Big Data Analytics for Enhancing Coal-Based Energy Production Amidst AI Infrastructure Growth

Modern-day AI infrastructure development requires more urgent need for reliable and efficient energy resources. Renewable energy obtains increasing attention, but coal-based energy generates substantial power in the worldwide energy consumption alongside emerging markets. The need for innovation becomes essential to optimize coal utilization because coal production contains efficiency problems alongside environmental challenges. The analysis draws data from multiple high-demand coal plant regions through their production logs with IoT sensors and their connected SCADA systems. Predictive models with machine learning algorithms, evaluate operational trends and breakdown patterns and environmental compliance performance. The implementation of BDA in AI-supported energy infrastructures is studied through case-based research that proves how better decisions, and reduced costs accompany balanced power distribution. Analysis of big data has proven to enhance coal-based energy operations its compatibility with AI-driven systems, which delivers better process efficiency and sustained energy production capabilities. The coal energy, artificial intelligence and big data analytics form a practical method to achieve smarter and more responsible energy operations in a data-centered environment. The study recommends political and energy sector investments in data infrastructure along with qualified personnel to bring out the complete advantages of these benefits.

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Publication Details

Journal
Journal of Posthumanism
Published
2025-04-24
DOI
https://doi.org/10.63332/joph.v5i5.2087
Citations
2
Primary Topic
Big Data Technologies and Applications
Type
article
Field-Weighted Citation Impact
8.34
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article

Big Data Analytics for Enhancing Coal-Based Energy Production Amidst AI Infrastructure Growth

Mohiuddin Ahmed Bhuiyan, Md. Sharif Uddin, M. Ahmed, Mia Md Tofayel Gonee Manik et al.
2 citations
Journal of Posthumanism
Big Data Technologies and Applications
8.34
article

Big Data Analytics for Enhancing Coal-Based Energy Production Amidst AI Infrastructure Growth

Mohiuddin Ahmed Bhuiyan, Md. Sharif Uddin, M. Ahmed, Mia Md Tofayel Gonee Manik, Fahmida Binte Khair, Md Alamgir Miah, Evha Rozario, Md Аsikur Rаhmаn Chy
article en
2 citations

Abstract

Modern-day AI infrastructure development requires more urgent need for reliable and efficient energy resources. Renewable energy obtains increasing attention, but coal-based energy generates substantial power in the worldwide energy consumption alongside emerging markets. The need for innovation becomes essential to optimize coal utilization because coal production contains efficiency problems alongside environmental challenges. The analysis draws data from multiple high-demand coal plant regions through their production logs with IoT sensors and their connected SCADA systems. Predictive models with machine learning algorithms, evaluate operational trends and breakdown patterns and environmental compliance performance. The implementation of BDA in AI-supported energy infrastructures is studied through case-based research that proves how better decisions, and reduced costs accompany balanced power distribution. Analysis of big data has proven to enhance coal-based energy operations its compatibility with AI-driven systems, which delivers better process efficiency and sustained energy production capabilities. The coal energy, artificial intelligence and big data analytics form a practical method to achieve smarter and more responsible energy operations in a data-centered environment. The study recommends political and energy sector investments in data infrastructure along with qualified personnel to bring out the complete advantages of these benefits.

Journal of PosthumanismVol. 5(5)
American University (US)
Openalex Percentile: Top 3%
Big Data Technologies and Applications
8.34
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