Edge computing security: State of the art and challenges

Y Xiao, Y Jia, C Liu, X Cheng, J Yu… - Proceedings of the …, 2019 - ieeexplore.ieee.org
The rapid developments of the Internet of Things (IoT) and smart mobile devices in recent
years have been dramatically incentivizing the advancement of edge computing. On the one …

[HTML][HTML] Artificial intelligence evolution in smart buildings for energy efficiency

H Farzaneh, L Malehmirchegini, A Bejan, T Afolabi… - Applied Sciences, 2021 - mdpi.com
The emerging concept of smart buildings, which requires the incorporation of sensors and
big data (BD) and utilizes artificial intelligence (AI), promises to usher in a new age of urban …

[图书][B] Privacy is power

C Véliz - 2021 - igi-global.com
Privacy is Power Page 1 International Journal of Technoethics Volume 12 • Issue 2 • July-December
2021  Copyright©2021,IGIGlobal.CopyingordistributinginprintorelectronicformswithoutwrittenpermissionofIGIGlobalisprohibited …

[HTML][HTML] An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study

D Murray, L Stankovic, V Stankovic - Scientific data, 2017 - nature.com
Smart meter roll-outs provide easy access to granular meter measurements, enabling
advanced energy services, ranging from demand response measures, tailored energy …

Fedgan: Federated generative adversarial networks for distributed data

M Rasouli, T Sun, R Rajagopal - arXiv preprint arXiv:2006.07228, 2020 - arxiv.org
We propose Federated Generative Adversarial Network (FedGAN) for training a GAN across
distributed sources of non-independent-and-identically-distributed data sources subject to …

[HTML][HTML] Energy sustainability in smart cities: Artificial intelligence, smart monitoring, and optimization of energy consumption

KT Chui, MD Lytras, A Visvizi - Energies, 2018 - mdpi.com
Energy sustainability is one of the key questions that drive the debate on cities' and urban
areas development. In parallel, artificial intelligence and cognitive computing have emerged …

Residential loads flexibility potential for demand response using energy consumption patterns and user segments

M Afzalan, F Jazizadeh - Applied Energy, 2019 - Elsevier
Demand response (DR) is considered an effective approach in mitigating the ever-growing
concerns for supplying the electricity peak demand. Recent attempts have shown that the …

[HTML][HTML] An active learning framework for the low-frequency non-intrusive load monitoring problem

T Todic, V Stankovic, L Stankovic - Applied Energy, 2023 - Elsevier
With the widespread deployment of smart meters worldwide, quantification of energy used
by individual appliances via Non-Intrusive Load Monitoring (NILM), ie, virtual submetering, is …

The determinants of residential energy expenditure in Italy

G Besagni, M Borgarello - Energy, 2018 - Elsevier
As a large part of primary energy consumption in different countries is related to the
residential sector, a reduction in energy consumption at the" household-scale" may …

Can non-intrusive load monitoring be used for identifying an appliance's anomalous behaviour?

H Rashid, P Singh, V Stankovic, L Stankovic - Applied energy, 2019 - Elsevier
Identification of faulty appliance behaviour in real time can signal energy wastage and the
need for appliance servicing or replacement leading to energy savings. The problem of …