Sensors and wrong values

Abstract

In the world of IoT and BigData, sensor based data collection is a really important domain. Using these tools it is possible to stow large amounts of data collection sensors in a factory or in nature in harsh environments. However, in order to obtain valuable information from these tools, it is important that potentially wrong data is discovered and handled. Automated exploration of wrong data is not a trivial task, even if similar measurements are performed in parallel with spatial differences. We present the difficulties of revealing defected data and suggest easy-to-implement procedures for detecting and handing them. We also draw attention to the potential disadvantages of these methods based on the given results.