Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications
Chen, Long1,2,3,4; Li, Yuchen3,5,6; Silamu, Wushour7; Li, Qingquan8; Ge, Shirong9; Wang, Fei-Yue1,2
发表期刊IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
ISSN2379-8858
2024-03-01
卷号9期号:3页码:4383-4393
通讯作者Wang, Fei-Yue(feiyue@ieee.org)
摘要The increasing importance of mineral resources in contemporary society is becoming more prominent, playing an indispensable and crucial role in the global economy. These resources not only provide essential raw materials for the global economic system but also play an irreplaceable role in supporting the development of modern industry, technology, and infrastructure. With the rapid development of intelligent technologies such as Industry 5.0 and advanced Large Language Models (LLMs), the mining industry is facing unprecedented opportunities and challenges. The development of smart mines has become a crucial direction for industry progress. This article aims to explore the strategic requirements for the development of smart mines by combining advanced products or technologies such as Chat-GPT (one of the successful applications of LLMs), digital twins, and scenario engineering. We propose a comprehensive architecture consisting of three different levels, the mining industrial Internet of Things (IoT) platform, mining operating systems, and foundation models. The systems and models empower the mining equipment for transportation. The architecture delivers a comprehensive solution that aligns perfectly with the demands of Industry 5.0. The application and validation outcomes of this intelligent solution showcase a noteworthy enhancement in mining efficiency and a reduction in safety risks, thereby laying a sturdy groundwork for the advent of Mining 5.0.
关键词Digital twins Fifth Industrial Revolution Industries Task analysis Production Ontologies Biological system modeling Mining 5.0 smart mining autonomous driving industry 5.0 architectures mining transportation trucks
DOI10.1109/TIV.2024.3365997
关键词[WOS]INTELLIGENT VEHICLES
收录类别SCI
语种英语
资助项目National Key Research and Development Program of China
项目资助者National Key Research and Development Program of China
WOS研究方向Computer Science ; Engineering ; Transportation
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号WOS:001214544700011
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/58415
专题多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者Wang, Fei-Yue
作者单位1.Chinese Acad Sci, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.WAYTOUS Inc, Beijing 100083, Peoples R China
4.Guangdong Lab Artificial Intelligence & Digital Ec, Shenzhen 518107, Peoples R China
5.BNU HKBU United Int Coll, Fac Sci & Technol, Zhuhai 519087, Peoples R China
6.Hong Kong Baptist Univ, Kowloon, Hong Kong 999077, Peoples R China
7.Xinjiang Univ, Sch Informat Sci & Engn, Urumqi 830046, Peoples R China
8.Shenzhen Univ, Sch Architecture & Urban Planning, Shenzhen 518060, Peoples R China
9.China Univ Min & Technol Beijing, Sch Mech Elect & Informat Engn, Beijing 100083, Peoples R China
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Chen, Long,Li, Yuchen,Silamu, Wushour,et al. Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2024,9(3):4383-4393.
APA Chen, Long,Li, Yuchen,Silamu, Wushour,Li, Qingquan,Ge, Shirong,&Wang, Fei-Yue.(2024).Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,9(3),4383-4393.
MLA Chen, Long,et al."Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 9.3(2024):4383-4393.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Chen, Long]的文章
[Li, Yuchen]的文章
[Silamu, Wushour]的文章
百度学术
百度学术中相似的文章
[Chen, Long]的文章
[Li, Yuchen]的文章
[Silamu, Wushour]的文章
必应学术
必应学术中相似的文章
[Chen, Long]的文章
[Li, Yuchen]的文章
[Silamu, Wushour]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。