Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions

SB Atitallah, M Driss, W Boulila, HB Ghézala - Computer Science Review, 2020 - Elsevier
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …

[HTML][HTML] Building energy performance monitoring through the lens of data quality: A review

J Morewood - Energy and Buildings, 2023 - Elsevier
Data quality is important across sectors to ensure that data meets the requirements of its
users, but until now little attention has been given to how it is reported in the architecture …

Machine learning-integrated IoT-based smart home energy management system

M Syamala, CR Komala, PV Pramila… - … of Research on Deep …, 2023 - igi-global.com
The internet of things (IoT) is an important data source for data science technology,
providing easy trends and patterns identification, enhanced automation, constant …

Usage and impact of the internet-of-things-based smart home technology: a quality-of-life perspective

LY Rock, FP Tajudeen, YW Chung - Universal access in the information …, 2024 - Springer
The aim of this paper is to explore the usage and impact of the Internet-of-Things-based
Smart Home Technology (IoT-SHT) in Malaysia. Face-to-face interviews were conducted …

Energy management solutions in the Internet of Things applications: Technical analysis and new research directions

D Wang, D Zhong, A Souri - Cognitive Systems Research, 2021 - Elsevier
By advancement of Internet of Things (IoT) technology in smart life such as smart city, smart
home, smart healthcare and smart transportation, interconnections between smart things are …

AI and ML Adaptive Smart-Grid Energy Management Systems: Exploring Advanced Innovations

S Saravanan, R Khare, K Umamaheswari… - … and Applications in …, 2024 - igi-global.com
The chapter explores the transformative role of artificial intelligence (AI) and machine
learning (ML) in shaping smart energy management systems (SEMS) and predicts …

Applications of IoT and digital twin in electrical power systems: A comprehensive survey

DEA Mansour, M Numair, AS Zalhaf… - IET Generation …, 2023 - Wiley Online Library
This paper reviews the applications of Internet of Things (IoT) and digital twin technology in
electrical power systems. It begins by discussing the generalized IoT value chain, followed …

A comprehensive predictive-learning framework for optimal scheduling and control of smart home appliances based on user and appliance classification

W Shafqat, KT Lee, DH Kim - Sensors, 2022 - mdpi.com
Energy consumption is increasing daily, and with that comes a continuous increase in
energy costs. Predicting future energy consumption and building an effective energy …

[HTML][HTML] Faults in consumer products are difficult to diagnose, and design is to blame: A user observation study

BP Arcos, S Dangal, C Bakker, J Faludi… - Journal of Cleaner …, 2021 - Elsevier
The process of fault diagnosis is an essential first step when repairing a product: it
determines the condition of the parts and identifies the origin of failure. We report on how …

LSTM forecasts for smart home electricity usage

RE Alden, H Gong, C Ababei… - 2020 9th International …, 2020 - ieeexplore.ieee.org
With increasing of distributed energy resources deployment behind-the-meter and of the
power system levels, more attention is being placed on electric load and generation …