Assistente virtual para centros de operação

Abstract

The coordination of the electricity sector’s operating activities is carried out by a set of tools and technologies, the most notable of which is audio communication between real-time teams of agents and technicians in the field. These calls are recorded, stored, and consulted on demand for auditing and traceability purposes, as well as to support postoperative analyses. However, because of the difficulty in accessing their content, these recordings, which contain relevant information for both system operation and agent billing, are underutilized. Thus, by transcribing them, it is possible to trace and associate these audios with each other and with other records from different operating systems, allowing for the optimization of activities that require a significant amount of time from post-operation engineers. This dissertation describes a virtual assistant for energy generators, transmitters, and distributors’ operation centers that transcribes all audio communications from these centers and uses natural language processing techniques to extract information from the audios, classify them into topics of interest to the operation, and correlate the recordings with each other and with operating systems. The system architecture is presented, as well as the audio-to-text transcription models used, the classification module, and the correlation between audios and with SCADA module. The project described here is intended to aid decision-making and contribute to greater efficiency, safety, and operational reliability in electrical system operation and post-operation.