Analysis of Electrical Equipment at UNICAMP: Insights from the Inventory Database

Data plays a crucial role in understanding several problems, including those related to electrical micro, smart grids and power consumption. In addition to electrical meters, data can be sourced from different channels such as environmental conditions, user expertise, maintenance history, and inventory registries. This paper introduces a Pythonbased analysis tool designed to search for equipment categories that exhibit constant power consumption within the asset inventory database of the University of Campinas. The software effectively identifies and categorizes items as air conditioners, refrigerators, computers, uninterrupted power supplies and internet routers, providing detailed insights into their specific characteristics. The tool generates a comprehensive PDF report featuring item discrimination through values, charts, organized and university units. Additionally, the software incorporates identification item lists and logs, aiding in the identification of missing or mismatched data throughout the process. These reports has been utilized to establish internal guidelines for optimizing in power consumption and already help the university to improve its GreenMetric index.

Palavras-chave

Big data, Data analysis, Python language

Idioma

Inglês

Citação

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 14468 LNCS, p. 213-223.