Big data mining of energy time series for behavioral analytics and energy consumption forecasting
Responsible, efficient and environmentally aware energy consumption behavior is
becoming a necessity for the reliable modern electricity grid. In this paper, we present an …
becoming a necessity for the reliable modern electricity grid. In this paper, we present an …
Mining human activity patterns from smart home big data for health care applications
Nowadays, there is an ever-increasing migration of people to urban areas. Health care
service is one of the most challenging aspects that is greatly affected by the vast influx of …
service is one of the most challenging aspects that is greatly affected by the vast influx of …
A Kalman filter-based bottom-up approach for household short-term load forecast
Renewable energy sources are now being used with buildings like PV panels.
Consequently, short-term household load forecast plays an important role in managing …
Consequently, short-term household load forecast plays an important role in managing …
Artificial intelligence for social good: A survey
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and
advance artificial intelligence to address societal issues and improve the well-being of the …
advance artificial intelligence to address societal issues and improve the well-being of the …
Energy consumption prediction of appliances using machine learning and multi-objective binary grey wolf optimization for feature selection
D Moldovan, A Slowik - Applied Soft Computing, 2021 - Elsevier
Prediction of the energy consumed by household appliances is a challenging research topic
owing to a transition toward the Internet of Everything. Although classical machine learning …
owing to a transition toward the Internet of Everything. Although classical machine learning …
Decentralized federated learning framework for the neighborhood: a case study on residential building load forecasting
The fast-growing trend of Internet of Things (IoT) has provided its users with opportunities to
improve user experience such as voice assistants, smart cameras, and home energy …
improve user experience such as voice assistants, smart cameras, and home energy …
An adaptive machine learning framework for behind-the-meter load/PV disaggregation
R Saeedi, SK Sadanandan… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
A significant amount of distributed photovoltaic (PV) generation is “invisible” to distribution
system operators since it is behind the meter on customer premises and not directly …
system operators since it is behind the meter on customer premises and not directly …
Tariff agent: interacting with a future smart energy system at home
Smart systems are becoming increasingly ubiquitous and consequently transforming our
lives. The level of system autonomy plays a vital role in the development of smart systems as …
lives. The level of system autonomy plays a vital role in the development of smart systems as …
Algorithmic and strategic aspects to integrating demand-side aggregation and energy management methods
Demand-side participation schemes are employed to alter customers' use of electrical
power. The design of a complete scheme comprises two separate sub-problems, a …
power. The design of a complete scheme comprises two separate sub-problems, a …
An energy prediction approach for a nonintrusive load monitoring in home appliances
B Buddhahai, W Wongseree… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Home energy monitoring by appliance-level information can provide consumers awareness
on energy saving. The system can be implemented through a smart meter which requires an …
on energy saving. The system can be implemented through a smart meter which requires an …