İrsel G.2024-06-122024-06-1220169.78802E+12https://hdl.handle.net/20.500.14551/178086th International Conference on Trends in Agricultural Engineering 2016, TAE 2016 -- 7 September 2016 through 9 September 2016 -- -- 128604In this study, it is aimed to create a sensor which may be able to learn with artificial intelligence. The sensor constituted is an industrial inclination sensor. Due to centrifugal force and/or shocking impacts, inclination sensors may have incorrect measurements. Decree of action that causes this error however has been measured by an acceleration sensor. It has been intended to remedy and correct the error of inclination and obtain a usable inclination data. Acceleration sensor, inclination sensor, data logger card have been installed on a platform. Inclination and acceleration values have been simultaneously observed and recorded. Data have been analyzed with WEKA Machine Learning Program. Rules obtained have been used as code in “Arduino”. Thus, using the machine learning technique, and with the support of arduino programming card, a system which transforms measurements of inclination and acceleration sensor to utilizable inclination measurement value has been achieved. © 2016 Czech University of Life Sciences Prague. All Rights Reserved.eninfo:eu-repo/semantics/closedAccessAcceleration Sensor; Arduino; Inclination Balancing System; Inclination Sensor; Machine Learning; WekaAcceleration; Agricultural Engineering; Agriculture; Artificial Intelligence; Acceleration Sensors; Arduino; Balancing System; Inclination Sensors; Weka; Learning SystemsConference Object2016-September2302372-s2.0-85051712347N/A