Analysis of risk factors in financial supply chain based on machine learning and IoT technology

2020 ◽  
pp. 1-11
Author(s):  
Sun Hongjin
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Supply Chain ◽  
Internet Of Things ◽  
Learning Algorithm ◽  
The Internet ◽  
Supply Chain Risk ◽  
Financing Model ◽  
Internet Of Things Technology ◽  
The Internet Of Things

The financial supply chain is affected by many factors, so an artificial intelligence model is needed to identify supply chain risk factors. This article combines the actual situation of the financial supply chain, improves the traditional machine learning algorithm, and takes the actual company as an example to build a corresponding risk factor recognition model. From the perspective of optimizing the supply chain financial model, this paper combines the functions of the Internet of Things technology and the characteristics of the supply chain financial inventory pledge financing model to design a new type of inventory pledge financing model. The new model makes up for the defects of the original model through the functions of intelligent identification, visual tracking and cloud computing big data processing of the Internet of Things technology. In addition, this study verifies the performance of the system, uses a large amount of data in Internet finance as an object, and obtains the corresponding results through mathematical statistical analysis. The research results show that the model proposed in this paper has a certain effect on the identification and analysis of financial supply chain risk factors.

scholarly journals Social Media Analytics of the Internet of Things

2021 ◽  
Author(s):  
Jim Scheibmeir ◽  
Yashwant K. Malaiya
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Internet Of Things ◽  
Smart Cities ◽  
The Internet ◽  
Social Media Analytics ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Internet Of Things Technology ◽  
The Internet Of Things

Abstract The Internet of Things technology offers convenience and innovation in areas such as smart homes and smart cities. Internet of Things solutions require careful management of devices and the risk mitigation of potential vulnerabilities within cyber-physical systems. The Internet of Things concept, its implementations, and applications are frequently discussed on social media platforms. This article illuminates the public view of the Internet of Things through a content-based analysis of contemporary conversations occurring on the Twitter platform. Tweets can be analyzed with machine learning methods to converge the volume and variety of conversations into predictive and descriptive models. We have reviewed 684,503 tweets collected in a two-week period. Using supervised and unsupervised machine learning methods, we have identified interconnecting relationships between trending themes and the most mentioned industries. We have identified characteristics of language sentiment which can help to predict popularity within the realm of IoT conversation. We found the healthcare industry as the leading use case industry for IoT implementations. This is not surprising as the current Covid-19 pandemic is driving significant social media discussions. There was an alarming dearth of conversations towards cybersecurity. Only 12% of the tweets relating to the Internet of Things contained any mention of topics such as encryption, vulnerabilities, or risk, among other cybersecurity-related terms.

scholarly journals Application research of perception data fusion system of agricultural product supply chain based on Internet of things

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xu Sun ◽  
Kunliang Shu
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Data Fusion ◽  
Agricultural Products ◽  
Current Status ◽  
Agricultural Product ◽  
The Internet ◽  
Market Demand ◽  
Internet Of Things Technology ◽  
The Internet Of Things

AbstractThere are often agricultural product quality problems in the production and circulation of agricultural products. Therefore, there are more and more people on the agricultural product supply chain based on the Internet of things. This article mainly introduces the research on the perception data fusion of agricultural product supply chain in the context of the Internet of things. This is a simple research result based on the Internet of things technology platform, which analyzes the current status of the product according to market demand. After analysis and comparison, a sensory data fusion model suitable for the supply chain of agricultural products is obtained, and information technology based on the Internet of things is used to transform and optimize the Internet of things in the circulation of agricultural products. The experimental results of this article show that data fusion technology based on the Internet of things can solve and track 69.45% of the problem of unknown sources of agricultural products, improve the supply efficiency of agricultural products by 43%, reduce the health problems of agricultural products by 31.24%, and reduce the prices of agricultural products by 13–20%. Improving logistics efficiency can save 5 million tons of agricultural products.

scholarly journals Intelligent Coordination Distribution of the Whole Supply Chain Based on the Internet of Things

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hongxiu Cui
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Economic Benefits ◽  
Cold Chain ◽  
The Internet ◽  
Key Technologies ◽  
Coordination System ◽  
The Impact ◽  
Internet Of Things Technology ◽  
The Internet Of Things

In this paper, through the intelligent research of the whole process of logistics and distribution with the Internet of Things supply chain, we study how to improve the development of the cold chain, reduce the loss in circulation, improve the social and economic benefits, and carry out intelligent information collection, monitoring, management, and information tracing of the whole cold chain. This paper analyzes and empirically studies the impact of key technologies of the Internet of Things in cold chain coordination from the perspective of building an intelligent cold chain coordination system with the Internet of Things technology. This paper analyzes the current situation of cold chain logistics and the impact that the application of IoT technology will have, explains that IoT technology can improve the intelligence level of the cold chain, and then introduces the application of intelligent cold chain logistics under IoT orientation, combining the process of cold chain logistics with the three-layer architecture of IoT technology. By extracting the key technologies of IoT perception layer, network layer, and intelligence layer, the intelligent cold chain coordination system based on IoT technology is constructed, and then, the correctness of the system is verified, to have some reference and evaluation for the cold chain construction. The system was then verified to have some reference and guidance significance for the construction and evaluation of the cold chain. The results of this paper are more accurate and more efficient.

scholarly journals Social media analytics of the Internet of Things

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Jim A. Scheibmeir ◽  
Yashwant K. Malaiya
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Internet Of Things ◽  
Smart Cities ◽  
The Internet ◽  
Social Media Analytics ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Internet Of Things Technology ◽  
The Internet Of Things

AbstractThe Internet of Things technology offers convenience and innovation in areas such as smart homes and smart cities. Internet of Things solutions require careful management of devices and the risk mitigation of potential vulnerabilities within cyber-physical systems. The Internet of Things concept, its implementations, and applications are frequently discussed on social media platforms. This research illuminates the public view of the Internet of Things through a content-based and network analysis of contemporary conversations occurring on the Twitter platform. Tweets can be analyzed with machine learning methods to converge the volume and variety of conversations into predictive and descriptive models. We have reviewed 684,503 tweets collected in a 2-week period. Using supervised and unsupervised machine learning methods, we have identified trends within the realm of IoT and their interconnecting relationships between the most mentioned industries. We have identified characteristics of language sentiment which can help to predict the popularity of IoT conversation topics. We found the healthcare industry as the leading use case industry for IoT implementations. This is not surprising as the current COVID-19 pandemic is driving significant social media discussions. There was an alarming dearth of conversations towards cybersecurity. Recent breaches and ransomware events denote that organizations should spend more time communicating about risks and mitigations. Only 12% of the tweets relating to the Internet of Things contained any mention of topics such as encryption, vulnerabilities, or risk, among other cybersecurity-related terms. We propose an IoT Cybersecurity Communication Scorecard to help organizations benchmark the density and sentiment of their corporate communications regarding security against their specific industry.

scholarly journals Perception Data Fusion of Agricultural Products Supply Chain Based on Internet of Things

2020 ◽  
Author(s):  
Xu Sun ◽  
Kunliang Shu
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Data Fusion ◽  
Agricultural Products ◽  
Agricultural Product ◽  
The Internet ◽  
Logistics Industry ◽  
The Status ◽  
Internet Of Things Technology ◽  
The Internet Of Things

Abstract With the continuous development of the logistics industry and big data technology, the integration of traditional industries and the Internet of Things has become the trend of the times. However, agricultural product quality problems occur from time to time in multiple links such as the production and circulation of agricultural products. Therefore, the agricultural product supply chain based on the Internet of Things has gradually received attention. The purpose of this paper is to study the application of perception data fusion of agricultural products supply chain based on internet of things. In order to study the application of perception data fusion of agricultural products supply chain based on Internet of things, this paper analyzes the status quo of agricultural products industry traceability platform and extracts other product supply modes based on the Internet of things technology. After analysis and comparison, it comes to the perception data fusion mode suitable for the agricultural product supply chain, and uses the information technology based on the internet of things to carry out the agricultural product circulation process Internet of things transformation and process optimization. The results show that the application of data fusion based on the internet of things can solve 69.45% of the agricultural products whose origins are unknown and cannot be traced, improve the supply efficiency of agricultural products by 43%, reduce the health problems of agricultural products by 31.24%, reduce the prices of agricultural products by 13%-20%, improve the logistics efficiency and save about 5 million tons of agricultural products. Therefore, it is necessary to study the application of agricultural product perception data fusion based on internet of things.

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

Sign in / Sign up

Export Citation Format

Share Document