Abstract
Every electric appliance has an electronic footprint known as its VI profile. The aggregate VI profile of a group of appliances may also be obtained and using deep learning and computer vision methods, the VI profile of each individual appliance may then be extracted from this aggregate. This allows for a non-intrusive way to detect the individual appliances in a household. The detection paves way for monitoring of load based on power consumption to conserve electricity and prevent electrical theft. This work proposes an intelligent load detection system for monitoring of electric appliances within a household with a dataset for four domestic appliances used in Pakistan.
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