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Abstract
The rapid evolution of Industrial Internet of Things (IoT) technologies has provided new opportunities for enhancing energy efficiency in manufacturing systems. This study presents the design and implementation of a scalable, cloud-based IoT platform specifically engineered to monitor and analyze specific energy consumption (SEC) in manufacturing environments. Given that industrial sectors in developing economies, such as Uzbekistan, often exhibit energy intensities significantly higher than global benchmarks, the development of localized, low-cost monitoring solutions is imperative. The proposed system integrates high-precision electrical sensors (PZEM-004T), microcontroller units (ESP32) for edge data processing, and a centralized cloud-based dashboard for real-time visualization and analytics. The research methodology involves the deployment of the platform within a medium-scale manufacturing facility to evaluate its performance in tracking SEC—defined as the energy required to produce a single unit of output. Statistical analysis of the collected data reveals that real-time visibility into energy use patterns allows for the identification of non-productive energy peaks and operational inefficiencies. Results indicate that the system achieves a measurement accuracy of 98.5% compared to commercial laboratory-grade meters, while offering a cost reduction of nearly 70% in hardware expenditure. Furthermore, the discussion highlights how the platform supports decision-making for energy-saving interventions, potentially reducing total energy costs by up to 15%. This research contributes to the regional literature on Industry 4.0 transition in Central Asia, providing a practical framework for digitalizing energy management in local industrial contexts.
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