{'fraction_non_alphanumeric': 0.022388059701492536, 'fraction_numerical': 0.0014925373134328358, 'mean_word_length': 5.045045045045045, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
EMD inspired filtering algorithm for signal analysis in the context of non intrusive load monitoring

Smart meters based on Non-intrusive load monitoring (NILM) will be an essential part of our homes and buildings in the near future. In this paper, a novel algorithm for signal analysis in the context of NILM is proposed. The total electrical consumption is decomposed adaptively into narrow banded modes, which can be analyzed to extract useful information about the individual consumption of each device, including its ON-OFF events. The algorithm delivered very good results when used for the purpose of event detection on a publically available dataset (BLUED) [1].