AI-driven energy optimization: integrating smart meters, controllers, and cloud analytics for efficient urban infrastructure management
Pawan Whig, Siva Subrahmanyam Balantrapu, Anumaan Whig, Naved Alam, Rohit Subhash Shinde, Pushan Kumar Dutta
Abstract
This research examines the transformative impact of Artificial Intelligence (AI) on smart city infrastructure, focusing on energy management and optimization. We present the iWattMeter, iWattController, and iWattCloud system, an integrated AI-driven solution for real-time electricity consumption analysis, forecasting, and management. Our technology utilizes high-frequency time series data of voltage, current, power, and power factor to detect and isolate individual device consumption patterns within electrical installations. Through advanced statistical and pattern recognition methods, the system reconstructs device-specific power usage profiles, enabling precise energy monitoring and control. The cloud-based platform offers real-time visualization and control capabilities for both private households and businesses. It seamlessly integrates with photovoltaic systems, energy storage units, and electric vehicle charging stations, providing a comprehensive 360° energy management solution. Initial implementations have shown significant improvements in energy efficiency. The system's ability to optimize self-produced electricity usage, coupled with its proactive device control features, has led to substantial reductions in overall energy consumption. Moreover, the unified interface eliminates the need for multiple apps and systems, streamlining energy management processes. This research demonstrates the potential of AI-driven solutions in creating more efficient and sustainable urban environments, particularly in the domain of energy infrastructure management. The findings underscore the critical role of intelligent systems in achieving smart city objectives and addressing urban energy challenges. Additionally, AI applications in waste management have optimized collection routes, reducing costs by 15% and increasing recycling rates by 10%. These findings highlight AI's significant benefits in creating smarter, more efficient, and resilient urban environments.