":null,"abstract":"Emotion awareness is one of the most important subjects in the field of affective computing. Using nonverbal behavioral methods such as recognition of facial expression, verbal behavioral method, recognition of speech emotion, or physiological signals-based methods such as recognition of emotions based on electroencephalogram (EEG) can predict human emotion. However, it is notable that data obtained from either nonverbal or verbal behaviors are indirect emotional signals suggesting brain activity. Unlike the nonverbal or verbal actions, EEG signals are reported directly from the human brain cortex and thus may be more effective in representing the inner emotional states of the brain. Consequently, when used to measure human emotion, the use of EEG data can be more accurate than data on behavior. For this reason, the identification of human emotion from EEG signals has become a very important research subject in current emotional brain-computer interfaces (BCIs) aimed at inferring human emotional states based on the EEG signals recorded. In this paper, a hybrid deep learning approach has proposed using CNN and a long short-term memory (LSTM) algorithm is investigated for the purpose of automatic classification of epileptic disease from EEG signals. The signals have been processed by CNN for feature extraction from runtime environment while LSTM has used for classification of entire data. Finally, system demonstrates each EEG data file as normal or epileptic disease. In this research to describes a state of art for effective epileptic disease detection prediction and classification using hybrid deep learning algorithms. This research demonstrates a collaboration of CNN and LSTM for entire classification of EEG signals in numerous existing systems.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117084617","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 traditional agricultural supply chain management, due to involvement of many stakeholders in the entire procedure ranging from farmers, retailers to final vendors, it is merely the producer of the agricultural products i.e., farmers get its direct benefit. The middle stakeholders are always more beneficial than farmers and hence, the conditions of farmers are always the same though they sometimes get good earning and it is becoming a very serious concern in India. The major reason behind it, the transparency and traceability of the entire supply chain of this agricultural products journey from farm to vendor shop. In addition, consumers are becoming more conscious of where their food and food products come from. Block chains have distributed ledger technology (DLT) which has potential to provide transparency and trust for agricultural product supply chains at its different stages and even useful for improving its efficiency. This can boost confidence of all stakeholders who are involved in this farming supply chain. This research paper proposes the same concept in its subsequent sections.
{"title":"Enhancing Agricultural Product Supply Chain Management Using Blockchain Technology: Concept","authors":"M. A. Jawale, A. B. Pawar","doi":"10.3233/apc210240","DOIUrl":"https://doi.org/10.3233/apc210240","url":null,"abstract":"In traditional agricultural supply chain management, due to involvement of many stakeholders in the entire procedure ranging from farmers, retailers to final vendors, it is merely the producer of the agricultural products i.e., farmers get its direct benefit. The middle stakeholders are always more beneficial than farmers and hence, the conditions of farmers are always the same though they sometimes get good earning and it is becoming a very serious concern in India. The major reason behind it, the transparency and traceability of the entire supply chain of this agricultural products journey from farm to vendor shop. In addition, consumers are becoming more conscious of where their food and food products come from. Block chains have distributed ledger technology (DLT) which has potential to provide transparency and trust for agricultural product supply chains at its different stages and even useful for improving its efficiency. This can boost confidence of all stakeholders who are involved in this farming supply chain. This research paper proposes the same concept in its subsequent sections.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114406716","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}
S. S. Amiripalli, P. Likhitha, Sisankita Patnaik, Suresh Babu, Rampay. Venkatarao
Speech emotion detection has been extremely relevant in today’s digital culture in recent years. RAVDESS, TESS, and SAVEE Datasets were used to train the model in our project. To determine the precision of each algorithm with each dataset, we looked at ten separate Machine Learning Algorithms. Following that, we cleaned the datasets by using the mask feature to eliminate unnecessary background noise, and then we applied all 10 algorithms to this clean speech dataset to improve accuracy. Then we look at the accuracies of all ten algorithms and see which one is the greatest. Finally, by using the algorithm, we could calculate the number of sound files correlated with each of the emotions described in those datasets.
{"title":"A Study on Speech Emotion Recognitions on Machine Learning Algorithms","authors":"S. S. Amiripalli, P. Likhitha, Sisankita Patnaik, Suresh Babu, Rampay. Venkatarao","doi":"10.3233/apc210225","DOIUrl":"https://doi.org/10.3233/apc210225","url":null,"abstract":"Speech emotion detection has been extremely relevant in today’s digital culture in recent years. RAVDESS, TESS, and SAVEE Datasets were used to train the model in our project. To determine the precision of each algorithm with each dataset, we looked at ten separate Machine Learning Algorithms. Following that, we cleaned the datasets by using the mask feature to eliminate unnecessary background noise, and then we applied all 10 algorithms to this clean speech dataset to improve accuracy. Then we look at the accuracies of all ten algorithms and see which one is the greatest. Finally, by using the algorithm, we could calculate the number of sound files correlated with each of the emotions described in those datasets.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131299747","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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