Enhancing Energy Efficiency and Security in IoTDriven Smart Cities Using Hybrid GAN-ICA Framework

The rapid emergence of IoT-powered smart cities has generated substantial apprehensions regarding energy efficiency and security. Current technologies frequently fail to adequately address these concerns in a comprehensive manner. This study presents a hybrid framework that combines GAN with ICA to improve energy efficiency and security in smart city infrastructures. The design of the model utilizes GANs to generate synthetic data and ICA to extract independent characteristics, resulting in improved accuracy and security of IoT systems. The accuracy of our model surpassed that of previous technologies, reaching 97.5%. Additionally, our model achieved a precision of 95.0% and an F1 score of 95.6%. As a result, our model has established a new benchmark in smart city research. The results showcase the model's capacity to enhance smart city operations, rendering it a worthwhile addition to the field.