We present a software package utilizing machine learning methods to detect cloud coverage based on All Sky Camera images. The code will use different methods for nighttime and daytime cloud detection and with machine learning the accuracy of the results is improved. This piece of software will be one of the methods to be used in the Eastern Anatolia Observatory(DAG)'s 4m class telescope. For this purpose, we used Python3 and other related modules.
DAG (Eastern Anatolia Observatory) project is an ongoing project of 4 m visible (VIS) and near-infrared (IR) class telescope with active optics on primary mirror and adaptive optics on the Nasmyth platform at 3170 m altitude in Erzurum, Turkey. The first light of DAG Telescope will be taken on 2020. Some meteorological and astronomical measurements have been taken from several devices (meteorology stations, all sky camera, seeing camera and seeing quality meter, GNSS receiver, etc.) placed on a platform at the top of a 7 m tall DIMM tower at DAG Site (Konaklı/Erzurum) since the beginning of project (2012). Every device produces many various types of big-data. In order to analyse and evaluate these data all together in real-time, we have planned to design a database and a controller-pipeline software. In this poster, we present the first plans of this effort on a WEB GUI which allows to control historical and current data via the related charts.
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