Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00053
Runhui Zhao, Sijing Wang, Hong Wen
With the wide use of UAV clusters, malicious attacks against UAV nodes are becoming more and more frequent. Aiming at the problem of malicious node detection in large-scale UAV clusters, this paper proposes a malicious node detection scheme based on community division. Firstly, the Leiden community discovery algorithm divides the flight cluster into multiple communities. Then, this paper presents a combined node importance evaluation algorithm using UAV Communication topology and control topology to evaluate the importance of cluster nodes. Finally, this paper proposes a method to select community leader nodes by using the importance, trust degree and residual power of UAV community nodes.
{"title":"A Scheme for Detecting Malicious Nodes in UAV Clusters Based on Community Division","authors":"Runhui Zhao, Sijing Wang, Hong Wen","doi":"10.1109/ICNISC57059.2022.00053","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00053","url":null,"abstract":"With the wide use of UAV clusters, malicious attacks against UAV nodes are becoming more and more frequent. Aiming at the problem of malicious node detection in large-scale UAV clusters, this paper proposes a malicious node detection scheme based on community division. Firstly, the Leiden community discovery algorithm divides the flight cluster into multiple communities. Then, this paper presents a combined node importance evaluation algorithm using UAV Communication topology and control topology to evaluate the importance of cluster nodes. Finally, this paper proposes a method to select community leader nodes by using the importance, trust degree and residual power of UAV community nodes.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114263610","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 : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00009
Jingxian Wang, Ziao Quan, Zheming Liu, Jing Zhang
Faced with the requirement of coverage extensions in 6G network, this paper first analyzes the research status of international standardization organizations and related alliances on 6G technology and satellite-ground integrated network. Then, a satellite-ground integrated network architecture is proposed, which is divided into physical domain and logical domain. In the physical domain, the integration of multi-orbit space-based network and ground-based network is considered to meet the user's demand for casual access under the constraints of platform resources. In the logical domain, the separation of the user plane, control plane, management plane, and orchestration plane is considered to support the modular and iterative evolution of the network architecture. Finally, the key enabling technologies are discussed, hoping to provide useful reference for the development of satellite-ground integrated network in 6G.
{"title":"Satellite-Ground Integrated Network Architecture and Key Enabling Technologies for 6G","authors":"Jingxian Wang, Ziao Quan, Zheming Liu, Jing Zhang","doi":"10.1109/ICNISC57059.2022.00009","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00009","url":null,"abstract":"Faced with the requirement of coverage extensions in 6G network, this paper first analyzes the research status of international standardization organizations and related alliances on 6G technology and satellite-ground integrated network. Then, a satellite-ground integrated network architecture is proposed, which is divided into physical domain and logical domain. In the physical domain, the integration of multi-orbit space-based network and ground-based network is considered to meet the user's demand for casual access under the constraints of platform resources. In the logical domain, the separation of the user plane, control plane, management plane, and orchestration plane is considered to support the modular and iterative evolution of the network architecture. Finally, the key enabling technologies are discussed, hoping to provide useful reference for the development of satellite-ground integrated network in 6G.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131221770","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 : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00171
Cuili Yao, Lin Feng, Yuqiu Kong, Lin Xiao, Tao Chen
In recent years, RGB-D salient object detection (SOD) has attracted increased attention and has been widely employed in various computer vision applications. Fully convolutional networks dominate many RGB-D SOD tasks and have already achieved outstanding results. However, solving the cross-modality fusion of low-quality depth and RGB cues remains challenging. We present TranSal, an innovative network, depth-guided transformer for RGB-D SOD, based on the Transformer's fantastic performance in image recognition and segmentation. A dual-branch U-Net architecture is used in the proposed model. To begin, it uses ResNet-50 to extract multi-level RGB and depth features. Second, it employs Transformer layers to represent image sequentiality. Finally, the representation is projected into spatial order, and the multi-scale cross-modality characteristics are fused to generate an accurate saliency map using a depth-guided fusion subnetwork. TranSal can successfully mitigate the negative impacts of low-quality depth information and create a saliency map with clear contours and accurate semantics compared to previous models. Experiments and analyses on five large-scale benchmarks verify that TranSal achieves satisfactory performance compared to the recent state-of-the-art methods.
{"title":"TranSal: Depth-guided Transformer for RGB-D Salient Object Detection","authors":"Cuili Yao, Lin Feng, Yuqiu Kong, Lin Xiao, Tao Chen","doi":"10.1109/ICNISC57059.2022.00171","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00171","url":null,"abstract":"In recent years, RGB-D salient object detection (SOD) has attracted increased attention and has been widely employed in various computer vision applications. Fully convolutional networks dominate many RGB-D SOD tasks and have already achieved outstanding results. However, solving the cross-modality fusion of low-quality depth and RGB cues remains challenging. We present TranSal, an innovative network, depth-guided transformer for RGB-D SOD, based on the Transformer's fantastic performance in image recognition and segmentation. A dual-branch U-Net architecture is used in the proposed model. To begin, it uses ResNet-50 to extract multi-level RGB and depth features. Second, it employs Transformer layers to represent image sequentiality. Finally, the representation is projected into spatial order, and the multi-scale cross-modality characteristics are fused to generate an accurate saliency map using a depth-guided fusion subnetwork. TranSal can successfully mitigate the negative impacts of low-quality depth information and create a saliency map with clear contours and accurate semantics compared to previous models. Experiments and analyses on five large-scale benchmarks verify that TranSal achieves satisfactory performance compared to the recent state-of-the-art methods.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130189998","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 : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00136
B. Fang, Haozhi Li, Shi Zhu, Pohuang Jiang
High-speed Power Line Carrier (HPLC) and micropower wireless can coordinate and supply each other by taking advantages of each channel, so in this paper, a distributed relay selection and bandwidth allocation method based on interference level is proposed, which can adaptively establish multi-hop transmission network by dynamically adjusting the transmission relays and bandwidth resource allocation based on channel conditions. This method can significantly improve the data acquisition rate of the concentrator by fully multiplexing the bandwidth through controlling the mutual interference.
{"title":"A Distributed Relay Selection and Bandwidth Allocation Method Based on Interference Level for HPLC and Micro-power Wireless Integration","authors":"B. Fang, Haozhi Li, Shi Zhu, Pohuang Jiang","doi":"10.1109/ICNISC57059.2022.00136","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00136","url":null,"abstract":"High-speed Power Line Carrier (HPLC) and micropower wireless can coordinate and supply each other by taking advantages of each channel, so in this paper, a distributed relay selection and bandwidth allocation method based on interference level is proposed, which can adaptively establish multi-hop transmission network by dynamically adjusting the transmission relays and bandwidth resource allocation based on channel conditions. This method can significantly improve the data acquisition rate of the concentrator by fully multiplexing the bandwidth through controlling the mutual interference.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132634768","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 : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00141
Heng-I Chen, Shikun Zhou, Lei Shi, Y. Yue, Ninggang An
Fault diagnosis methods based on deep learning have a strong ability to distinguish faults with unknown mechanisms in the field of mechanical fault diagnosis. However, when the noise interference is strong, the accuracy of the model will decrease to a certain extent. This paper proposes an anti-noise fault diagnosis model named APR-CNN. The model is designed based on a two-dimensional convolutional neural network, which uses the wavelet time-frequency images as input. According to the characteristic of the periodic transformation of the wavelet time-frequency image of the bearing signals, average pooling on rows method is used to compress the time domain information and extract the features effectively. Compared with classical methods on the open-source bearing fault dataset, experiments show that the APR-CNN model can still have an accuracy rate of 98% even in a noisy environment with SNR of −10, which is at least 30% higher than other methods.
{"title":"Anti-noise Fault Diagnosis Model Based on Convolutional Neural Network","authors":"Heng-I Chen, Shikun Zhou, Lei Shi, Y. Yue, Ninggang An","doi":"10.1109/ICNISC57059.2022.00141","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00141","url":null,"abstract":"Fault diagnosis methods based on deep learning have a strong ability to distinguish faults with unknown mechanisms in the field of mechanical fault diagnosis. However, when the noise interference is strong, the accuracy of the model will decrease to a certain extent. This paper proposes an anti-noise fault diagnosis model named APR-CNN. The model is designed based on a two-dimensional convolutional neural network, which uses the wavelet time-frequency images as input. According to the characteristic of the periodic transformation of the wavelet time-frequency image of the bearing signals, average pooling on rows method is used to compress the time domain information and extract the features effectively. Compared with classical methods on the open-source bearing fault dataset, experiments show that the APR-CNN model can still have an accuracy rate of 98% even in a noisy environment with SNR of −10, which is at least 30% higher than other methods.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134311927","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 : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00045
Hong Zhang
In 2016, there were amount of news of new technological breakthroughs in the field of machine translation at home and abroad. Whether machine translation can replace human translation has become one of the hot topics in academic circles. This paper argues that in specific restricted language translation, machines translation has provided people with convenient and efficient services, but on the whole, the translation quality of machine translation is not as good as human translation and can not replace human translation in a short time. Translation quality assessment is an important sub task in the field of machine translation. At present, translation quality assessment has a good performance in Chinese-English, English-German machine translation, and the technology is relatively mature. However, applying the model to the machine translation of Haihunhou publicity text still has many problems. Compared with the parallel corpus of manual translation, the differences of machine translation in terms translation, vocabulary discrimination, syntactic analysis and symbol translation in Haihunhou publicity text provide a corpus analysis basis for improving the machine translation system.
{"title":"Comparison between Human Translation and Machine Translation in Translating the Publicity Text of Haihunhou Museum","authors":"Hong Zhang","doi":"10.1109/ICNISC57059.2022.00045","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00045","url":null,"abstract":"In 2016, there were amount of news of new technological breakthroughs in the field of machine translation at home and abroad. Whether machine translation can replace human translation has become one of the hot topics in academic circles. This paper argues that in specific restricted language translation, machines translation has provided people with convenient and efficient services, but on the whole, the translation quality of machine translation is not as good as human translation and can not replace human translation in a short time. Translation quality assessment is an important sub task in the field of machine translation. At present, translation quality assessment has a good performance in Chinese-English, English-German machine translation, and the technology is relatively mature. However, applying the model to the machine translation of Haihunhou publicity text still has many problems. Compared with the parallel corpus of manual translation, the differences of machine translation in terms translation, vocabulary discrimination, syntactic analysis and symbol translation in Haihunhou publicity text provide a corpus analysis basis for improving the machine translation system.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"436 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132558935","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}
Based on the application background of PROTOS70 cigarette machine widely used in the tobacco industry, this paper designs and implements a high-precision online cigarette sampling device, which can automatically sample the cigarettes produced by the cigarette machine online and send them to the C2 cigarette quality detector. The results show that the system can realize the function of cigarette non-destructive sampling, improve the degree of cigarette detection automation, prevent the occurrence of batch quality accidents, and realize the intellectualization of cigarette quality control.
{"title":"Design of High Precision Cigarette Online Sampling Device","authors":"H. Lu, Shunkai Sun, Sixiao Chen, Weilin Cao, Zhoufan Huang, Meng Shu, Yingxiao Chi, Liang Chen","doi":"10.1109/ICNISC57059.2022.00177","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00177","url":null,"abstract":"Based on the application background of PROTOS70 cigarette machine widely used in the tobacco industry, this paper designs and implements a high-precision online cigarette sampling device, which can automatically sample the cigarettes produced by the cigarette machine online and send them to the C2 cigarette quality detector. The results show that the system can realize the function of cigarette non-destructive sampling, improve the degree of cigarette detection automation, prevent the occurrence of batch quality accidents, and realize the intellectualization of cigarette quality control.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131888700","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 : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00195
Lu Gao, Lianjia Zhao, Fanmiao Kong, Xiaolin Zhang
Wind power is an important source of electricity for the national grid. The unstable characteristics of wind make scheduling and decision-making problems for power companies. Therefore, it is necessary to improve the accuracy of predicted wind power. To solve this problem, this paper adopts the particle swarm optimization algorithm (PSO) to optimize the GRU neural network method, and selects the optimal combination of GRU hyperparameters through PSO to determine the most suitable network topology. The experimental experiment in this paper uses the measured power data of a wind farm in Inner Mongolia as the data set. And use root mean square error and mean absolute error as evaluation criteria. The experimental results show that the algorithm proposed in this paper achieves better experimental results in power prediction, and achieves higher prediction accuracy compared with BPNN, SVR and other models. It proves that the model can achieve good results in wind power prediction. It has practical application value.
{"title":"Research Method of Ultra-short-term Wind Power Prediction Based on PSO-GRU Prediction","authors":"Lu Gao, Lianjia Zhao, Fanmiao Kong, Xiaolin Zhang","doi":"10.1109/ICNISC57059.2022.00195","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00195","url":null,"abstract":"Wind power is an important source of electricity for the national grid. The unstable characteristics of wind make scheduling and decision-making problems for power companies. Therefore, it is necessary to improve the accuracy of predicted wind power. To solve this problem, this paper adopts the particle swarm optimization algorithm (PSO) to optimize the GRU neural network method, and selects the optimal combination of GRU hyperparameters through PSO to determine the most suitable network topology. The experimental experiment in this paper uses the measured power data of a wind farm in Inner Mongolia as the data set. And use root mean square error and mean absolute error as evaluation criteria. The experimental results show that the algorithm proposed in this paper achieves better experimental results in power prediction, and achieves higher prediction accuracy compared with BPNN, SVR and other models. It proves that the model can achieve good results in wind power prediction. It has practical application value.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133760267","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 : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00067
Jun Peng, Xiaoyu Jia
Purpose: To analyze the current research on the cultivation of advertising creative talents in colleges and universities in the era of “artificial intelligence+”. Approach: Discuss the reform and significance of the current training of advertising creative talents based on “artificial intelligence +” from the aspects of education methods and influence of artificial intelligence for advertising creative talents in colleges and universities, and the path of social-oriented innovation model. Results: Artificial intelligence technology has led to the emergence of new communication methods for advertising, and the demands for advertising creative talents have begun to shift to digital creativity and technological creativity, prompting colleges and universities to take a new look at the education of advertising creative talents. Conclusion: With the development of Internet and artificial intelligence, the cultivation of advertising creative talents in colleges and universities is moving from the traditional mode to the “artificial intelligence +” technology education mode. In the context of “AI+”, we should integrate different disciplines to stimulate creativity; deepen the university-enterprise-industry collaborative education; promote the “course-competition-integrated” education model; improve the digital literacy of advertising creative talents; and layout the AI education system. This study provides some innovative ideas and reference for the current advertising creative talents training mode in colleges and universities.
{"title":"Research on the Training Mode of Advertising Creative Talents in Colleges and Universities from the Perspective of “Artificial Intelligence+”","authors":"Jun Peng, Xiaoyu Jia","doi":"10.1109/ICNISC57059.2022.00067","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00067","url":null,"abstract":"Purpose: To analyze the current research on the cultivation of advertising creative talents in colleges and universities in the era of “artificial intelligence+”. Approach: Discuss the reform and significance of the current training of advertising creative talents based on “artificial intelligence +” from the aspects of education methods and influence of artificial intelligence for advertising creative talents in colleges and universities, and the path of social-oriented innovation model. Results: Artificial intelligence technology has led to the emergence of new communication methods for advertising, and the demands for advertising creative talents have begun to shift to digital creativity and technological creativity, prompting colleges and universities to take a new look at the education of advertising creative talents. Conclusion: With the development of Internet and artificial intelligence, the cultivation of advertising creative talents in colleges and universities is moving from the traditional mode to the “artificial intelligence +” technology education mode. In the context of “AI+”, we should integrate different disciplines to stimulate creativity; deepen the university-enterprise-industry collaborative education; promote the “course-competition-integrated” education model; improve the digital literacy of advertising creative talents; and layout the AI education system. This study provides some innovative ideas and reference for the current advertising creative talents training mode in colleges and universities.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132239952","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 : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00187
Song Tang, Zhiqiang Wang, Suli Ge
With the development of information technology, blockchain technology has been increasingly used in all walks of life due to its features of decentralization, openness and transparency, and immutability. In view of the lack of a traceability model that covers the production and circulation links of the entire industrial chain and effectively realizes the multi-source aggregation of traceability data, the lack of data integration and applicability, the lack of data support and decision analysis, etc. This paper proposes to build a quality improvement platform for the agricultural industry chain based on blockchain technology. Using the technical characteristics of blockchain technology such as secure encryption, non-tampering, and traceability, it can increase the end-to-end data transparency of the supply chain, reduce transaction costs, and improve the supply chain. Endorsement of trust between upstream and downstream. Integrate blockchain technology into the agricultural product traceability platform to improve the authenticity of system data, and carry out systematic and informatized upgrades and transformations for production, transaction, procurement, logistics, distribution and other links, so as to achieve end-to-end digital and intelligent transformation.
{"title":"Application Research on Quality Improvement of Agricultural Industry Chain Based on Blockchain Technology","authors":"Song Tang, Zhiqiang Wang, Suli Ge","doi":"10.1109/ICNISC57059.2022.00187","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00187","url":null,"abstract":"With the development of information technology, blockchain technology has been increasingly used in all walks of life due to its features of decentralization, openness and transparency, and immutability. In view of the lack of a traceability model that covers the production and circulation links of the entire industrial chain and effectively realizes the multi-source aggregation of traceability data, the lack of data integration and applicability, the lack of data support and decision analysis, etc. This paper proposes to build a quality improvement platform for the agricultural industry chain based on blockchain technology. Using the technical characteristics of blockchain technology such as secure encryption, non-tampering, and traceability, it can increase the end-to-end data transparency of the supply chain, reduce transaction costs, and improve the supply chain. Endorsement of trust between upstream and downstream. Integrate blockchain technology into the agricultural product traceability platform to improve the authenticity of system data, and carry out systematic and informatized upgrades and transformations for production, transaction, procurement, logistics, distribution and other links, so as to achieve end-to-end digital and intelligent transformation.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133374402","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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