Akıllı Saat Algılayıcıları ile İnsan Hareketlerinin Sınıflandırılması
Year 2017,
Volume: 21 Issue: 3, 980 - 990, 08.05.2017
Ensar Arif Sağbaş
,
Serkan Ballı
Abstract
Giyilebilir teknolojideki gelişmelerle birlikte ortaya çıkan cihazlar hızla gündelik hayatın bir parçası haline gelmiştir. Özellikle sahip oldukları algılayıcılar, bu cihazların kullanışlılığını artırmaktadır. Bu çalışmanın amacı, akıllı saatlerin sahip olduğu algılayıcılar kullanılarak insan hareketlerinin tespit edilmesidir. Bu amaçla, akıllı saatler üzerinde çalışabilen bir mobil uygulama geliştirilmiştir. Geliştirilen uygulama ile 9 farklı insan hareketi için algılayıcı verileri akıllı saat aracılığı ile toplanmış ve 4 saniyelik pencere aralıkları ile desenler oluşturulmuştur. Oluşturulan desenler 10 farklı makine öğrenmesi yöntemi ile test edilmiş ve performansları karşılaştırılmıştır.
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Year 2017,
Volume: 21 Issue: 3, 980 - 990, 08.05.2017
Ensar Arif Sağbaş
,
Serkan Ballı
References
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- [20] Feng T., Timmermans H.J.P. 2010. Comparative Evaluation of Algorithms for GPS Data Imputation. 13th WCTR, 15 Temmuz, Rio de Janerio, 1-11.
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- [25] Frank, E., Wang, Y., Inglis, S., Holmes, G., Witten, I. H. 1998. Using model trees for classification. Machine Learning, 32(1), 63-76.
- [26] Zhao, Y., Zhang, Y. 2008. Comparison of decision tree methods for finding active objects. Advances in Space Research, 41(12), 1955-1959.
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- [31] Using the Step Counter Sensor, http://developer.android.com/guide/topics/sensors/sensors_motion.html#sensors-motion-stepcounter (Erişim Tarihi: 05.04.2016)
- [32] Ballı S., 2016. A data mining approach to the diagnosis of failure modes for two serial fastened sandwich composite plates. Journal of Composite Materials. Baskıda.
- [33] Witten I.H., Frank E. 2005. Data mining: Practical machine learning tools and techniques. San Francisco, CA: Morgan Kaufmann Publishers, 525s.
- [34] Garner, S. R. (1995). Weka: The waikato environment for knowledge analysis. In Proceedings of the New Zealand computer science research students conference. Hamilton, New Zealand, 57-64.