Online devices monitoring and analysis using data mining

In this study, which is expected to be performed on printers that are connected to a network to be online, the counter values (number of prints, odometer, etc.) of all these devices are recorded and recorded in certain periods. In this study, it is expected that the efficiency of the subject devices will be increased. The data to be collected can be made by manual methods (control over the device) or by remote connection. This data will be stored depending on the serial numbers of the printers and will be available upon request. Then, these data are used by using various data mining and artificial intelligence methods and algorithms, taking into account the technical capacity and technical life of the machine, determining whether the location is in need of a lower volume or high volume device, making inferences from past data for the future. To determine the factors that affect the counter of the printer, to determine their degree of effect. Within the scope of the study, different data analysis with Excel Data Analysis, WeKa Explorer and MatLab were performed and all of them were interpreted in the conclusion.