Pub Date : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10150732
Thangarasan, D. J, P. M, P. Patro, S. J, Maniraj P
For the detection and prognosis of heart disease, Internet of Medical Things (IoMT) technology has recently been implemented in healthcare systems. The intended study's main objective is to foresee heart illness using medical data and imaging to classify data. Preprocessing is done on the input dataset to deal with missing values and incorrect data. IoT devices analyse the data they receive from patients, physicians, or nurses using the Modified Imperialist Competitive Algorithm (MICA). The IoT device's analysis of the data allows for effective and informed judgements to be made by humans, robots, and even other IoT devices. A modified imperialist competitive algorithm is suggested in this research in order to pinpoint the essential characteristics of heart disease. The Modified Imperialist Competitive Algorithm is used to select features for the diagnosis of heart disease (MICA). The improved self-adaptive Bayesian algorithm (ISABA) technique is then used to classify the chosen features into normal and abnormal states. For detecting normal sensor data and abnormal sensor data, respectively, the ISABA approach achieved accuracy of 96.85% and 98.31%. With a 96.32% specificity and a 99.15% maximum accuracy in categorizing images, the proposed model outperformed the competition
{"title":"Modified Imperialist Competitive Algorithm (MICA) For Smart Heart Disease Prediction in IoT System","authors":"Thangarasan, D. J, P. M, P. Patro, S. J, Maniraj P","doi":"10.1109/ICDCECE57866.2023.10150732","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150732","url":null,"abstract":"For the detection and prognosis of heart disease, Internet of Medical Things (IoMT) technology has recently been implemented in healthcare systems. The intended study's main objective is to foresee heart illness using medical data and imaging to classify data. Preprocessing is done on the input dataset to deal with missing values and incorrect data. IoT devices analyse the data they receive from patients, physicians, or nurses using the Modified Imperialist Competitive Algorithm (MICA). The IoT device's analysis of the data allows for effective and informed judgements to be made by humans, robots, and even other IoT devices. A modified imperialist competitive algorithm is suggested in this research in order to pinpoint the essential characteristics of heart disease. The Modified Imperialist Competitive Algorithm is used to select features for the diagnosis of heart disease (MICA). The improved self-adaptive Bayesian algorithm (ISABA) technique is then used to classify the chosen features into normal and abnormal states. For detecting normal sensor data and abnormal sensor data, respectively, the ISABA approach achieved accuracy of 96.85% and 98.31%. With a 96.32% specificity and a 99.15% maximum accuracy in categorizing images, the proposed model outperformed the competition","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124464055","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 : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10151144
Beibei Ren
As long as translators adapt to new technologies and are willing to learn new skills and adapt to the evolving needs of the market, the translation industry will continue to thrive. The purpose of this paper is to study MTPE model translation course recommendation based on mobile cloud computing technology. The characteristics of mobile cloud computing and distributed cloud computing translation course recommendation services and algorithms are studied. On the basis of machine translation, a classification system of error types (science and technology, humanities, medical articles) is established to guide students to identify machine translation errors, evaluate and make statistics and analysis on students' cognitive ability of translation quality and post-translation editing ability, and propose corresponding teaching strategies. After using the MTPE model based on mobile cloud technology for experimental teaching, the overall recognition rate of students is significantly improved, and the average number of vocabulary recognition errors is 88 and 23 times more than before experimental teaching. The average number of grammatical meaning recognition errors is 50 or 9 times more than that before experimental teaching. The recognition rate of contextual meaning is the highest, with an average of 86 errors. Other errors average 82; There are an average of 69 style correction questions. This shows that this technology can improve the students' error recognition rate and improve the learning effect.
{"title":"MTPE Model Translation Course Recommendations Based on Mobile Cloud Computing Technology","authors":"Beibei Ren","doi":"10.1109/ICDCECE57866.2023.10151144","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151144","url":null,"abstract":"As long as translators adapt to new technologies and are willing to learn new skills and adapt to the evolving needs of the market, the translation industry will continue to thrive. The purpose of this paper is to study MTPE model translation course recommendation based on mobile cloud computing technology. The characteristics of mobile cloud computing and distributed cloud computing translation course recommendation services and algorithms are studied. On the basis of machine translation, a classification system of error types (science and technology, humanities, medical articles) is established to guide students to identify machine translation errors, evaluate and make statistics and analysis on students' cognitive ability of translation quality and post-translation editing ability, and propose corresponding teaching strategies. After using the MTPE model based on mobile cloud technology for experimental teaching, the overall recognition rate of students is significantly improved, and the average number of vocabulary recognition errors is 88 and 23 times more than before experimental teaching. The average number of grammatical meaning recognition errors is 50 or 9 times more than that before experimental teaching. The recognition rate of contextual meaning is the highest, with an average of 86 errors. Other errors average 82; There are an average of 69 style correction questions. This shows that this technology can improve the students' error recognition rate and improve the learning effect.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125217589","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 : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10151146
Yu Jiang, Jun Ye, Zhengqi Zhang
With the innovation of technology, the amount of data has doubled and people have entered the era of big data. As one of the important resources, the economic and social value of data is increasing, but in the process of sharing, processing, circulation, and use of data, how to achieve a balance between the protection and utilization has become a key issue affecting national security today. Firstly, this paper presents the significance of this research based on the analysis of high-profile cases in recent years; Secondly, the current situation at national and international will be analyzed in two directions; national legislation and technical research; Thirdly, a summary of current problems. Finally, solutions are proposed on how to achieve the protection and use of personal information.
{"title":"Protection and Utilization of Personal Information in the Context of Big Data","authors":"Yu Jiang, Jun Ye, Zhengqi Zhang","doi":"10.1109/ICDCECE57866.2023.10151146","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151146","url":null,"abstract":"With the innovation of technology, the amount of data has doubled and people have entered the era of big data. As one of the important resources, the economic and social value of data is increasing, but in the process of sharing, processing, circulation, and use of data, how to achieve a balance between the protection and utilization has become a key issue affecting national security today. Firstly, this paper presents the significance of this research based on the analysis of high-profile cases in recent years; Secondly, the current situation at national and international will be analyzed in two directions; national legislation and technical research; Thirdly, a summary of current problems. Finally, solutions are proposed on how to achieve the protection and use of personal information.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"460 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125833784","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 : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10151119
Durga Bhavani Kinthadi, Abhishekar Burugu, Anish Rumandla, S. S
The demand for accurate identification and verification of a person has increased as the number of smart security systems has grown. In recent years, data from a human face has been used in numerous real-world applications, including social networking, security monitoring, advertising, and entertainment. Computer vision researchers have long been interested in this topic because automatic age and gender prediction from facial images is crucial for interpersonal communication. This work predicts that the gender will be either ‘Male’ or ‘Female,’ and that the age will be one of the following ranges: (0-5), (6-10), (11-17), (18-25), (25-32), (33-45), (46-55), (55-70). In the proposed system the images are preprocessed and then the convolutional neural networks are used to extract age and gender-related features and classified the images using the appropriate classifiers. The face images are taken from the UTK dataset and the proposed method achieved a training accuracy of 92.5% and a validation accuracy of 90%.
{"title":"Prediction of Human Age and Gender Using Deep Learning For Smart Security Systems","authors":"Durga Bhavani Kinthadi, Abhishekar Burugu, Anish Rumandla, S. S","doi":"10.1109/ICDCECE57866.2023.10151119","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151119","url":null,"abstract":"The demand for accurate identification and verification of a person has increased as the number of smart security systems has grown. In recent years, data from a human face has been used in numerous real-world applications, including social networking, security monitoring, advertising, and entertainment. Computer vision researchers have long been interested in this topic because automatic age and gender prediction from facial images is crucial for interpersonal communication. This work predicts that the gender will be either ‘Male’ or ‘Female,’ and that the age will be one of the following ranges: (0-5), (6-10), (11-17), (18-25), (25-32), (33-45), (46-55), (55-70). In the proposed system the images are preprocessed and then the convolutional neural networks are used to extract age and gender-related features and classified the images using the appropriate classifiers. The face images are taken from the UTK dataset and the proposed method achieved a training accuracy of 92.5% and a validation accuracy of 90%.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125965584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a new design scheme for an OCR platform. The scheme first pre-trains the model on a standard dataset to improve its basic recognition ability, and then fine-tunes the pre-trained model using transfer learning techniques to a custom scenario, thus improving its recognition ability in power industry applications. This approach greatly reduces the need for annotated data and can quickly adapt to new meter types and updates. Additionally, an intelligent data collection, processing, and analysis platform can effectively help power companies monitor, measure, diagnose, and predict equipment and meters, thereby enhancing enterprise safety and stability. By introducing transfer learning-related techniques, the model’s knowledge learned on a standard dataset is transferred to a custom scenario, improving its recognition ability in power industry-specific applications and achieving rapid warning and diagnosis of abnormal situations in power equipment, further improving production efficiency and safety of the enterprise.
{"title":"The Design Scheme of OCR and Analysis Platform for Power Meter Identification","authors":"Zhenlin Huang, Zheng Wang, Zhenyu Chen, Yongwen Gong, Xing Wen, Liuqi Zhao, Ning Wang, Ziyan Feng, Tianyi Qiu","doi":"10.1109/ICDCECE57866.2023.10150773","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150773","url":null,"abstract":"This paper proposes a new design scheme for an OCR platform. The scheme first pre-trains the model on a standard dataset to improve its basic recognition ability, and then fine-tunes the pre-trained model using transfer learning techniques to a custom scenario, thus improving its recognition ability in power industry applications. This approach greatly reduces the need for annotated data and can quickly adapt to new meter types and updates. Additionally, an intelligent data collection, processing, and analysis platform can effectively help power companies monitor, measure, diagnose, and predict equipment and meters, thereby enhancing enterprise safety and stability. By introducing transfer learning-related techniques, the model’s knowledge learned on a standard dataset is transferred to a custom scenario, improving its recognition ability in power industry-specific applications and achieving rapid warning and diagnosis of abnormal situations in power equipment, further improving production efficiency and safety of the enterprise.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114956023","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 : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10150451
Xiaofei Ma, Guanghui Yue, Yuanchen Wu
Under the deep influence of digital technology, the management of major power enterprises has entered the process of digital transformation. In this context, with the gradual development of power enterprises, the defects and problems in their management process are gradually exposed. Digital transformation requires power enterprises to face not only more complex business challenges, but also more management challenges. One of the most important problems is how to effectively solve the problem of information interaction, realize data sharing, maximize the value of resources, and comprehensively improve the management level and core competitiveness of enterprises. In order to solve this problem, based on the overview of power enterprise management, combined with computer information technology, this paper has carried out an in-depth study of its management digital transformation. To verify its effectiveness, this paper evaluates its management benefit ratio from seven aspects, including strategic management and equipment management. The result shows that the average benefit ratio of each management content under this method is about 83.6%. From the experimental results, it can be seen that computer information technology has high application value in the digital transformation of power enterprise management, which can significantly improve the efficiency of enterprise management and promote the sustainable development of power enterprise management. The computer information technology can effectively improve the management level of the enterprise, make the management work of strategy, project and resources orderly, improve the degree of information interaction inside and outside the enterprise, and promote the digital transformation and sustainable development of the enterprise.
{"title":"Application of Computer Information Technology in the Digital Transformation of Power Enterprise Management","authors":"Xiaofei Ma, Guanghui Yue, Yuanchen Wu","doi":"10.1109/ICDCECE57866.2023.10150451","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150451","url":null,"abstract":"Under the deep influence of digital technology, the management of major power enterprises has entered the process of digital transformation. In this context, with the gradual development of power enterprises, the defects and problems in their management process are gradually exposed. Digital transformation requires power enterprises to face not only more complex business challenges, but also more management challenges. One of the most important problems is how to effectively solve the problem of information interaction, realize data sharing, maximize the value of resources, and comprehensively improve the management level and core competitiveness of enterprises. In order to solve this problem, based on the overview of power enterprise management, combined with computer information technology, this paper has carried out an in-depth study of its management digital transformation. To verify its effectiveness, this paper evaluates its management benefit ratio from seven aspects, including strategic management and equipment management. The result shows that the average benefit ratio of each management content under this method is about 83.6%. From the experimental results, it can be seen that computer information technology has high application value in the digital transformation of power enterprise management, which can significantly improve the efficiency of enterprise management and promote the sustainable development of power enterprise management. The computer information technology can effectively improve the management level of the enterprise, make the management work of strategy, project and resources orderly, improve the degree of information interaction inside and outside the enterprise, and promote the digital transformation and sustainable development of the enterprise.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116064349","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 : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10150531
B. N., R. T
Agriculture-based irrigation systems are essential to the rural heritage due to their ability to deliver water to crops and prevent soil erosion. Irrigation systems provide a reliable source of water for crops, improving crop yields and quality. In areas with limited access to water, irrigation systems are often the only reliable way to provide water for crops. Irrigation systems have been used for centuries in rural areas and have been a valuable asset to society. In many cases, irrigation systems are the only way to keep crops alive and thriving. Without irrigation, crops may fail to thrive due to lack of water, leading to decreased yields and even crop failure. While irrigation systems are necessary for rural heritages, there are many potential risks associated with using them. Irrigation systems can be difficult to maintain, and the potential for water loss or over-irrigation is always present. Additionally, irrigation systems can be expensive to install and maintain, leading to an increased cost burden on farmers. In order to mitigate the risks associated with agriculture-based irrigation systems, farmers should implement water conservation practices, such as drip irrigation and water recycling. Additionally, farmers should research the different irrigation systems available to them, to ensure that they are using the most efficient irrigation system for their particular climate and soil conditions. Finally, farmers should monitor their irrigation systems carefully and take steps to address any issues that may arise.
{"title":"A Smart Innovation Development of Agriculture Based Irrigation Systems for Rural Heritages","authors":"B. N., R. T","doi":"10.1109/ICDCECE57866.2023.10150531","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150531","url":null,"abstract":"Agriculture-based irrigation systems are essential to the rural heritage due to their ability to deliver water to crops and prevent soil erosion. Irrigation systems provide a reliable source of water for crops, improving crop yields and quality. In areas with limited access to water, irrigation systems are often the only reliable way to provide water for crops. Irrigation systems have been used for centuries in rural areas and have been a valuable asset to society. In many cases, irrigation systems are the only way to keep crops alive and thriving. Without irrigation, crops may fail to thrive due to lack of water, leading to decreased yields and even crop failure. While irrigation systems are necessary for rural heritages, there are many potential risks associated with using them. Irrigation systems can be difficult to maintain, and the potential for water loss or over-irrigation is always present. Additionally, irrigation systems can be expensive to install and maintain, leading to an increased cost burden on farmers. In order to mitigate the risks associated with agriculture-based irrigation systems, farmers should implement water conservation practices, such as drip irrigation and water recycling. Additionally, farmers should research the different irrigation systems available to them, to ensure that they are using the most efficient irrigation system for their particular climate and soil conditions. Finally, farmers should monitor their irrigation systems carefully and take steps to address any issues that may arise.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116524541","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 : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10151337
K. Xing
This paper also evaluates various classification algorithm models and determines that the K nearest neighbor prediction model has the best performance in classifying and predicting academic performance; Based on the research results, suggestions for timely teaching interventions in the online learning process are provided, with a view to providing useful references for teachers to understand the learning situation of online learners, learners to improve the effectiveness of online learning, and managers to optimize educational decision-making. Music education is a research field that has existed for many years. It is an art form passed down from generation to generation, which can be said to be one of the most important things in life. Music plays a very important role in our life. It can bring out the best or worst emotions in our hearts. It is also considered one of the most popular forms of entertainment in the world. In this era, technology is very important in almost every aspect of life. With the progress of technology, new methods are needed to use it to make things easier or more efficient. One area where technology can be used to make things easier or more effective is music education. The main idea of the content-based method is that a document can be described by a set of features directly calculated from its content. Generally speaking, content-based multimedia data access requires specific methods, which must be customized for each specific media. However, the core information retrieval (IR) technology based on statistics and probability theory can be more widely used outside the text, because the underlying model can describe the basic features shared by different media, languages and application fields.
{"title":"Application of Data Mining Technology in Music Education Information","authors":"K. Xing","doi":"10.1109/ICDCECE57866.2023.10151337","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151337","url":null,"abstract":"This paper also evaluates various classification algorithm models and determines that the K nearest neighbor prediction model has the best performance in classifying and predicting academic performance; Based on the research results, suggestions for timely teaching interventions in the online learning process are provided, with a view to providing useful references for teachers to understand the learning situation of online learners, learners to improve the effectiveness of online learning, and managers to optimize educational decision-making. Music education is a research field that has existed for many years. It is an art form passed down from generation to generation, which can be said to be one of the most important things in life. Music plays a very important role in our life. It can bring out the best or worst emotions in our hearts. It is also considered one of the most popular forms of entertainment in the world. In this era, technology is very important in almost every aspect of life. With the progress of technology, new methods are needed to use it to make things easier or more efficient. One area where technology can be used to make things easier or more effective is music education. The main idea of the content-based method is that a document can be described by a set of features directly calculated from its content. Generally speaking, content-based multimedia data access requires specific methods, which must be customized for each specific media. However, the core information retrieval (IR) technology based on statistics and probability theory can be more widely used outside the text, because the underlying model can describe the basic features shared by different media, languages and application fields.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122329054","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 : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10150622
Jing Zhao
Population aging is a social problem that every country cannot avoid in the process of modernization. China has rapidly stepped into the threshold of an aging society. With the deepening of the aging of the population and with the increasing demand for diversified services for the elderly, there is an urgent need to provide multi-level, high-quality elderly care(ec) services for the elderly. There is a large gap in human resources and other resources in the traditional pension industry. The pension industry needs to develop. Zhiyi pension has opened a new realm of the pension model. It cannot only provide a variety of life assistance, Rehabilitation care, psychological comfort and social support services for the elderly through intelligent decision-making and control, but also always protect the safety of the elderly and meet the multi-level and diversified service The needs of urban and rural elderly. We should play the leading comprehensive role of innovation driving role of information technology, accelerate the development of smart health care industry, improve people's livelihood and cultivate new economic drivers, On the 23rd of 2017, the Ministry of Industry, Information Technology and Information Technology, the Ministry of Civil Affairs and the Health and Family Planning Commission jointly issued the Action Plan for the Development of Smart ec Industry (2017-2022), which explicitly mentioned the year 2022, It will "basically form a smart health care industry system covering the whole life cycle. So far, the Smart Pension (SM) industry has completed its overall layout and entered the practical level.
{"title":"Construction of Smart Pension System for Urban and Rural Residents Based on Big Data Mining Algorithm","authors":"Jing Zhao","doi":"10.1109/ICDCECE57866.2023.10150622","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10150622","url":null,"abstract":"Population aging is a social problem that every country cannot avoid in the process of modernization. China has rapidly stepped into the threshold of an aging society. With the deepening of the aging of the population and with the increasing demand for diversified services for the elderly, there is an urgent need to provide multi-level, high-quality elderly care(ec) services for the elderly. There is a large gap in human resources and other resources in the traditional pension industry. The pension industry needs to develop. Zhiyi pension has opened a new realm of the pension model. It cannot only provide a variety of life assistance, Rehabilitation care, psychological comfort and social support services for the elderly through intelligent decision-making and control, but also always protect the safety of the elderly and meet the multi-level and diversified service The needs of urban and rural elderly. We should play the leading comprehensive role of innovation driving role of information technology, accelerate the development of smart health care industry, improve people's livelihood and cultivate new economic drivers, On the 23rd of 2017, the Ministry of Industry, Information Technology and Information Technology, the Ministry of Civil Affairs and the Health and Family Planning Commission jointly issued the Action Plan for the Development of Smart ec Industry (2017-2022), which explicitly mentioned the year 2022, It will \"basically form a smart health care industry system covering the whole life cycle. So far, the Smart Pension (SM) industry has completed its overall layout and entered the practical level.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122030318","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 : 2023-04-29DOI: 10.1109/ICDCECE57866.2023.10151268
S. Suparshya Babu, S. K
Green IT (information technology) can ultimately change how we think about energy harvesting. We can develop novel approaches to capture energy from renewable sources, such as sunlight and wind, by utilizing the power of IT. Then, we can use this energy to run our homes and do other daily chores. We will examine the possibilities of green IT for energy collecting and review several applications in this post. Using intelligent grids is one of the most promising approaches to leverage green IT for energy gathering. By gathering data from each of their parts and sending it to a central place, intelligent grids are intended to use energy more effectively. The most economical and efficient energy sources for a specific location can then be identified using this data. We can develop a more sustainable energy system by integrating this data with solar, wind, and other renewable energy sources. An efficient energy storage system can also be made using green IT. We can develop energy storage systems that are more effective and economical by utilizing information technology. This can entail the utilization of batteries, solar energy systems, or other renewable resources. We can make sure that energy is available when and where needed by leveraging green IT to build an energy storage system.
{"title":"The Performance Optimization of Harnessing Green Information Technology for Energy Harvesting","authors":"S. Suparshya Babu, S. K","doi":"10.1109/ICDCECE57866.2023.10151268","DOIUrl":"https://doi.org/10.1109/ICDCECE57866.2023.10151268","url":null,"abstract":"Green IT (information technology) can ultimately change how we think about energy harvesting. We can develop novel approaches to capture energy from renewable sources, such as sunlight and wind, by utilizing the power of IT. Then, we can use this energy to run our homes and do other daily chores. We will examine the possibilities of green IT for energy collecting and review several applications in this post. Using intelligent grids is one of the most promising approaches to leverage green IT for energy gathering. By gathering data from each of their parts and sending it to a central place, intelligent grids are intended to use energy more effectively. The most economical and efficient energy sources for a specific location can then be identified using this data. We can develop a more sustainable energy system by integrating this data with solar, wind, and other renewable energy sources. An efficient energy storage system can also be made using green IT. We can develop energy storage systems that are more effective and economical by utilizing information technology. This can entail the utilization of batteries, solar energy systems, or other renewable resources. We can make sure that energy is available when and where needed by leveraging green IT to build an energy storage system.","PeriodicalId":221860,"journal":{"name":"2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117009562","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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