Anomaly Detection Algorithm for Localized Abnormal Weather Using Low-Cost Wireless Sensor Nodes

In recent years, we have witnessed an unpresented increase localized heavy weather phenomena such as tornadoes and localized heavy rain which can not be expected by the conventional weather forecast system. However, the number of observation posts is few little for forecasting for tornadoes and heavy rain. It is necessary to increase dramatically the observation points in order to perform ware correct prediction using real data. We have developed a compact and low-cost pressure information acquisition system, to detect the signs of localized abnormal weather. This research proposes an algorithm to predict local weather by detecting anomalous pressure values in the time series of the pressure sensor information, and then to notify users.