Prediction Framework with Kalman Filter Algorithm

Abstract

The article describes the autonomous open data prediction framework, which is in its infancy and is designed to automate predictions with a variety of data sources that are mostly external. The framework has been implemented with the Kalman filter approach, and an experiment with road maintenance weather station data is being performed. The framework was written in Python programming language; the frame is published on GitHub with all currently available results. The experiment is performed with 34 weather station data, which are time-series data, and the specific measurements that are predicted are dew points. The framework is published as a Web service to be able to integrate with ERP systems and be able to be reusable.