Today, the organizations that store very large amounts of data need decision support technologies to achieve a satisfactory development of their organizational objectives. It is the case of the National Hydrocarbon Agency of Bolivia (ANH), which due the smuggling of fuel, implemented the RFID technology in order to store the records of fueling of all fleet vehicular in Bolivia. From the model of Anomaly Detection in Records of Fueling trough machine learning techniques proposed by Buarque et al., we propose a Business Intelligence (BI) solution able to deal with huge volume of information from records of fueling and anomalies scores in a local and global level. The proposal permitted the analysis of high anomalies presented in a specific time, by vehicle type, by department and also geo-referenced service stations (with this, the specialist could take decisions of control in some risk zones and specific service stations or vehicle type). We use the Open Source Pentaho Business Intelligence platform, one of the most used currently. This management platform covers data analysis integrated with R and reporting operations, making this a flexible solution to cover our study case: "Anomaly Detection in Records of Fueling in automobiles used for illegal fuel storage". So, the principal contribution in this paper is design and development a BI solution responsible of analyze in large amount of records of anomalies in Bolivia and in this way to allow to make better decisions of control of fuel smuggling by the ANH, having the right information in the right place at the right time.
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Aquize, V., & Santos Filho, M. (2018). Business Intelligence for the detection of anomalies in records of fueling. Revista De Engenharia E Pesquisa Aplicada, 3(3). https://doi.org/10.25286/repa.v3i3.925
Edição Especial em Ciência de Dados e Analytics