INTELLIGENT CITIES USING ARTIFICIAL INTELLIGENCE TO SAVE ENERGY.
Abstract
The high rate of urbanization has greatly escalated the issue of energy demand in the
contemporary cities. The Smart City projects are meant to enhance the efficiency of
the urban systems in a digital manner. Artificial Intelligence (AI) significantly
contributes to the analysis of big amounts of urban data and optimization of energy
usage. This research paper is about the way AI can enhance energy efficiency of smart
cities by predicting demand, controlling distributed energy sources, and promoting
intelligent energy delivery. It is suggested to use a hybrid model consisting of deep
learning and reinforcement learning to enhance energy prediction and adaptive control.
The results of the simulation prove that the proposed method leads to a better
forecasting accuracy, less peak load demand and higher total energy savings compared
to the conventional statistical approaches. The article explains how AI-oriented
decision-making systems can be important in ensuring the sustainability and energy
efficiency of the urban areas.
References
J. Doe, “Artificial Intelligence Applications in Smart Cities,” Journal of Sustainable
Computing,
A. Smith, “Reinforcement Learning for Smart Grid Optimization,” IEEE Transactions
on
Smart
Grid,
K. Li, “Deep Learning Approaches for Energy Demand Forecasting,” ACM Computing
Surveys,
M. Brown, “Energy Management in Smart Urban Infrastructure,” International Journal
of Energy Research, 2024.
