Aplicación de Minería de datos a un Sistema de Mantenimiento Predictivo de Detección de Incendios

When treatment is given to large data volumes, it is necessary to use a set of computational techniques known as data mining. In particular, the medium-sized building smoke detection devices can far exceed the one hundred units and fire detection devices require periodic maintenance according to certain pre-established control patterns. To fulfill this purpose requires a crucial tool to optimize the maintenance of such devices to determine which devices require maintenance. This article discusses the concepts of data mining and its application in the maintenance of security systems for fire detection in medium and large infrastructure details. It also proposes a methodology to forecast the trend for maintenance and fault smoke detectors of an intelligent system, we will base it on automatic reports generated by the system panel and written reports of the maintenance work.