Endorsing Energy Efficiency Through Accurate Appliance-Level Power Monitoring, Automation and Data Visualization

[1]  Yaya Keho,et al.  What drives energy consumption in developing countries? The experience of selected African countries , 2016 .

[2]  Yi-Ming Wei,et al.  Impact factors of household energy-saving behavior: An empirical study of Shandong Province in China , 2018, Journal of Cleaner Production.

[3]  Yassine Himeur,et al.  Smart power consumption abnormality detection in buildings using micromoments and improved K‐nearest neighbors , 2021, Int. J. Intell. Syst..

[4]  Abbes Amira,et al.  A survey of recommender systems for energy efficiency in buildings: Principles, challenges and prospects , 2021, Inf. Fusion.

[5]  Xiaodong Cao,et al.  Building energy-consumption status worldwide and the state-of-the-art technologies for zero-energy buildings during the past decade , 2016 .

[6]  Abdulsalam Yassine,et al.  Big Data Mining of Energy Time Series for Behavioral Analytics and Energy Consumption Forecasting , 2018 .

[7]  M. Glencross,et al.  Drivers behind Residential Electricity Demand Fluctuations Due to COVID-19 Restrictions , 2020, Energies.

[8]  George Dimitrakopoulos,et al.  The emergence of explainability of intelligent systems: Delivering explainable and personalized recommendations for energy efficiency , 2021, Int. J. Intell. Syst..

[9]  Helia Zandi,et al.  VOLTTRON-enabled Home Energy Management System , 2019 .

[10]  Abbes Amira,et al.  Improving in-home appliance identification using fuzzy-neighbors-preserving analysis based QR-decomposition , 2020, ArXiv.

[11]  Iraklis Varlamis,et al.  REHAB-C: Recommendations for Energy HABits Change , 2020, Future Gener. Comput. Syst..

[12]  Abbes Amira,et al.  An intelligent nonintrusive load monitoring scheme based on 2D phase encoding of power signals , 2020, Int. J. Intell. Syst..

[13]  Sherali Zeadally,et al.  Blockchain for Internet of Energy management: Review, solutions, and challenges , 2020, Comput. Commun..

[14]  George Dimitrakopoulos,et al.  Reshaping consumption habits by exploiting energy-related micro-moment recommendations: A case study , 2020, ArXiv.

[15]  Sandeeka Mannakkara,et al.  Making Sense of Energy-Saving Behaviour: A Theoretical Framework on Strategies for Behaviour Change Intervention , 2019, Procedia Computer Science.

[16]  Abbes Amira,et al.  The Emergence of Hybrid Edge-Cloud Computing for Energy Efficiency in Buildings , 2021, IntelliSys.

[17]  Haleem Farman,et al.  Internet of Energy: Opportunities, applications, architectures and challenges in smart industries , 2020, Comput. Electr. Eng..

[18]  George Dimitrakopoulos,et al.  On the Applicability of 2D Local Binary Patterns for Identifying Electrical Appliances in Non-intrusive Load Monitoring , 2020, IntelliSys.

[19]  Imran A. Zualkernan,et al.  A smart home energy management system using IoT and big data analytics approach , 2017, IEEE Transactions on Consumer Electronics.

[20]  Abbes Amira,et al.  A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks , 2020, Cognitive Computation.

[21]  Ching Man Chan,et al.  Energy conservation through smart homes in a smart city: A lesson for Singapore households , 2017 .

[22]  Chien-Cheng Chou,et al.  Spatiotemporal analysis and visualization of power consumption data integrated with building information models for energy savings , 2017 .

[23]  Abbes Amira,et al.  Artificial Intelligence based Anomaly Detection of Energy Consumption in Buildings: A Review, Current Trends and New Perspectives. , 2020 .

[24]  Abbes Amira,et al.  Data fusion strategies for energy efficiency in buildings: Overview, challenges and novel orientations , 2020, Inf. Fusion.

[25]  Abbes Amira,et al.  Achieving Domestic Energy Efficiency Using Micro-Moments and Intelligent Recommendations , 2020, IEEE Access.

[26]  Abbes Amira,et al.  Building power consumption datasets: Survey, taxonomy and future directions , 2020, Energy and Buildings.