scholarly journals An Intelligent Supply Chain Information Collaboration Model Based on Internet of Things and Big Data

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 58324-58335 ◽  
Author(s):  
Wuxue Jiang
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Internet Of Things ◽  
Model Based ◽  
Collaboration Model

scholarly journals A Weakly Supervised Academic Search Model Based on Knowledge-Enhanced Feature Representation

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mingying Xu ◽  
Junping Du ◽  
Feifei Kou ◽  
Meiyu Liang ◽  
Xin Xu ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Feature Representation ◽  
Search Model ◽  
Model Based ◽  
Proposed Model ◽  
Cloud Server ◽  
Weakly Supervised ◽  
Internet Of Things Technology ◽  
Academic Search

Internet of Things search has great potential applications with the rapid development of Internet of Things technology. Combining Internet of Things technology and academic search to build academic search framework based on Internet of Things is an effective solution to realize massive academic resource search. Recently, the academic big data has been characterized by a large number of types and spanning many fields. The traditional web search technology is no longer suitable for the search environment of academic big data. Thus, this paper designs academic search framework based on Internet of Things Technology. In order to alleviate the pressure of the cloud server processing massive academic big data, the edge server is introduced to clean and remove the redundancy of the data to form a clean data for further analysis and processing by the cloud server. Edge computing network effectively makes up for the deficiency of cloud computing in the conditions of distributed and high concurrent access, reduces long-distance data transmission, and improves the quality of network user experience. For Academic Search, this paper proposes a novel weakly supervised academic search model based on knowledge-enhanced feature representation. The proposed model can relieve high cost of acquisition of manually labeled data by obtaining a lot of pseudolabeled data and consider word-level interactive matching and sentence-level semantic matching for more accurate matching in the process of academic search. The experimental result on academic datasets demonstrate that the performance of the proposed model is much better than that of the existing methods.

scholarly journals Research on measurement of supply chain finance credit risk based on Internet of Things

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771987400 ◽  
Author(s):  
Waseem Ahmed Abbasi ◽  
Zongrun Wang ◽  
Yanju Zhou ◽  
Shahzad Hassan
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Credit Risk ◽  
Measurement Model ◽  
The Internet ◽  
Financial Model ◽  
Model Based ◽  
Supply Chain Finance ◽  
Credit Risk Measurement ◽  
The Internet Of Things

This article first expounds the concept of supply chain finance and its credit risk, describes the hierarchical structure of the Internet of Things and its key technologies, and combines the unique functions of the Internet of Things technology and the business process of the inventory pledge financing model to design the supply chain financial model based on the Internet of Things. Then it studies the credit risk assessment under the supply chain financial model based on the Internet of Things, and uses the support vector machine algorithm and Logistic regression method to establish a credit risk measurement model considering the subject rating and debt rating. Finally, an example analysis shows that the credit risk measurement model has a high accuracy rate for determining whether small and medium-sized enterprises in the supply chain financial model based on the Internet of Things are trustworthy. This will facilitate the revision and improvement of the existing credit evaluation system and improve the accuracy of measuring the current financial risk of supply chain. This research adopts the Internet of Things to measure financial credit risk in supply chain and provides a reference for the following researches.

scholarly journals Logistics and Supply Chain Engineering: Perspectives on Paperless System for Highway Automatic Tollgate (HAT) through Industry 4.0. in Indonesia

2020 ◽  
Author(s):  
Gatot Suharjanto ◽  
Khristian Edi Nugroho Soebandrija
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Internet Of Things ◽  
Product Design ◽  
Industry 4.0 ◽  
Big Data Analytics ◽  
Future Research ◽  
Internet Of Everything ◽  
Industrial Implementation ◽  
Theoretical Perspectives

This paper elaborates discourse on Highway Automatic Tollgate (HAT) within logistics and supply chain engineering perspectives. The aforementioned HAT and its implementation are complying with the Product Design Engineering’s perspectives within theoretical and industrial implementation through Industry 4.0 in Indonesia. The objective of this paper is to intertwine the theoretical perspectives with industrial implementation. The industrial implementation constitutes the effort to implement paperless system for HAT in order to reduce wasted papers that are necessarily needed by user of this HAT, as transaction proof. The result and discussion of this paper comprise several discussions to be considered. To begin with, the result of this paperless system helps the cleaning service officers to reduce their cleaning duty. Furthermore, the result of this paperless system integrates the concept of industry 4.0 within scope of internet of things (IoT) and internet of everything (IoE). Subsequently, the discussion on this paper refers to the discourse on logistics and supply chain engineering perspectives, to ease the transaction proof involving big data. As a result, it reduces significantly the vehicle traffic and time needed to proceed to transaction in the aforementioned HAT. This paper refers to the research methodology within quantitative approach. As future research, it is indispensable to intertwine both aforementioned theoretical and industrial implementation. Both implementation, as future research, need to be integrated within the Asia Region. Keywords: big data analytics; internet of things; making Indonesia 4.0; paperless mechanism; product design engineering

scholarly journals Supply Chain 4.0 challenges

2020 ◽  
Vol 27 (3) ◽  
Author(s):  
Felipe de Campos Martins ◽  
Alexandre Tadeu Simon ◽  
Renan Stenico de Campos
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Supply Chain ◽  
Internet Of Things ◽  
Literature Review ◽  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Legal Challenges ◽  
New Industry

Abstract: The Supply Chain has undergone major transformations due to the need to implement new Industry 4.0 technologies, such as Internet of Things, Big Data, Cyber-Physical Systems and Cloud Computing. Thanks to these technologies, as well as to their subsystems and components, full integration of the supply chain is becoming possible. However, it is observed that the real impacts of Industry 4.0 technologies, rather positive or negative, are not yet totally clear and identified. This paper aims to identify and present an analysis of the challenges and obstacles that Industry 4.0 technologies may cause in the Supply Chain. For this, the most relevant papers on the topic were selected and analyzed through a systematic literature review. Twenty challenges grouped into four macrogroups were identified: (1) technical challenges, (2) financial, environmental and legal challenges, (3) technological challenges, and (4) sociocultural challenges. It should be noted that these challenges require greater attention and more in-depth studies on the part of the academy to support industry in order to mitigate them and thus allow better use of the available technological resources and optimize the performance of Supply Chain operations.

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