An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles

Shen, Xuehao; Wu, Yuezhong; Chen, Shuhong; Luo, Xueming; Gu, ed., Ke

doi:10.1155/2021/5231092

Title: An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles

Journal Article · 29 August 2021 · Mobile Information Systems

DOI: https://doi.org/10.1155/2021/5231092 · OSTI ID:1817933

Shen, Xuehao ^[1];

^[1];

^[2]; Luo, Xueming ^[3]; Gu, ed., Ke

College of Railway Transportation, Hunan University of Technology, Zhuzhou 412007, China
School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou 510006, China
Scholl of Computer Science, Hunan University of Technology, Zhuzhou 412007, China

In order to enable Social Internet of Vehicles devices to achieve the purpose of intelligent and autonomous garbage classification in a public environment, while avoiding network congestion caused by a large amount of data accessing the cloud at the same time, it is therefore considered to combine mobile edge computing with Social Internet of Vehicles to give full play to mobile edge computing features of high bandwidth and low latency. At the same time, based on cutting-edge technologies such as deep learning, knowledge graph, and 5G transmission, the paper builds an intelligent garbage sorting system based on edge computing and visual understanding of Social Internet of Vehicles. First of all, for the massive multisource heterogeneous Social Internet of Vehicles big data in the public environment, different item modal data adopts different processing methods, aiming to obtain a visual understanding model. Secondly, using the 5G network, the model is deployed on the edge device and the cloud for cloud-side collaborative management, aiming to avoid the waste of edge node resources, while ensuring the data privacy of the edge node. Finally, the Social Internet of Vehicles devices is used to make intelligent decision-making on the big data of the items. First, the items are judged as garbage, and then the category is judged, and finally the task of grabbing and sorting is realized. The experimental results show that the system proposed in this paper can efficiently process the big data of Social Internet of Vehicles and make valuable intelligent decisions. At the same time, it also has a certain role in promoting the promotion of Social Internet of Vehicles devices.

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Sponsoring Organization:: USDOE Office of Electricity (OE), Advanced Grid Research & Development. Power Systems Engineering Research

OSTI ID:: 1817933

Journal Information:: Mobile Information Systems, Journal Name: Mobile Information Systems Vol. 2021; ISSN 1574-017X

Publisher:: Hindawi Publishing CorporationCopyright Statement

Country of Publication:: Country unknown/Code not available

Language:: English

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