Matlab-based Graphical User Interface for IoT Sensor Measurements Subject to Outlier

Graphical user interface is addressed for outlier detection in sensor measurement. One of the essential steps toward sensor measurement analysis and decision making is anomaly detection. Specifically, measurement noise may encounter abnormal readings, which affect the model algorithm and hence misleading decisions; hence, data must be explored, cleaned, and corrected before being considered for statistical analysis. In this paper, we propose an interactive, easy to navigate, and friendly user interface to extract and explore the sensor's abnormal measurement records. Extraction, visualization, and detection are the three main tasks of such an interface, particularly providing the user with a variety of predefined detection techniques as the first step toward data analysis. The interface is operated via Matlab, and the effectiveness of such a tool is demonstrated by the mean of real-time measurements extraction where different outlier detection is considered.