**5.1 Artificial intelligence (AI)**

AI technologies, such as machine learning and predictive analytics, can be used to analyze and interpret the large amounts of data generated by IoT devices, providing insights into energy usage patterns, and identifying areas for optimization. AI can also be used to automate energy management processes, reducing the need for manual intervention, and improving overall efficiency [11]. For example, AI algorithms can predict energy demand and adjust supply, accordingly, ensuring energy resources are used more effectively. Artificial intelligence (AI): AI technologies hold promise in addressing the complexities of IoT-enabled energy management. Machine learning algorithms can analyze the massive volume of data generated by IoT devices, uncovering patterns and trends that might be difficult for humans to identify. Predictive analytics can forecast energy demand based on historical data, weather forecasts, and other factors. AI-driven optimization can dynamically adjust energy consumption patterns, making systems more responsive and efficient. For instance, AI can optimize the operation of smart grids by balancing energy supply and demand, reducing wastage, and minimizing costs. By automating energy management processes, AI reduces human error and allows for real-time decision-making, resulting in more effective resource allocation.
