Towards Energy Smart Homes

Algorithms, Technologies, and Applications
1. Auflage 2021
ISBN: 978-3-030-76476-0
Verlag: Springer International Publishing

Buch, Englisch, 620 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1109 g

This book exemplifies how smart buildings have a crucial role to play for the future of energy. The book investigates what already exists in regards to technologies, approaches and solutions both with a scientific and technological point of view. The authors cover solutions for mirroring and tracing human activities, optimal strategies to configure home settings, and generating explanations and persuasive dashboards to get occupants better committed in their home energy managements. Solutions are adapted from the fields of Internet of Things, physical modeling, optimization, machine learning and applied artificial intelligence. Practical applications are given throughout.

Zielgruppe

Research

Autoren/Hrsg.

Ploix, Stephane

Bouguila, Nizar

Amayri, Manar

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik

Inhaltsverzeichnis

Introduction.- Smart grids, districts and energy smart homes.- Urban modeling and analytics in a smart context.- What kind of technologies for Smart-Homes.- Services for energy smart home.- Modeling and calibration for energy management in smart-places.- Machine Learning: a fundamental tool for smart-places.- Estimate building system state.- Disaggregate loads to analyze human behavior predicting energy demand.- Determine the best actions.- Generate explanation.- Human machine interface (HMI).- Diagnose appliance and sensor faults but also misbehavior.- Tools for Energy Management system.- Conclusion.

Über Autor(innen)

Stéphane Ploix is a Professor at the Grenoble Institute of Technology in the Energy, Water and Environment department. After a Master of Technology in mechanics and electricity from a French "grande école[MOU1] " and a Master of Sciences in Control, he obtained in 1998 a Ph.D. from the Institute National Polytechnique de Lorraine in control engineering and signal processing. He became a full Professor in 2009. From the very beginning his researches set at the interface of engineering, control and computer sciences. He started by extending algorithms for diagnostic analysis coming from artificial intelligence community to different engineering area, including sensor networks for hydrology, water networks and photovoltaic farms. In 2006, he decided to redirect his researches in energy smart-building and to study how computers and control sciences could contribute to this new application area. His researches led to the development of the G-homeTech software for global anticipative model based energy management of buildings. In 2012, he was part of the team that won the Solar Decathlon Europe worldwide competition with the CANOPEA building equipped with the G-homeTech software. He is one of the founders of the Vesta-System company that markets applications for building energy management. Then, his interest turned to human-machine cooperation in building energy management: how to get the best from occupants and from smart systems thanks to cooperative mechanisms? He has been involved in various industrial projects with small and big companies and institutions such as EDF, CSTB, Orange, CEA, Schneider Electric and Engie.

Manar AMAYRI is a researcher at CNRS in G-SCOP lab (Sciences pour la conception, l'Optimisation et la Production), her work as a postdoctoral fellow is part of a French national project on building performance mamed COMEPOS. This project focuses on « Positive Energy » detached houses. She’s developing a toolto calculate usage indicators in different sites. She obtained her Ph.D. degree from Grenoble Institute of Technology in energy smart-buildings in 2017 and  a master degree in smart grids and buildings, ENES3, INP-Grenoble (Institute National Polytechnique de Grenoble) in 2014, She has also a master degree in electrical power systems, Power department, Damascus University. and a Bachelor degree in power engineering from Damascus university, Syria. Her current research interests focus on developing interactive approaches based on machine learning algorithms applied to different smart buildings related tasks (e.g. occupancy estimation, activity recognition ,etc).

Nizar BOUGUILA received the engineer degree from the University of Tunis, Tunis, Tunisia, in 2000, and the M.Sc. and Ph.D. degrees in computer science from Sherbrooke University, Sherbrooke, QC, Canada, in 2002 and 2006, respectively. He is currently a Professor with the Concordia Institute for Information Systems Engineering (CIISE) at Concordia University, Montreal, Quebec, Canada. His research interests include machine learning, data mining, computer vision, and pattern recognition applied to different real-life problems (e.g. Quality control, security, smart buildings, finance, etc). Prof. Bouguila received the best Ph.D Thesis Award in Engineering and Natural Sciences from Sherbrooke University in 2007. He was awarded the prestigious Prix d’excellence de l’association des doyens des etudes superieures au Quebec (best Ph.D Thesis Award in Engineering and Natural Sciences in Quebec), and was a runner-up for the prestigious NSERC doctoral prize. He is the author or co-author of more than 200 publications in several prestigious journals and conferences. He is a regular reviewer for many international journals and serving as associate editor for several journals such as  Pattern Recognition journal. Dr. Bouguila is a licensed Professional Engineer registered in Ontario, and a Senior Member of the IEEE. He is the holder of Concodia University Research Chair.