Enhancing Industrial Automation and Safety Through Real-Time Monitoring and Control Systems

Industrial automation has revolutionized the efficiency and safety of manufacturing and processing industries. This paper explores the development of a real-time monitoring and control system aimed at enhancing industrial automation andsafety by integrating advanced sensor networks, data analytics, and automated response protocols. The proposed system utilizes robust sensor fusion techniques to monitor operational parameters continuously, enabling predictive maintenance and immediate response to potential hazards. This paper discusses the system architecture, mathematical modeling of sensor data, and implementation strategies to ensure high reliability and minimal human intervention. Simulation results are presented to validate the system's effectiveness and comparative analysis is conducted between two model variations. The findings demonstrate significant improvement in both operational safety and process efficiency.

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Publication Details

Journal
International Journal on Smart & Sustainable Intelligent Computing
Published
2024-10-31
DOI
https://doi.org/10.63503/j.ijssic.2024.30
Citations
10
Primary Topic
Fault Detection and Control Systems
Type
article
Field-Weighted Citation Impact
3.28
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article

Enhancing Industrial Automation and Safety Through Real-Time Monitoring and Control Systems

Rohit Sharma
10 citations
International Journal on Smart & Sustainable Intelligent Computing
Fault Detection and Control Systems
3.28
article

Enhancing Industrial Automation and Safety Through Real-Time Monitoring and Control Systems

Rohit Sharma
article en
10 citations

Abstract

Industrial automation has revolutionized the efficiency and safety of manufacturing and processing industries. This paper explores the development of a real-time monitoring and control system aimed at enhancing industrial automation andsafety by integrating advanced sensor networks, data analytics, and automated response protocols. The proposed system utilizes robust sensor fusion techniques to monitor operational parameters continuously, enabling predictive maintenance and immediate response to potential hazards. This paper discusses the system architecture, mathematical modeling of sensor data, and implementation strategies to ensure high reliability and minimal human intervention. Simulation results are presented to validate the system's effectiveness and comparative analysis is conducted between two model variations. The findings demonstrate significant improvement in both operational safety and process efficiency.

International Journal on Smart & Sustainable Intelligent ComputingVol. 1(2)
ABES Engineering College
Openalex Percentile: Top 7%
Fault Detection and Control Systems
3.28
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