Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications

Sie sind hier: Homepage > Suche

Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications

Chen, Long / Li, Yuchen / Silamu, Wushour / Li, Qingquan / Ge, Shirong / Wang, Fei-Yue

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.

Zugriff

Zugriff prüfen

Verfügbarkeit in meiner Bibliothek prüfen

Bestellung bei Subito €

Exportieren, teilen und zitieren

Dokumentinformationen

Titel :

Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications

Beteiligte:

Chen, Long (Autor:in) / Li, Yuchen (Autor:in) / Silamu, Wushour (Autor:in) / Li, Qingquan (Autor:in) / Ge, Shirong (Autor:in) / Wang, Fei-Yue (Autor:in)

Erschienen in:

IEEE Transactions on Intelligent Vehicles ; 9 , 3 ; 4383-4393

Erscheinungsdatum :

2024-03-01

Format / Umfang :

5032885 byte

ISSN :

2379-8904 , 2379-8858

DOI :

https://doi.org/10.1109/TIV.2024.3365997

Medientyp :

Aufsatz (Zeitschrift)