AI Driven Streamlining of Appliance Load Monitoring in Facilities Management
Author:
Affiliation:
1. EKYC Solutions Co. Ltd,Phnom Penh,Cambodia
2. The University of Essex,School of Computer Science and Electronic Engineering,Colchester,United Kingdom
3. Cloudfm Group Ltd,Colchester,United Kingdom
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10620912/10620920/10620932.pdf?arnumber=10620932
Reference14 articles.
1. An Overview of Non-Intrusive Load Monitoring Based on V-I Trajectory Signature;Lu;Energies,2023
2. An Empirical Investigation of V-I Trajectory Based Load Signatures for Non-Intrusive Load Monitoring;Hassan;IEEE Transactions on Smart Grid,2014
3. A feasibility study of automated plug-load identification from high-frequency measurements;Gao
4. Automated classification of appliances using elliptical fourier descriptors;De Baets
5. VI-Based Appliance Classification Using Aggregated Power Consumption Data;De Baets
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