Industrial Load Monitoring and Controlling System

Abstract- Industrial sectors, such as manufacturing, chemical processing, and energy-intensive industries, face significant energy consumption costs and sustainability challenges. By implementing IPEMS, industries can monitor real-time energy consumption across various machines, identify inefficiencies, and predict equipment failures through advanced data analytics and machine learning algorithms. The system enables industries to make data-driven decisions regarding energy management, reducing both operational costs and the environmental footprint. IPEMS relies on key technologies, such as IoT-based sensors, smart meters, and cloud computing, to collect, analyse, and visualize energy usage data. The system offers actionable insights into the performance of equipment, suggesting optimization measures, such as load balancing, scheduling, and preventive maintenance. Additionally, predictive analytics enable the system to forecast potential energy inefficiencies and maintenance needs based on historical data patterns. With growing emphasis on green energy and sustainability in industrial operations, IPEMS helps organizations meet energy efficiency standards and regulatory requirements. By reducing unnecessary energy consumption, this system not only enhances profitability but also supports corporate sustainability goals by decreasing carbon emissions

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-06-09
DOI
https://doi.org/10.55041/ijsrem49709
Primary Topic
Industrial Automation and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Industrial Load Monitoring and Controlling System

Rushikesh Borudhe
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Industrial Automation and Control Systems
article

Industrial Load Monitoring and Controlling System

Rushikesh Borudhe
article en

Abstract

Abstract- Industrial sectors, such as manufacturing, chemical processing, and energy-intensive industries, face significant energy consumption costs and sustainability challenges. By implementing IPEMS, industries can monitor real-time energy consumption across various machines, identify inefficiencies, and predict equipment failures through advanced data analytics and machine learning algorithms. The system enables industries to make data-driven decisions regarding energy management, reducing both operational costs and the environmental footprint. IPEMS relies on key technologies, such as IoT-based sensors, smart meters, and cloud computing, to collect, analyse, and visualize energy usage data. The system offers actionable insights into the performance of equipment, suggesting optimization measures, such as load balancing, scheduling, and preventive maintenance. Additionally, predictive analytics enable the system to forecast potential energy inefficiencies and maintenance needs based on historical data patterns. With growing emphasis on green energy and sustainability in industrial operations, IPEMS helps organizations meet energy efficiency standards and regulatory requirements. By reducing unnecessary energy consumption, this system not only enhances profitability but also supports corporate sustainability goals by decreasing carbon emissions

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(06)
Savitribai Phule Pune University (IN)
Openalex Percentile: Top 86%
Industrial Automation and Control Systems
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