Proceedings of the IMC, Giron, 2014 59 CMN_ADAPT and CMN_binViewer software Denis Vida 1 , Damir Šegon 2 , Peter S. Gural 3 , Goran Martinović 4 , Ivica Skokić 5 1 Astronomical Society “Anonymus”, B. Radića 34, 31550 Valpovo, Croatia Faculty of Electrical Engineering, J.J. Strossmayer University of Osijek, Kneza Trpimira 2b, 31000 Osijek, Croatia denis.vida@gmail.com 2 Astronomical Society Istra Pula, Park Monte Zaro 2, 52100 Pula, Croatia damir.segon@pu.htnet.hr 3 351 Samantha Drive, Sterling, Virginia 20164, USA peter.s.gural@leidos.com 4 Faculty of Electrical Engineering, J.J. Strossmayer University of Osijek, Kneza Trpimira 2b, 31000 Osijek, Croatia goran.martinovic@etfos.hr 5 Astronomical Society “Anonymus”, B. Radića 34, 31550 Valpovo, Croatia ivica.skokic@gmail.com As the main focus of the Croatian Meteor Network (CMN) shifted from data collection to data analysis, primarily to the discovery of new meteor showers, it became clear that the current data processing pipeline was slow and outdated. In this paper new software for fully automatic data acquisition and processing is presented. Furthermore, a new tool for viewing the data acquired with the CAMS capture and compression software is described and a link is given for free download from the CMN webpage. 1 Introduction Since late 2009, when the first procedures for automatic CMN data processing were written (Vida et al., 2011), a constant further development of such tools has been ongoing. Although the process of meteor detection, data calibration (astrometry and photometry) and orbit pairing was mostly a matter of running a few automated scripts, data processing was far from real-time. It is evident from the CMN publications of orbit catalogs (Šegon et al., 2012a; Korlević et al., 2013; Croatian Meteor Network, 2013) that in some cases data had still not been fully processed several years after their initial capture. As the main focus of the network shifted from mere data acquisition to data analysis in 2012 and 2013 (Šegon et al., 2014), it became clear that the existing procedures would no longer be sufficient. CMN staff would not have sufficient time to carry out both activities in parallel. Thus it has been decided to develop a new tool that will provide a fully automatic way of data acquisition and processing. In the second part of the paper a new tool is presented for viewing the files acquired by the CAMS capture, compression and detection software (Jenniskens et al., 2011), and by Skypatrol. 2 Old data processing pipeline summary Data acquisition Since the beginning of the Network, Skypatrol software has been used for data acquisition, mostly because of its low minimum system requirements. In the years of the Network’s expansion, acquiring a PC with a top-line configuration to be available only for the purpose of meteor capturing proved very difficult. Thus Skypatrol presented a good alternative to other more demanding solutions. With the further development of computer technology and the wider availability of faster computer configurations, CMN could afford more advanced capturing solutions. Replacing Skypatrol was a high- priority task as it had certain drawbacks. After each image had been captured there was a 6 second pause taken up by for internal processing procedures and for the writing of the data to disk. This meant that 10% of all meteors would be missed. For some bright multi-station fireballs it was found that although several stations captured it properly, there would often be one station the fireball happened to coincide with the “6 second time hole”. Furthermore, there was no automatic way to start and to stop the capturing process. Automatic scripts which moved the mouse pointer and clicked the start and stop buttons were not very reliable because the Skypatrol window was often minimized and and it could not be automatically restored as the software randomly changed the name of the window. Among other drawbacks, it also could not capture more than two concurrent events. Meteor detection and image calibration Meteor detection was done using MTP_MeteorDetector software (Gural et al., 2009) which was run by a script that allowed large volumes of data to be processed at the same time. The detection procedure was very time- consuming, often requiring more than 24 hours of processor time for a few months of data from only one station. The data collected had to be further filtered to remove unwanted detections and to be calibrated with the CMN_AutoCheckFit software in order to perform astrometry and photometry procedures. In cases where