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Higher National School of Renewable Energies, Environment and Sustainable Development
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Item Energy Monitoring(Higher National School of Renewable Energies, Environment and Sustainable Development, 2024-06-15) ABD ELMERAIM RaziqaThis dissertation describes a new AI-based energy conservation solution. It has built-in advanced sensors, wireless connectivity, and AI algorithms that monitor and optimize energy consumption in real time. The device achieves huge energy savings by providing device-level monitoring, predictive analytics, and automated optimization. This holistic solution provides a comprehensive and proactive method for efficient energy management. Real-time energy consumption patterns give users the information they need to make decisions. Predictive analytics that accounts for fluctuations in energy demand allows for proactive adjustments, while automatic optimization constantly focuses on efficiency goals, ensuring that these goals are met with significant reductions in energy consumption. In addition to immediate energy savings, the integrated system promotes sustainable practices and helps reduce carbon footprints. Seamless integration of advanced sensors, predictive analytics, and automatic tuning. This manuscript presents an innovative energy conservation solution that incorporates artificial intelligence. It does this by monitoring and optimizing energy consumption in real-time using advanced sensors, wireless connectivity, and AI-based algorithms. Through device-level monitoring and predictive analytics, energy savings are dramatic. It is a comprehensive and proactive program for efficient energy management. Consumers receive real-time insights into their energy consumption patterns, enabling them to make informed decisions. Predictive analysis of consumer data can anticipate surges or dips in demand, enabling proactive demand management, while automated optimization ensures that the system dynamically achieves efficiency targets over time, delivering significant energy savings. In addition to immediate energy savings, the integrated system promotes sustainable practices and reduces carbon footprints through the seamless integration of advanced sensors, predictive analytics, and automatic tuning. Through the integration of advanced sensors and AI algorithms, our energy conservation solution has yielded tangible results in optimizing power consumption across multiple dimensions. By accurately measuring active, reactive, and apparent power, our system provides comprehensive insights into energy usage patterns, enabling users to make informed decisions in real time. The seamless integration of our AI model with an intuitive application empowers users to proactively manage their energy consumption, leading to substantial reductions in overall power usage. Across various applications, from industrial to residential settings, our solution has consistently delivered significant energy savings, surpassing traditional energy management methods. By harnessing the power of AI and precise power measurement capabilities, our solution promotes efficiency and drives sustainability, contributing to a greener and more resource-efficient future.