Pub Date : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640661
Ruizhu Xi, Bencai Gao, Xiao Xia
Data analysis and clustering technologies have becoming the state-of-the-art method of analyzing the complex information. Hence, this paper studies the real-time feedback system of the funding data flow based on the data tracking and classification. The existing research work pays little attention to the secure deletion of private data in mobile cloud, especially the secure deletion of payment information and sensitive private messages generated by mobile cloud and mobile terminal, which is not recoverable, hence, the model is implemented with the optimization of data tracking framework and the classification. After building the model, this research wrk applies it into the funding data flow tracking and monitoring, as well as considering the real-time requirement. The proposed system has been tested on various data sets and the convincing results are achieved.
{"title":"Real-time Feedback System of Funding Data Flow Based on Data Tracking and Classification","authors":"Ruizhu Xi, Bencai Gao, Xiao Xia","doi":"10.1109/I-SMAC52330.2021.9640661","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640661","url":null,"abstract":"Data analysis and clustering technologies have becoming the state-of-the-art method of analyzing the complex information. Hence, this paper studies the real-time feedback system of the funding data flow based on the data tracking and classification. The existing research work pays little attention to the secure deletion of private data in mobile cloud, especially the secure deletion of payment information and sensitive private messages generated by mobile cloud and mobile terminal, which is not recoverable, hence, the model is implemented with the optimization of data tracking framework and the classification. After building the model, this research wrk applies it into the funding data flow tracking and monitoring, as well as considering the real-time requirement. The proposed system has been tested on various data sets and the convincing results are achieved.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117138082","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640723
B. Dhanalaxmi, K. Anirudh, G. Nikhitha, R. Jyothi
The approach of new technological developments in the genetic disease repository has facilitated genetic disease treatment. In the post-genomic time gene detection, which causes genetically excessive diseases, is one of the greatest deterrent tasks. Complex diseases are frequently very heterogeneous and make biological markers difficult to identify. Markers commonly depend on the Machine Learning Algorithms to define, but their success completely depends on the quality and dimensions of the data present. In the machine learning area, computers are promised to support people and analyze large and complex data systems primarily for the production of practically enhanced algorithms. A supervised machine learning methodology has been developed to predict complex genes that cause disease and experiment with the developed algorithm to improve and identify genetic classifications that engage in complex diseases. Genetic Disease Analyzer (GDA) was de veloped using machine learning using the Principal Component Analysis (PCA), Random forest, Naive Bayes and Decision Tree algorithms and the results were compared. The accuracy of 98.79% and sensitivity of 98.67% for the GEO data set is provided for the GDA model. The results of machine learning approaches were examined and their practical applications were discussed in the study of genetic and genomic data.
{"title":"A Survey on Analysis of Genetic Diseases Using Machine Learning Techniques","authors":"B. Dhanalaxmi, K. Anirudh, G. Nikhitha, R. Jyothi","doi":"10.1109/I-SMAC52330.2021.9640723","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640723","url":null,"abstract":"The approach of new technological developments in the genetic disease repository has facilitated genetic disease treatment. In the post-genomic time gene detection, which causes genetically excessive diseases, is one of the greatest deterrent tasks. Complex diseases are frequently very heterogeneous and make biological markers difficult to identify. Markers commonly depend on the Machine Learning Algorithms to define, but their success completely depends on the quality and dimensions of the data present. In the machine learning area, computers are promised to support people and analyze large and complex data systems primarily for the production of practically enhanced algorithms. A supervised machine learning methodology has been developed to predict complex genes that cause disease and experiment with the developed algorithm to improve and identify genetic classifications that engage in complex diseases. Genetic Disease Analyzer (GDA) was de veloped using machine learning using the Principal Component Analysis (PCA), Random forest, Naive Bayes and Decision Tree algorithms and the results were compared. The accuracy of 98.79% and sensitivity of 98.67% for the GEO data set is provided for the GDA model. The results of machine learning approaches were examined and their practical applications were discussed in the study of genetic and genomic data.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117302548","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9641052
V. K. Prathyushaa, P. Chandrasekar, R. Anuradha
Western music notation converter is essential in the field of music for the conversion of music notes which are mostly in Western staff notation to its Carnatic music note equivalent. It is difficult for the Carnatic musicians and singers to have the music notes in the form of the corresponding Swaras in Carnatic music to comprehend them. Over the past few decades, researchers have built models that recognise handwritten musical notations called Optical Music Recognition (OMR) [9]. But, when researchers who are from a non-musical background work with digital representations, the task becomes tedious and a need for processing the images arises. Therefore, instead of relying on humans for conversion of notations, image processing models are used with the help of transfer learning and classification is done using 4 models, of which 3 are pre-trained, i.e., ResNet50, VGG19, InceptionV3 and one is a simple CNN model. The models provide competitive results when compared to human experts labelling of datasets.
{"title":"A Comparative Study of Image Classification Models for Western Notation to Carnatic Notation : Conversion of Western Music Notation to Carnatic Music Notation","authors":"V. K. Prathyushaa, P. Chandrasekar, R. Anuradha","doi":"10.1109/I-SMAC52330.2021.9641052","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9641052","url":null,"abstract":"Western music notation converter is essential in the field of music for the conversion of music notes which are mostly in Western staff notation to its Carnatic music note equivalent. It is difficult for the Carnatic musicians and singers to have the music notes in the form of the corresponding Swaras in Carnatic music to comprehend them. Over the past few decades, researchers have built models that recognise handwritten musical notations called Optical Music Recognition (OMR) [9]. But, when researchers who are from a non-musical background work with digital representations, the task becomes tedious and a need for processing the images arises. Therefore, instead of relying on humans for conversion of notations, image processing models are used with the help of transfer learning and classification is done using 4 models, of which 3 are pre-trained, i.e., ResNet50, VGG19, InceptionV3 and one is a simple CNN model. The models provide competitive results when compared to human experts labelling of datasets.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123398092","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640725
Keshav Kumar, Anil Kumar Kori
For problem of load flow and power flow analysis is variable stability index. Also, arrangement of different bus system and fault tolerance occurrence across the load. In this case, resolution of power quality and improvement of power distribution performance apply islanding protection method. This paper is resenting result and simulation section arrangement of 9 bus system and Reducing Fault effects.
{"title":"Power Load flow analysis for Active Islanding Mode","authors":"Keshav Kumar, Anil Kumar Kori","doi":"10.1109/I-SMAC52330.2021.9640725","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640725","url":null,"abstract":"For problem of load flow and power flow analysis is variable stability index. Also, arrangement of different bus system and fault tolerance occurrence across the load. In this case, resolution of power quality and improvement of power distribution performance apply islanding protection method. This paper is resenting result and simulation section arrangement of 9 bus system and Reducing Fault effects.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"64 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123443971","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640750
S. Routray, Laxmi Sharma, Anindita Sahoo, A. Javali, S. K P, Eisha Akanksha
Smart systems are now very much common in several applications. These systems are found in large numbers in our daily lives in the recent times. The current pandemic induced restrictions forced us to go for all kinds of smart systems which can provide both the comfort as well as the essential functions needed at the ground level. Classrooms are among the basic needs of the modern education system. There are several new developments in the commonly used technologies which can make the classrooms better and smarter. Digital technologies are the main front runners of these smart initiatives. Among these smart digital technologies, information and communication technologies (ICT) and immersive technologies are found to be the main enablers. This research study reviews the main technologies used for smart classrooms. Moreover, it has been shown that the smart classrooms are essential for the future generation. These smart classrooms can handle several limitations of the traditional classrooms. In addition to the typical teaching and learning processes, smart classrooms can provide value added services to the teachers, students and other stakeholders. Finally, this research work analyzes the long term value and sustainability of these smart classrooms.
{"title":"IoT and Immersive Technology based Smart Classrooms","authors":"S. Routray, Laxmi Sharma, Anindita Sahoo, A. Javali, S. K P, Eisha Akanksha","doi":"10.1109/I-SMAC52330.2021.9640750","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640750","url":null,"abstract":"Smart systems are now very much common in several applications. These systems are found in large numbers in our daily lives in the recent times. The current pandemic induced restrictions forced us to go for all kinds of smart systems which can provide both the comfort as well as the essential functions needed at the ground level. Classrooms are among the basic needs of the modern education system. There are several new developments in the commonly used technologies which can make the classrooms better and smarter. Digital technologies are the main front runners of these smart initiatives. Among these smart digital technologies, information and communication technologies (ICT) and immersive technologies are found to be the main enablers. This research study reviews the main technologies used for smart classrooms. Moreover, it has been shown that the smart classrooms are essential for the future generation. These smart classrooms can handle several limitations of the traditional classrooms. In addition to the typical teaching and learning processes, smart classrooms can provide value added services to the teachers, students and other stakeholders. Finally, this research work analyzes the long term value and sustainability of these smart classrooms.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123071709","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640675
Ameyaa Biwalkar, Ashwini Rao, K. Shah
Different platforms of information data semantics are affected by Fake news in the recent years. Due to the inherent writing style and propagation speed of such false information, it has been difficult to pinpoint them from the true ones. The related work in the field makes use of various supervised as well as unsupervised machine-learning algorithms to classify and detect fake news. This paper provides an in-depth overview of the algorithms that are being used for detection. The paper also provides an analysis of notable algorithms on two datasets: Source based Fake News classification and Fake and Real News dataset. The results show that supervised algorithms with proper embedding and vectorizer models can provide great accuracies. The experimentation output shows the effectiveness of the proposed architecture.
{"title":"Real or Fake: An intrinsic analysis using supervised machine learning algorithms","authors":"Ameyaa Biwalkar, Ashwini Rao, K. Shah","doi":"10.1109/I-SMAC52330.2021.9640675","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640675","url":null,"abstract":"Different platforms of information data semantics are affected by Fake news in the recent years. Due to the inherent writing style and propagation speed of such false information, it has been difficult to pinpoint them from the true ones. The related work in the field makes use of various supervised as well as unsupervised machine-learning algorithms to classify and detect fake news. This paper provides an in-depth overview of the algorithms that are being used for detection. The paper also provides an analysis of notable algorithms on two datasets: Source based Fake News classification and Fake and Real News dataset. The results show that supervised algorithms with proper embedding and vectorizer models can provide great accuracies. The experimentation output shows the effectiveness of the proposed architecture.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123535390","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9641058
D. S. Vijayan, S. Arvindan, V. Gokulnath, Kaarthik Manoharan
Internet of things (IoT) plays a vital role in present days in developing a sustainable environment. Due to overpopulation, which increases the pressure of using the vehicle on the road, IoT is the best technology to use resources and space effectively. IoT is friendly to the environment, energy efficiency, and public services. This proposed review article provides insight into the application of IoT in smart cities exclusively for traffic requirements. The article also discusses sensor technologies adopted for IoT applications. This paper provides valuable data to implement IoT in smart cities to enhance the technology development in the country.
{"title":"Applications of IoT in Smart Cities and Highways – A Review","authors":"D. S. Vijayan, S. Arvindan, V. Gokulnath, Kaarthik Manoharan","doi":"10.1109/I-SMAC52330.2021.9641058","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9641058","url":null,"abstract":"Internet of things (IoT) plays a vital role in present days in developing a sustainable environment. Due to overpopulation, which increases the pressure of using the vehicle on the road, IoT is the best technology to use resources and space effectively. IoT is friendly to the environment, energy efficiency, and public services. This proposed review article provides insight into the application of IoT in smart cities exclusively for traffic requirements. The article also discusses sensor technologies adopted for IoT applications. This paper provides valuable data to implement IoT in smart cities to enhance the technology development in the country.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121770192","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640695
Suhui Li
In recent years, the continuous development of data mining technology has penetrated into the real estate industry. Due to the accumulation of various types of data and information, it gradually forms a real estate data ocean. Data mining technology is the process of digging out unknown but useful knowledge and information for each of our decisions from a large amount of information. This will provide powerful technical support for real estate price prediction. Based on the data mining algorithm, this paper carries out the evolutionary optimization of real estate pricing, and studies the influence of different factors on real estate pricing.
{"title":"Research on Evolutionary Optimization Algorithm of Real Estate Pricing Based on Data Mining","authors":"Suhui Li","doi":"10.1109/I-SMAC52330.2021.9640695","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640695","url":null,"abstract":"In recent years, the continuous development of data mining technology has penetrated into the real estate industry. Due to the accumulation of various types of data and information, it gradually forms a real estate data ocean. Data mining technology is the process of digging out unknown but useful knowledge and information for each of our decisions from a large amount of information. This will provide powerful technical support for real estate price prediction. Based on the data mining algorithm, this paper carries out the evolutionary optimization of real estate pricing, and studies the influence of different factors on real estate pricing.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122712735","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9641035
M. J. Kumar, B. Rao, N. Sai, S. S. Kumar
WSN is a large-scale ad hoc network with the property of sufficient accessibility, including the all extents of correspondence applications, similar to medical care, home computerization, far off perceptions, snags recognition, and so forth WSN comprises of gigantic measure of small actuators, situated on better places which have minimal expense and simple establishment with limitations of restricted energy assets, computational limit and memory size. WSN is presented to numerous security dangers because of its restrictions, broadcast nature and unattended climate. Numerous distributions have proposed various IDS plans to effectively safeguard WSNs against security dangers. To conquer this issue, the proposed paper examines distinctive proposed IDS systems and analyzes them to survey the effectiveness from their qualities and shortcomings. In this paper, obstruction affirmation structure is masterminded and executed utilizing game hypothesis and AI to perceive various assaults. Game theory is organized and used to apply the IDS ideally in WSN. The game model is organized by depicting the players and the differentiating frameworks. QRE considered game hypothesis is utilized to pick the systems in ideal manner for the impedance's region. Further, these obstructions are assigned disavowing of association assault, rank assault or express sending assaults utilizing oversaw AI procedure subject as far as possible and rules. Results show that the entirety of the assaults are seen with commendable region rate and the proposed approach gives ideal utilization of IDS
{"title":"Using QRE-based Game Model for better IDS","authors":"M. J. Kumar, B. Rao, N. Sai, S. S. Kumar","doi":"10.1109/I-SMAC52330.2021.9641035","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9641035","url":null,"abstract":"WSN is a large-scale ad hoc network with the property of sufficient accessibility, including the all extents of correspondence applications, similar to medical care, home computerization, far off perceptions, snags recognition, and so forth WSN comprises of gigantic measure of small actuators, situated on better places which have minimal expense and simple establishment with limitations of restricted energy assets, computational limit and memory size. WSN is presented to numerous security dangers because of its restrictions, broadcast nature and unattended climate. Numerous distributions have proposed various IDS plans to effectively safeguard WSNs against security dangers. To conquer this issue, the proposed paper examines distinctive proposed IDS systems and analyzes them to survey the effectiveness from their qualities and shortcomings. In this paper, obstruction affirmation structure is masterminded and executed utilizing game hypothesis and AI to perceive various assaults. Game theory is organized and used to apply the IDS ideally in WSN. The game model is organized by depicting the players and the differentiating frameworks. QRE considered game hypothesis is utilized to pick the systems in ideal manner for the impedance's region. Further, these obstructions are assigned disavowing of association assault, rank assault or express sending assaults utilizing oversaw AI procedure subject as far as possible and rules. Results show that the entirety of the assaults are seen with commendable region rate and the proposed approach gives ideal utilization of IDS","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123986114","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 : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640877
Shengfeng Jiang, Lei Jiang
New infrastructure is an infrastructure based on emerging technology, especially a new generation of information technology. It is the foundation and guarantee for the digital transformation and high-quality development of traditional businesses. It has the characteristics of new technology, new ecology and new power; standardization and intelligence are the promotion of new infrastructure The key to innovation and development is the foundation, guarantee and support for its function; this article studies the design of the standardization and intelligent framework of enterprise artificial intelligence new infrastructure.
{"title":"Enterprise Artificial Intelligence New Infrastructure Standardization and Intelligent Framework Design","authors":"Shengfeng Jiang, Lei Jiang","doi":"10.1109/I-SMAC52330.2021.9640877","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640877","url":null,"abstract":"New infrastructure is an infrastructure based on emerging technology, especially a new generation of information technology. It is the foundation and guarantee for the digital transformation and high-quality development of traditional businesses. It has the characteristics of new technology, new ecology and new power; standardization and intelligence are the promotion of new infrastructure The key to innovation and development is the foundation, guarantee and support for its function; this article studies the design of the standardization and intelligent framework of enterprise artificial intelligence new infrastructure.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124262363","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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