{'fraction_non_alphanumeric': 0.020356234096692113, 'fraction_numerical': 0.0, 'mean_word_length': 5.450819672131147, '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}}
A COMPREHENSIVE APPROACH TO THE PREDICTIVE MAINTENANCE OF SECONDARY DISTRIBUTION SUBSTATIONS: DEVICES AND METHODS

The present work addresses the predictive maintenance of Secondary Distribution Substations (SDS) by resorting to IoT models and technologies. Consisting of a fully modular platform, this solution encompasses a number of different wireless smart sensors whose data are locally integrated in an edge unit (information handler and gateway to the cloud). A comprehensive diagnosis, involving both data trending and the detection of single events, is remotely fed to people in charge. Thus, it contributes not only to improve the quality of service, by reducing the number and duration of power outages, but also to reduce costs to both operational and long-term investments.