A Hierarchical and Cloud-Integrated Architecture for Industrial Automation and IoT-Based Data Processing
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I1P101Keywords:
Industrial Automation, IoT, Edge Computing, Cloud Computing, Data Processing, Machine Learning, SCADA, Predictive Analytics, Smart Manufacturing, Industry 4.0Abstract
The integration of Industrial Automation (IA) and the Internet of Things (IoT) has revolutionized the way industries operate, enabling real-time monitoring, predictive maintenance, and optimized resource utilization. However, the sheer volume and complexity of data generated by IoT devices pose significant challenges in terms of data processing, storage, and analysis. This paper proposes a hierarchical and cloud-integrated architecture designed to address these challenges. The architecture consists of edge devices, fog nodes, and cloud servers, each layer responsible for specific data processing tasks. The paper discusses the design, implementation, and evaluation of this architecture, highlighting its benefits in terms of scalability, efficiency, and security. Additionally, a novel data processing algorithm is introduced to optimize the distribution of tasks across the hierarchical layers. The results of our experimental evaluation demonstrate the effectiveness of the proposed architecture in handling large-scale industrial data
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