Pub Date : 2021-11-11DOI: 10.1109/I-SMAC52330.2021.9640737
V. A, S. Vanaja, B. Sathyasri, R. S., Ramyaa D, Prem S
Nowadays, automation is the most efficient resource mechanism which is available in day today life in an economical way. In daily circumstances, life is not possible without automotive mechanism. The automotive method adopted in this system would be by displaying the various parameters through an informative system. So, our aim is to develop an informative system to indicate multiple parameters of the automobile resources like fuel, engine temperature, AC voltage in engine, air, battery voltage, wear out temperature, hydrocarbons quantity and machine speed. The proposed system is useful for any users for recognizing the various parameters in a single and compact Liquid Crystal Display. A voice recorder Integrated Circuit has been used in this project to produce warning voice signals during abnormal conditions of resources. This project involves the usage of the latest embedded microcontroller. In case of any abnormal situations some points are set to stir the end user for the itemize specifications as well as for each and every action is -taking place is stipulated with the help of voice output.
{"title":"Future Driver Assistant with Reconfigurable On-Board Diagnostics system","authors":"V. A, S. Vanaja, B. Sathyasri, R. S., Ramyaa D, Prem S","doi":"10.1109/I-SMAC52330.2021.9640737","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640737","url":null,"abstract":"Nowadays, automation is the most efficient resource mechanism which is available in day today life in an economical way. In daily circumstances, life is not possible without automotive mechanism. The automotive method adopted in this system would be by displaying the various parameters through an informative system. So, our aim is to develop an informative system to indicate multiple parameters of the automobile resources like fuel, engine temperature, AC voltage in engine, air, battery voltage, wear out temperature, hydrocarbons quantity and machine speed. The proposed system is useful for any users for recognizing the various parameters in a single and compact Liquid Crystal Display. A voice recorder Integrated Circuit has been used in this project to produce warning voice signals during abnormal conditions of resources. This project involves the usage of the latest embedded microcontroller. In case of any abnormal situations some points are set to stir the end user for the itemize specifications as well as for each and every action is -taking place is stipulated with the help of voice output.","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":"126060181","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-SMAC52330.2021.9640666
Jianhua Li
BIM is a kind of engineering data model which can integrate all kinds of information in the whole process of construction engineering. It is based on three-dimensional digital technology and provides the basis for collaborative work. It can integrate all kinds of information data and set up simulation model by setting parameters to simulate building entity, construction process and operation situation. Based on the secondary development technology of engineering software, this paper studies API development tools. Through the establishment of parametric family library, this paper develops a rapid modeling method for rapid generation of water conservancy and hydropower project model, and finally realizes the construction schedule simulation by using the cooperation of VR tool related software and NavisWorks software.
{"title":"Application of Software Simulation in Guiding Reform of Engineering Project with VR Tools","authors":"Jianhua Li","doi":"10.1109/I-SMAC52330.2021.9640666","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640666","url":null,"abstract":"BIM is a kind of engineering data model which can integrate all kinds of information in the whole process of construction engineering. It is based on three-dimensional digital technology and provides the basis for collaborative work. It can integrate all kinds of information data and set up simulation model by setting parameters to simulate building entity, construction process and operation situation. Based on the secondary development technology of engineering software, this paper studies API development tools. Through the establishment of parametric family library, this paper develops a rapid modeling method for rapid generation of water conservancy and hydropower project model, and finally realizes the construction schedule simulation by using the cooperation of VR tool related software and NavisWorks software.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"21 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":"126828836","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-SMAC52330.2021.9640866
Abhishek A. Madankar, Akhilesh Agrawal, Vedant Yede
When it comes to loved ones, humans strive to keep them fit and healthy at all times. But what if they forget to take their medicine and become ill as a result? Hence, many patients require medication at the health care center, and it is difficult for us to remind each patient to take medicine at a specific time. Traditional way requires lot of human effort to remind the patient to take medicine. But in this digital era, humans make use of machines to do certain works. Pill remainder has a wide range of uses, including use by patients at home, doctors in hospitals, and a variety of other settings. This paper presents a working of advance pill remainder setup, which can remove asymmetry in taking medicine dosages and remind the patient to take medicine at prescribed time and particular number of dosages. In this approach, the users are switching from human memory to automated supervision.
{"title":"IoT based Advance Pill Reminder System for Distinct Patients","authors":"Abhishek A. Madankar, Akhilesh Agrawal, Vedant Yede","doi":"10.1109/I-SMAC52330.2021.9640866","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640866","url":null,"abstract":"When it comes to loved ones, humans strive to keep them fit and healthy at all times. But what if they forget to take their medicine and become ill as a result? Hence, many patients require medication at the health care center, and it is difficult for us to remind each patient to take medicine at a specific time. Traditional way requires lot of human effort to remind the patient to take medicine. But in this digital era, humans make use of machines to do certain works. Pill remainder has a wide range of uses, including use by patients at home, doctors in hospitals, and a variety of other settings. This paper presents a working of advance pill remainder setup, which can remove asymmetry in taking medicine dosages and remind the patient to take medicine at prescribed time and particular number of dosages. In this approach, the users are switching from human memory to automated supervision.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"2 6-7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120929460","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-SMAC52330.2021.9640850
Bhavani M, Shrijeeth S, Rohit M, Sanjeev Krishnan R, Sharveshwaran R
Under the present developments and current situation, the entire globe is changing fast. With the Internet being utilized in every sector, the internet has become a necessary requirement for everyone. With the quick expansion in informal community applications, individuals are utilizing these stages to voice their sentiments as to everyday issues. Assembling and investigating people's reactions toward purchasing an item, public administrations are essential. Sentiment analysis is a common dialogue preparing task that aims to discover the sentiments behind opinions in texts on varying subjects [1]. As of late, analysts in the field of estimation examination have been worried about dissecting suppositions on various subjects, for example, films, business items, and day by day cultural issues. Twitter is a gigantically mainstream microblog on which customers may voice their assessments. Assessment examination of Twitter information is a field that has been given a lot of consideration in the course of the most recent decade and includes taking apart "tweets" and the substance of these articulations. In this paper, a deep learning model has been made with Embedding, CNN and LSTM layers. Then tweets from the web are collected for a particular topic using the Web Scraping technique by Twitter API and the overall sentiment is analyzed and a detailed sentiment report is made for that particular topic.
{"title":"A detailed study on sentimental analysis using Twitter data with an Improved deep learning model","authors":"Bhavani M, Shrijeeth S, Rohit M, Sanjeev Krishnan R, Sharveshwaran R","doi":"10.1109/I-SMAC52330.2021.9640850","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640850","url":null,"abstract":"Under the present developments and current situation, the entire globe is changing fast. With the Internet being utilized in every sector, the internet has become a necessary requirement for everyone. With the quick expansion in informal community applications, individuals are utilizing these stages to voice their sentiments as to everyday issues. Assembling and investigating people's reactions toward purchasing an item, public administrations are essential. Sentiment analysis is a common dialogue preparing task that aims to discover the sentiments behind opinions in texts on varying subjects [1]. As of late, analysts in the field of estimation examination have been worried about dissecting suppositions on various subjects, for example, films, business items, and day by day cultural issues. Twitter is a gigantically mainstream microblog on which customers may voice their assessments. Assessment examination of Twitter information is a field that has been given a lot of consideration in the course of the most recent decade and includes taking apart \"tweets\" and the substance of these articulations. In this paper, a deep learning model has been made with Embedding, CNN and LSTM layers. Then tweets from the web are collected for a particular topic using the Web Scraping technique by Twitter API and the overall sentiment is analyzed and a detailed sentiment report is made for that particular topic.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"20 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":"127815370","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-SMAC52330.2021.9640974
V. Annapurna, S. Nagaraja Rao, M. N. Giriprasad
Steganography is necessary to encrypt data efficiently between different organizations. Steganography can have significant use in transmitting secret data through videos. However, this is susceptible to third party attacks such as video change, copyright change, security update changes etc. Numerous cryptographic algorithms have been proposed to be incorporated into data hiding techniques. As the number of sensitive data required is large, these models require powerful computer memory and high processing cycles to process. In that case, these cryptographic models could not be applied to large video data for integrity computation and encryption. In this paper, different video steganography approaches and their limitations are studied on the video databases.
{"title":"A Survey of different video steganography approaches against man-in-the middle attacks","authors":"V. Annapurna, S. Nagaraja Rao, M. N. Giriprasad","doi":"10.1109/I-SMAC52330.2021.9640974","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640974","url":null,"abstract":"Steganography is necessary to encrypt data efficiently between different organizations. Steganography can have significant use in transmitting secret data through videos. However, this is susceptible to third party attacks such as video change, copyright change, security update changes etc. Numerous cryptographic algorithms have been proposed to be incorporated into data hiding techniques. As the number of sensitive data required is large, these models require powerful computer memory and high processing cycles to process. In that case, these cryptographic models could not be applied to large video data for integrity computation and encryption. In this paper, different video steganography approaches and their limitations are studied on the video databases.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"23 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":"132765773","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-SMAC52330.2021.9640735
Qinmin Ma
With the rapid development of computer network technology, more and more units and individuals share abundant data resources, and information security has become the primary problem to be solved by network information systems. The database management system comes with a basic security technology strategy, which can solve common database security requirements. However, for some special data security applications, the security technology strategy of the database itself cannot meet the requirements, which requires data encryption. Processing data encryption is the core content of information security research, and database encryption is an important means to improve database security. This paper studies the design of embedded network database system based on BS structure.
{"title":"Embedded Network Database Encryption System Optimization Considering the B/S Structure and Software Optimization","authors":"Qinmin Ma","doi":"10.1109/I-SMAC52330.2021.9640735","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640735","url":null,"abstract":"With the rapid development of computer network technology, more and more units and individuals share abundant data resources, and information security has become the primary problem to be solved by network information systems. The database management system comes with a basic security technology strategy, which can solve common database security requirements. However, for some special data security applications, the security technology strategy of the database itself cannot meet the requirements, which requires data encryption. Processing data encryption is the core content of information security research, and database encryption is an important means to improve database security. This paper studies the design of embedded network database system based on BS structure.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"56 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":"133240044","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-SMAC52330.2021.9640736
Ramesh Nuthakki, Payel Masanta, Yukta T N
Speech enhancement is the process of treating noisy speech signals so as to improve human perception as well as improve system understanding of the signal. For speech signals with medium or high signal to noise ratio (SNR), the aim is to produce subjectively pragmatic signal, and for signals having low SNR the aim is to reduce the noise while still maintaining the intelligibility. Many noise reduction algorithms improve overall speech quality but little progress has been made to improve the overall speech intelligibility. This paper proposes a deep convolutional neural network (DCNN) speech enhancement method by enhancing loss function such as extended short time objective ineligibility (ESTOI) and mean square error (MSE). These loss functions are improved using Harris Hawks Optimization (HHO). The enhanced speech signal is acquired by separating the clean speech signal from the noisy speech signal. By using various predictive measure of objective speech intelligibility like short time objective intelligibility, source to artefact ratio (SAR), coherence speech intelligibility index (CSII) and source to distortion ratio (SDR), the efficacy of speech enhancement is calculated. The quality of the enhanced speech signal is assessed using the quality measure such as speech distortion (SD) and perceptual evaluation of speech quality (PESQ).
{"title":"Speech Enhancement based on Deep Convolutional Neural Network","authors":"Ramesh Nuthakki, Payel Masanta, Yukta T N","doi":"10.1109/I-SMAC52330.2021.9640736","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640736","url":null,"abstract":"Speech enhancement is the process of treating noisy speech signals so as to improve human perception as well as improve system understanding of the signal. For speech signals with medium or high signal to noise ratio (SNR), the aim is to produce subjectively pragmatic signal, and for signals having low SNR the aim is to reduce the noise while still maintaining the intelligibility. Many noise reduction algorithms improve overall speech quality but little progress has been made to improve the overall speech intelligibility. This paper proposes a deep convolutional neural network (DCNN) speech enhancement method by enhancing loss function such as extended short time objective ineligibility (ESTOI) and mean square error (MSE). These loss functions are improved using Harris Hawks Optimization (HHO). The enhanced speech signal is acquired by separating the clean speech signal from the noisy speech signal. By using various predictive measure of objective speech intelligibility like short time objective intelligibility, source to artefact ratio (SAR), coherence speech intelligibility index (CSII) and source to distortion ratio (SDR), the efficacy of speech enhancement is calculated. The quality of the enhanced speech signal is assessed using the quality measure such as speech distortion (SD) and perceptual evaluation of speech quality (PESQ).","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"23 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":"134252869","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-SMAC52330.2021.9640949
Zakir Hossain, Md. Mahmudur Rahman Sourov, Musharrat Khan, Parves Rahman
At present network intrusion is regarded as a great threat in network usage and communication. Network intrusion detection system detects and prevents anomalous activities or attacks in networks. Many classifiers are used to detect network attacks. In this paper, we have evaluated the performance of four popular classifiers, namely, Decision Tree, Support Vector Machine, Random Forest and Naïve Bayes on UNSW-NB15 dataset using Python language along with its Pandas and SKlearn libraries. We have used the complete UNSW-NB15 dataset with 43 features. Experimental results have shown improvement of accuracy for Random Forest, Decision Tree and Naïve Bayes over previously reported results produced by Apache Spark and its MLlib.
{"title":"Network Intrusion Detection using Machine Learning Approaches","authors":"Zakir Hossain, Md. Mahmudur Rahman Sourov, Musharrat Khan, Parves Rahman","doi":"10.1109/I-SMAC52330.2021.9640949","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640949","url":null,"abstract":"At present network intrusion is regarded as a great threat in network usage and communication. Network intrusion detection system detects and prevents anomalous activities or attacks in networks. Many classifiers are used to detect network attacks. In this paper, we have evaluated the performance of four popular classifiers, namely, Decision Tree, Support Vector Machine, Random Forest and Naïve Bayes on UNSW-NB15 dataset using Python language along with its Pandas and SKlearn libraries. We have used the complete UNSW-NB15 dataset with 43 features. Experimental results have shown improvement of accuracy for Random Forest, Decision Tree and Naïve Bayes over previously reported results produced by Apache Spark and its MLlib.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"21 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":"134571525","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-SMAC52330.2021.9640784
Ang Li, Chen Zhang, Lei Li
Communication and information transmission can be seen everywhere in people's lives, and its safety is extremely important. In order to further improve the security of data transmission in communication, in addition to adopting traditional source encryption codes, it is also very necessary to increase channel encryption measures. This thesis focuses on channel encryption, introduces and analyzes the encryption algorithm for long-distance data transmission in the Internet of Things based on channel nonlinear transformation. At the same time, in order to verify the feasibility, reliability and confidentiality of the above-mentioned channel encryption method, a verification communication system was designed.
{"title":"An Encryption Algorithm for Long-Distance Data Transmission in the Internet of Things Based on Channel Nonlinear Transformation","authors":"Ang Li, Chen Zhang, Lei Li","doi":"10.1109/I-SMAC52330.2021.9640784","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640784","url":null,"abstract":"Communication and information transmission can be seen everywhere in people's lives, and its safety is extremely important. In order to further improve the security of data transmission in communication, in addition to adopting traditional source encryption codes, it is also very necessary to increase channel encryption measures. This thesis focuses on channel encryption, introduces and analyzes the encryption algorithm for long-distance data transmission in the Internet of Things based on channel nonlinear transformation. At the same time, in order to verify the feasibility, reliability and confidentiality of the above-mentioned channel encryption method, a verification communication system was designed.","PeriodicalId":178783,"journal":{"name":"2021 Fifth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"4 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":"115379263","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-SMAC52330.2021.9640942
Shuai Shen
With the progress of the country and the development of Internet information technology, my country's e-commerce has achieved leapfrog development. On the one hand, it has strengthened the driving force of my country's economic development and promoted the sound and rapid development of the national economy. The entire training center can implement a series of business operation skills training from uploading, selling, outgoing, after-sales and related logistics of e-commerce products, and at the same time can help individuals start their own businesses and promote public employment. This paper studies the intelligent system construction of e-commerce training base based on logistics path visualization technology, and further analyzes the importance of e-commerce training system.
{"title":"Intelligent Construction System of E-Commerce Training Base Based on Logistics Path Visualization","authors":"Shuai Shen","doi":"10.1109/I-SMAC52330.2021.9640942","DOIUrl":"https://doi.org/10.1109/I-SMAC52330.2021.9640942","url":null,"abstract":"With the progress of the country and the development of Internet information technology, my country's e-commerce has achieved leapfrog development. On the one hand, it has strengthened the driving force of my country's economic development and promoted the sound and rapid development of the national economy. The entire training center can implement a series of business operation skills training from uploading, selling, outgoing, after-sales and related logistics of e-commerce products, and at the same time can help individuals start their own businesses and promote public employment. This paper studies the intelligent system construction of e-commerce training base based on logistics path visualization technology, and further analyzes the importance of e-commerce training system.","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":"114221048","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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