This dissertation was written as a part of the MSc in Data Science at the International
Hellenic University. The recent exponential growth of available data in today's fast-paced …

Energy demand forecasting has become a relevant subject in the energy management field.
Different techniques are being currently applied to forecast the energy demand for different …

The data-driven approach has been widely adopted in fault detection and diagnosis and
optimal control of building energy systems for improving building performance since the …

This study aims to enable cost-effective Internet of Things (IoT) system design by removing
redundant IoT sensors through the correlation analysis of sensing data collected in a smart …

Data mining and machine learning methods aimed at predicting the electrical energy
demand of air conditioning systems are described with reference to a real-time control of …

The sustainability of the planet is significantly impacted by buildings. Numerous research
has been done over the past few decades to improve the performance of buildings at …

SUMMARY Brains for Buildings Energy Systems (B4B) is a multi-year, multi-stakeholder
project that aims at developing smart building methods to enhance the operations in …

Concerns about the effects of global warming and predicted rising sea levels are radically
changing government policies to lower carbon emissions using sustainable green …

Buildings should play a key role in the energy transition, since they account for almost 40%
of EU's energy consumption. This is acknowledged by numerous European directives, which …

Growing urbanization tendencies have increased the role that buildings play in future
energy systems. We present a comparative study of load forecasting methods for large …