Expense tracker is an expense management system designed for day-to-day life. The application capably tracks the daily expenses of the user. Such applications allow the users to easily manage their expenditure and hence, eliminates the need of manual paper tasks. Such trackers are computerized diaries used to keep a record of the transactions made by the user. This paper explains about an expense tracker web application that inputs the salary from the user, source of this income and the date of earning that salary and creates a transaction entry as an income. It sums the entries to the total amount of income and makes real time changes. Similarly, it will also input the expenses and make entries for the same. The entries can be deleted after creation. The distribution of income and the expenditure can be visualized in the form of charts and graphs that will keep updating as per user’s transaction.
{"title":"TrackEZ Expense Tracker","authors":"Priyanka Bhatele, Divya Mahajan, B. Mahajan, Divesh Mahajan, Nikhil Mahajan, Prasad Mahajan","doi":"10.1109/INCET57972.2023.10170735","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170735","url":null,"abstract":"Expense tracker is an expense management system designed for day-to-day life. The application capably tracks the daily expenses of the user. Such applications allow the users to easily manage their expenditure and hence, eliminates the need of manual paper tasks. Such trackers are computerized diaries used to keep a record of the transactions made by the user. This paper explains about an expense tracker web application that inputs the salary from the user, source of this income and the date of earning that salary and creates a transaction entry as an income. It sums the entries to the total amount of income and makes real time changes. Similarly, it will also input the expenses and make entries for the same. The entries can be deleted after creation. The distribution of income and the expenditure can be visualized in the form of charts and graphs that will keep updating as per user’s transaction.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"269 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115599540","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}
Optical Character Recognition (OCR) is a widely used technology that converts image text or handwritten text into digital form. However, recognizing handwritten text, printed text, and image text poses a significant challenge due to variations in writing styles and the complexity of characters. This paper proposes a novel approach for OCR using Convolutional Recurrent Neural Network (CRNN) that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The proposed CRNN architecture can automatically learn and extract features from raw image pixels and recognize sequential patterns of characters. This research paper presents a robust OCR system using CRNN architecture with 7 convolutional layers and 2 LSTM layers for recognizing text in images with complex backgrounds and varying fonts. The proposed system achieved state-of-the-art performance on several benchmark datasets, demonstrating the effectiveness of the proposed approach. Our experimental results demonstrate that the proposed CRNN approach is better than other methods and achieves higher accuracy with less latency in recognizing text from an image. We also analyze the impact of different parameters, such as the number of layers, filter sizes, and hidden units, on the performance of the CRNN model. This paper provides a comprehensive study on OCR using CRNN and its potential to improve the accuracy and efficiency of recognizing text.
{"title":"OCR using CRNN: A Deep Learning Approach for Text Recognition","authors":"Aditya Yadav, Shauryan Singh, Muzzamil Siddique, Nileshkumar Mehta, Archana Kotangale","doi":"10.1109/INCET57972.2023.10170436","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170436","url":null,"abstract":"Optical Character Recognition (OCR) is a widely used technology that converts image text or handwritten text into digital form. However, recognizing handwritten text, printed text, and image text poses a significant challenge due to variations in writing styles and the complexity of characters. This paper proposes a novel approach for OCR using Convolutional Recurrent Neural Network (CRNN) that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The proposed CRNN architecture can automatically learn and extract features from raw image pixels and recognize sequential patterns of characters. This research paper presents a robust OCR system using CRNN architecture with 7 convolutional layers and 2 LSTM layers for recognizing text in images with complex backgrounds and varying fonts. The proposed system achieved state-of-the-art performance on several benchmark datasets, demonstrating the effectiveness of the proposed approach. Our experimental results demonstrate that the proposed CRNN approach is better than other methods and achieves higher accuracy with less latency in recognizing text from an image. We also analyze the impact of different parameters, such as the number of layers, filter sizes, and hidden units, on the performance of the CRNN model. This paper provides a comprehensive study on OCR using CRNN and its potential to improve the accuracy and efficiency of recognizing text.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124394984","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170125
K. Haleema, Sruthi Kumari Juluri, S. Pooja Sree, Praneeth Karnekota, K. Murugaperumal
The sustainable energy crisis is the primary social challenge in the Modern civilization. Global warming and the fast-exacting fossil fuels lead the energy generations from alternative renewable resources such as solar, wind, biomass, tidal etc. The main intention of our study is to design and develop to a hybrid renewable electrification system for urban residential community load. The proposed configuration of the HRE system consider of solar Photovoltaic, vertical wind turbine, biomass and gen-set including a battery storage system and bidirectional converter to meet the urban apartment load smoothly and economically. The optimized techno economical model will be designed through NREL’s Hybrid Optimization if Multiple Energy Resources, and the feasibility and comparative analysis will enrich its performance. The proposed system's outcome is expected to fulfil the sustainable goals of high renewable factors and the least net cost of the HRE system with environmental carbon credits. Plan of action includes the following steps: 1) Site resources analysis 2) Energy demand analysis 3) Energy generation technologies analysis 4) Hybrid renewable model construction 5) Optimal techno economic analysis 6) Feasibility report of the cost effective HRE configuration for urban community load.
{"title":"Sustainable Designing of Hybrid Renewable Electrification System for Urban Residential Community Load","authors":"K. Haleema, Sruthi Kumari Juluri, S. Pooja Sree, Praneeth Karnekota, K. Murugaperumal","doi":"10.1109/INCET57972.2023.10170125","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170125","url":null,"abstract":"The sustainable energy crisis is the primary social challenge in the Modern civilization. Global warming and the fast-exacting fossil fuels lead the energy generations from alternative renewable resources such as solar, wind, biomass, tidal etc. The main intention of our study is to design and develop to a hybrid renewable electrification system for urban residential community load. The proposed configuration of the HRE system consider of solar Photovoltaic, vertical wind turbine, biomass and gen-set including a battery storage system and bidirectional converter to meet the urban apartment load smoothly and economically. The optimized techno economical model will be designed through NREL’s Hybrid Optimization if Multiple Energy Resources, and the feasibility and comparative analysis will enrich its performance. The proposed system's outcome is expected to fulfil the sustainable goals of high renewable factors and the least net cost of the HRE system with environmental carbon credits. Plan of action includes the following steps: 1) Site resources analysis 2) Energy demand analysis 3) Energy generation technologies analysis 4) Hybrid renewable model construction 5) Optimal techno economic analysis 6) Feasibility report of the cost effective HRE configuration for urban community load.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"460 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123050797","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170263
Ruturaj Sutaria, R. Jain
Car price prediction is a crucial task in the automotive industry as it helps manufacturers, dealers, and buyers make informed decisions. In this project, we propose a model to predict the price of a car based on its attributes such as make, model, year, and mileage. We collected a dataset of used car listings and used it to train and test our model. Our model is based on a combination of linear regression and decision tree algorithms. The model was able to predict car prices with an accuracy of over 90%. Random Forest is well-suited for car price prediction because it is a powerful machine-learning algorithm that is capable of handling a high number of input features and modeling complex relationships between these features. Unlike linear regression, which assumes a linear relationship between the input features and the target variable, Random Forest can account for non-linear and complex interactions between features. This means that it can capture complex and intricate relationships between various features such as the make, model, year, engine size, and other specifications of a car and its price. Additionally, Random Forest can handle large amounts of data and noisy datasets, making it an ideal choice for car price prediction, where there may be a large number of features and a large dataset to work with. The proposed model can assist car sellers in pricing their cars competitively and can also assist buyers in identifying fair prices for the cars they wish to purchase. This model can be useful for car dealers, sellers, and buyers to make better decisions.
{"title":"Auto-Price Forecast: An Analysis of Car Value Trends","authors":"Ruturaj Sutaria, R. Jain","doi":"10.1109/INCET57972.2023.10170263","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170263","url":null,"abstract":"Car price prediction is a crucial task in the automotive industry as it helps manufacturers, dealers, and buyers make informed decisions. In this project, we propose a model to predict the price of a car based on its attributes such as make, model, year, and mileage. We collected a dataset of used car listings and used it to train and test our model. Our model is based on a combination of linear regression and decision tree algorithms. The model was able to predict car prices with an accuracy of over 90%. Random Forest is well-suited for car price prediction because it is a powerful machine-learning algorithm that is capable of handling a high number of input features and modeling complex relationships between these features. Unlike linear regression, which assumes a linear relationship between the input features and the target variable, Random Forest can account for non-linear and complex interactions between features. This means that it can capture complex and intricate relationships between various features such as the make, model, year, engine size, and other specifications of a car and its price. Additionally, Random Forest can handle large amounts of data and noisy datasets, making it an ideal choice for car price prediction, where there may be a large number of features and a large dataset to work with. The proposed model can assist car sellers in pricing their cars competitively and can also assist buyers in identifying fair prices for the cars they wish to purchase. This model can be useful for car dealers, sellers, and buyers to make better decisions.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114656040","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}
Due to the bypass diode operating across the shaded module, the electrical characteristics of the PV system under partly shaded PSC display numerous maxima. In order to get the most out of the PV system, it needs to be forced to run at global MPP under PSC. In this paper, Metaheuristic MPPT strategies Enhanced Grey Wolf Optimization algorithm (EGWO) and Marine Predator Algorithm (MPA) are discussed and comparison has been done. The use of suggested MPPT approaches for global MPP tracking exposed to PSC for dynamically changing shading patterns for 8S (Eight series) PV setups is discussed, and tracking results are shown.
{"title":"Applications of Metaheuristic Algorithms for MPPT Under Partial Shaded Condition in PV System","authors":"Sampath Kumar Vankadara, Shamik Chatterjee, Praveen Kumar Balachandran","doi":"10.1109/INCET57972.2023.10170183","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170183","url":null,"abstract":"Due to the bypass diode operating across the shaded module, the electrical characteristics of the PV system under partly shaded PSC display numerous maxima. In order to get the most out of the PV system, it needs to be forced to run at global MPP under PSC. In this paper, Metaheuristic MPPT strategies Enhanced Grey Wolf Optimization algorithm (EGWO) and Marine Predator Algorithm (MPA) are discussed and comparison has been done. The use of suggested MPPT approaches for global MPP tracking exposed to PSC for dynamically changing shading patterns for 8S (Eight series) PV setups is discussed, and tracking results are shown.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121309127","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 improvement of driving machine safety and accident prevention is one of the industry's top priorities. Many folks don't adhere to the legal traffic norms and regulations. This may also contribute to traffic collisions. Most traffic collisions are not done on purpose. Serious mistakes like being drowsy or exhausted might have a negative impact. An Aid System for Driver Safety has been put in place to prevent similar scenarios. This device has the capacity to get better driving comfort and security for drivers. This technique may be quite beneficial to elderly people as well. A human-machine interface was used in the construction of an assistance system for drivers' safety, which helps to increase traffic safety. Accidents which are caused by human errors can also be reduced. Some common safety technologies like wearing seatbelts and airbags are not able to prevent road destructions. An Assistance System for Driver’s Safety also alerts the driver during problems such as drowsiness, colliding objects, etc. This system helps in maintaining the stability of the vehicle under critical situations.
{"title":"An Assistance System for Driver’s Safety based on YOLO Algorithm","authors":"Pooja Patil, Sejal Borkar, Pranita Awari, Cristan Jangul","doi":"10.1109/INCET57972.2023.10170480","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170480","url":null,"abstract":"The improvement of driving machine safety and accident prevention is one of the industry's top priorities. Many folks don't adhere to the legal traffic norms and regulations. This may also contribute to traffic collisions. Most traffic collisions are not done on purpose. Serious mistakes like being drowsy or exhausted might have a negative impact. An Aid System for Driver Safety has been put in place to prevent similar scenarios. This device has the capacity to get better driving comfort and security for drivers. This technique may be quite beneficial to elderly people as well. A human-machine interface was used in the construction of an assistance system for drivers' safety, which helps to increase traffic safety. Accidents which are caused by human errors can also be reduced. Some common safety technologies like wearing seatbelts and airbags are not able to prevent road destructions. An Assistance System for Driver’s Safety also alerts the driver during problems such as drowsiness, colliding objects, etc. This system helps in maintaining the stability of the vehicle under critical situations.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127307380","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170196
Chang Liu, Jiawen Ma, Jingwen Du
Text generated image algorithm is an advanced image generation technology, which has been used to create countermeasure networks. It uses the principle of text generation and also generates images to create a countermeasure network. The algorithm of text generating image is based on generating countermeasure network. The algorithm generates the countermeasure network by using the counters of the nodes in the text generation network. The main idea behind this algorithm is that when we use text to generate countermeasures for nodes, it will be more effective than using only one node. In other words, if we have two or more nodes and they are connected to each other through some links, these links can be used as part of our countermeasure system. The main advantage of this method is that it can be used in all languages, including English and other languages. This technology can be used in various applications, such as security systems, surveillance cameras, etc., and they are more effective than other methods because they can generate high-quality images.
{"title":"Text Generation Image Algorithm based on Generating Countermeasure Network","authors":"Chang Liu, Jiawen Ma, Jingwen Du","doi":"10.1109/INCET57972.2023.10170196","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170196","url":null,"abstract":"Text generated image algorithm is an advanced image generation technology, which has been used to create countermeasure networks. It uses the principle of text generation and also generates images to create a countermeasure network. The algorithm of text generating image is based on generating countermeasure network. The algorithm generates the countermeasure network by using the counters of the nodes in the text generation network. The main idea behind this algorithm is that when we use text to generate countermeasures for nodes, it will be more effective than using only one node. In other words, if we have two or more nodes and they are connected to each other through some links, these links can be used as part of our countermeasure system. The main advantage of this method is that it can be used in all languages, including English and other languages. This technology can be used in various applications, such as security systems, surveillance cameras, etc., and they are more effective than other methods because they can generate high-quality images.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127534049","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170040
K. Ratheesh, K. Rajeev, Jyothika S, Athira B Menon, Rahul Krishnan Pathinarupothi
Sleep is the most essential and fundamental to an individual’s well-being and vitality because it provides for the restoration and re-energizing of both the body and mind. Sleep apnea is a common sleep problem that affects millions of individuals worldwide. It is distinguished by breathing pauses or shallow breathing during sleeping, which can result in a variety of health problems such as heart disease, stroke, and diabetes [1]. Sleep apnea diagnosis and management can be difficult because the cost and time-consuming polysomnography (PSG) testing requires specialized equipment and trained personnel. To address these concerns, we created and validated an artificial intelligence (AI)-based sleep apnea scoring system that analyses electrocardiogram (ECG) signals to predict the severity of sleep apnea. The system analyses ECG signals using 1D-CNN to predict the Apnea-Hypopnea Index (AHI), a measure of the severity of sleep apnea. The tool is organized into three sections: data exploration, data visualization, and prediction, and it is aimed at accurately forecasting patients’ risk of sleep apnea. Our research demonstrates the potential of AI-based approaches for the diagnosis and management of sleep apnea, and we believe that our system can help improve patient outcomes and quality of life.
{"title":"Open Tool-kit for AI-based Sleep Apnea Scoring","authors":"K. Ratheesh, K. Rajeev, Jyothika S, Athira B Menon, Rahul Krishnan Pathinarupothi","doi":"10.1109/INCET57972.2023.10170040","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170040","url":null,"abstract":"Sleep is the most essential and fundamental to an individual’s well-being and vitality because it provides for the restoration and re-energizing of both the body and mind. Sleep apnea is a common sleep problem that affects millions of individuals worldwide. It is distinguished by breathing pauses or shallow breathing during sleeping, which can result in a variety of health problems such as heart disease, stroke, and diabetes [1]. Sleep apnea diagnosis and management can be difficult because the cost and time-consuming polysomnography (PSG) testing requires specialized equipment and trained personnel. To address these concerns, we created and validated an artificial intelligence (AI)-based sleep apnea scoring system that analyses electrocardiogram (ECG) signals to predict the severity of sleep apnea. The system analyses ECG signals using 1D-CNN to predict the Apnea-Hypopnea Index (AHI), a measure of the severity of sleep apnea. The tool is organized into three sections: data exploration, data visualization, and prediction, and it is aimed at accurately forecasting patients’ risk of sleep apnea. Our research demonstrates the potential of AI-based approaches for the diagnosis and management of sleep apnea, and we believe that our system can help improve patient outcomes and quality of life.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125315543","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170385
Jing Wu, Ying Zhang
The rapid development of modern information and communication technology has greatly enriched and improved the means of cultural and creative communication. As the underlying technical framework of the Internet, blockchain has been applied in many fields, and "Internet plus+cultural and creative industry" is also increasingly valued. Nowadays, the media technology potential of blockchain has been applied to various media platforms, and has optimized the original communication process with its own advantages of decentralization, asymmetric encryption and autonomy. Based on this new modern underlying technology framework, the paper uses the relevant theories of cultural and creative communication, and adopts interdisciplinary and comparative analysis methods to explore the possible changes that blockchain technology may cause in the field of information communication, aiming at bringing new perspectives and reference values to the traditional media that need to be innovated on how to actively use new technology communication. Cultural and creative products have the functions of spreading culture, protecting culture and promoting cultural heritage. However, the full play of cultural and creative products depends on the successful promotion of the products. Therefore, this paper proposes a cultural and creative product promotion system based on blockchain technology. Through research, blockchain technology can better promote cultural and creative products, indicating that blockchain technology has good application value in promotion.
{"title":"The Application of Blockchain Technology in The Promotion of Cultural and Creative Products","authors":"Jing Wu, Ying Zhang","doi":"10.1109/INCET57972.2023.10170385","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170385","url":null,"abstract":"The rapid development of modern information and communication technology has greatly enriched and improved the means of cultural and creative communication. As the underlying technical framework of the Internet, blockchain has been applied in many fields, and \"Internet plus+cultural and creative industry\" is also increasingly valued. Nowadays, the media technology potential of blockchain has been applied to various media platforms, and has optimized the original communication process with its own advantages of decentralization, asymmetric encryption and autonomy. Based on this new modern underlying technology framework, the paper uses the relevant theories of cultural and creative communication, and adopts interdisciplinary and comparative analysis methods to explore the possible changes that blockchain technology may cause in the field of information communication, aiming at bringing new perspectives and reference values to the traditional media that need to be innovated on how to actively use new technology communication. Cultural and creative products have the functions of spreading culture, protecting culture and promoting cultural heritage. However, the full play of cultural and creative products depends on the successful promotion of the products. Therefore, this paper proposes a cultural and creative product promotion system based on blockchain technology. Through research, blockchain technology can better promote cultural and creative products, indicating that blockchain technology has good application value in promotion.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125546753","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 : 2023-05-26DOI: 10.1109/INCET57972.2023.10170476
A. Rehash Rushmi Pavitra, K. Anushree, A. V. R. Akshayalakshmi, K. Vijayalakshmi
Artificial Intelligence (AI) refers to the use of advanced computational algorithms and technologies to replicate or simulate human intelligence in machines or computer systems. Human expression is incredibly important in determining a person’s current condition and mood. AI is utilized to analyze human facial expressions and extract emotions based on features such as cheeks, forehead, eyes, and smiles. In addition, “songs” refers to an expressive medium that has always been the best option for analyzing and comprehending human emotions. The proposed ’smart music player' is a programmed system that functions under the assumption that we can tell someone’s mood by the expression on his/her face. This model that recognizes facial micro-expressions with multicultural facial expression details, recommends music in accordance with corresponding mood. It is developed using a combination of song’s features and micro-expression recognition technology of convolutional neural network. To do this, group facial expressions into seven distinct emotional groups, including happy, sad, angry, neutral, surprise and disgust. The primary objective of this study paper is to present an overview of a useful music player and social companion that automatically creates a playlist that will brighten your day based on your emotional condition, along with recommendations for future studies in the field of recommendation systems.
{"title":"Artificial Intelligence (AI) Enabled Music Player System for User Facial Recognition","authors":"A. Rehash Rushmi Pavitra, K. Anushree, A. V. R. Akshayalakshmi, K. Vijayalakshmi","doi":"10.1109/INCET57972.2023.10170476","DOIUrl":"https://doi.org/10.1109/INCET57972.2023.10170476","url":null,"abstract":"Artificial Intelligence (AI) refers to the use of advanced computational algorithms and technologies to replicate or simulate human intelligence in machines or computer systems. Human expression is incredibly important in determining a person’s current condition and mood. AI is utilized to analyze human facial expressions and extract emotions based on features such as cheeks, forehead, eyes, and smiles. In addition, “songs” refers to an expressive medium that has always been the best option for analyzing and comprehending human emotions. The proposed ’smart music player' is a programmed system that functions under the assumption that we can tell someone’s mood by the expression on his/her face. This model that recognizes facial micro-expressions with multicultural facial expression details, recommends music in accordance with corresponding mood. It is developed using a combination of song’s features and micro-expression recognition technology of convolutional neural network. To do this, group facial expressions into seven distinct emotional groups, including happy, sad, angry, neutral, surprise and disgust. The primary objective of this study paper is to present an overview of a useful music player and social companion that automatically creates a playlist that will brighten your day based on your emotional condition, along with recommendations for future studies in the field of recommendation systems.","PeriodicalId":403008,"journal":{"name":"2023 4th International Conference for Emerging Technology (INCET)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126631496","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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