Please use this identifier to cite or link to this item: http://dspace.univ-tiaret.dz:80/handle/123456789/16858
Title: Proposed Approach for an Intelligent Energy Management System in Smart Cities
Authors: NASRI, Sonia
Keywords: Smart cities
energy management
deep learning
Fuzzification
Issue Date: ماي-2025
Publisher: University of Ibn Khaldoun Tiaret
Abstract: The increasing complexity of urban environments and the growing demand for sustainable development have accelerated the adoption of smart city paradigms. Smart cities integrate advanced technologies to enable real-time monitoring and intelligent management of critical resources such as electricity gas, and water. These systems aim to enhance operational efficiency, reduce environmental impact, and support long-term sustainability. However, the implementation of such systems is not without challenges. Issues related to interoperability, scalability, data overload, and the energy requirements of IoT infrastructure could hinder the effectiveness and reliability of smart city applications. In particular, energy management within smart buildings remains a critical area requiring robust predictive models capable of handling uncertainty and complex consumption patterns.
URI: http://dspace.univ-tiaret.dz:80/handle/123456789/16858
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