Big Data Analytics for Enhancing Coal-Based Energy Production Amidst AI Infrastructure Growth - Miah, Md Alamgir; Ahmed, Md Kamal; Bhuiyan, Mohammad Muzahidur Rahman; Chy Md Аsikur Rаhmаn; Khair, Fahmida Binte; Uddin, Mukther; Rozario, Evha; Manik, Mia Md Tofayel Gonee (Journal of Posthumanism, 2025)
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.