Classification Methods Performance On Logistic Package State Recognition

https://doi.org/10.22146/ijccs.82697

Muhammad Auzan(1*), Dzikri Rahadian Fudholi(2), Paulus Josianlie P(3), M Ridho Fuadin(4)

(1) Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta
(2) Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta
(3) Bachelor Program of Electronics and Instrumentation, FMIPA UGM, Yogyakarta
(4) Bachelor Program of Electronics and Instrumentation, FMIPA UGM, Yogyakarta
(*) Corresponding Author

Abstract


 In the distribution sector, logistic package experience activities, such as transport, distribution, storage, packaging, and handling. Even though those processes have reasonable operational procedures, sometimes the package experience mishandling. The mishandling is hard to identify because many packages run simultaneously, and not all processes are monitored. An Inertial Measurement Unit (IMU) is installed inside a package to collect three acceleration and rotation data. The data is then labeled manually into four classes: correct handling, vertical fall, and thrown and rotating fall. Then, using cross-validation, ten classifiers were used to generate a model to classify the logistic package status and evaluate the accuracy score. It is hard to differentiate between free-fall and thrown. The classification only uses the accelerometer data to minimize the running time. The correct handling classification gives a good result because the data pattern has few variations. However, the thrown, free-fall and rotating data give a lower result because the pattern resembles each other. The average accuracy of the ten classifications is 78.15, with a mean deviation of 4.31. The best classifier for this research is the Gaussian Process, with a mean accuracy of 94.4 % and a deviation of 3.5 %.


Keywords


Classification; Logistic; IoT; IMU; Mishandling

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DOI: https://doi.org/10.22146/ijccs.82697

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