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Y. NaitMalek

Researcher at International University, Cambodia

Publications -  20
Citations -  286

Y. NaitMalek is an academic researcher from International University, Cambodia. The author has contributed to research in topics: Efficient energy use & Energy consumption. The author has an hindex of 8, co-authored 17 publications receiving 164 citations. Previous affiliations of Y. NaitMalek include Mohammed V University.

Papers
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Journal ArticleDOI

Towards a Real-time Occupancy Detection Approach for Smart Buildings

TL;DR: The work presented in this paper is towards the development of a holistic platform that combines recent IoT and Big data technologies for real-time occupancy detection by comparing static and dynamic machine learning techniques.
Journal ArticleDOI

Online battery state-of-charge estimation methods in micro-grid systems

TL;DR: Batteries have shown great potential for being integrated in Micro-Grid (MG) systems, however, their integration is not a trivial task and, therefore, requires extensive modeling and simulations in order to efficiently estimating their State-of-Charge (SoC) within MG systems.
Journal ArticleDOI

An energy management platform for micro-grid systems using Internet of Things and Big-data technologies:

TL;DR: Results show the usefulness of the proposed platform for efficient management of the deployed micro-grid system for efficient integration and management of renewable energy sources and storage devices.
Journal ArticleDOI

A Comparative Study of Predictive Approaches for Load Forecasting in Smart Buildings

TL;DR: The accuracy of various machine learning and statistical methods for forecasting energy consumption is investigated and results are reported to shed more light on the accuracy of these methods for load forecasting.
Proceedings ArticleDOI

Towards a context-driven platform using IoT and big data technologies for energy efficient buildings

TL;DR: A holistic platform that integrates recent sensing/actuating and Big data technologies for monitoring and data processing that develops context-driven control approaches whereby energy consumption, production, and storage could be controlled according to actual situations.