Akıllı Sensör Verileri Üzerinde Makine Öğrenmesi Yöntemleri Kullanılarak İnsan Aktivitelerinin Tanımlanması
Akıllı sensör teknolojilerindeki gelişmeler ve giyilebilir cihazların maliyetlerinin düşmesi sonucunda bu cihazlardan elde edilen sensör verileri kullanılarak günlük insan aktivitelerinin tanımlanmasına yönelik nesnelerin interneti tabanlı çalışmalar günümüzde önemli bir araştırma konusudur. İnsan aktivitelerinin tanımlanması sağlık, hasta takibi ve güvenlik gibi alanlarda aktiviteye bağlı sorunların çözümüne katkı sağlayabilmektedir. Bu çalışma, akıllı sensörlerden elde edilen veriler üzerinde makine öğrenmesi yöntemlerini kullanarak insan aktivitelerinin tanımlanmasını amaçlamaktadır. Çalışmada Karar Ağacı, OneVsOne ve Çok Katmanlı Algılayıcı sınıflandırıcıları ile modeller oluşturulmuş ve aktiviteleri içeren veri seti ile eğitim ve test aşamaları gerçekleştirilmiştir. Elde edilen sonuçlar karşılaştırılmış ve en iyi sonuca Çok Katmanlı Algılayıcı modeli ile ulaşıldığı görülmüştür.
Anahtar Kelimeler:
Nesnelerin İnterneti, Akıllı Sensörler, Makine Öğrenmesi, Yapay zeka
Recognition of Human Activities Using Machine Learning Methods on Smart Sensor Data
As a result of the developments in smart sensor technologies and the decrease in the costs of wearable devices, internet of things-based studies for the recognition of daily human activities by using sensor data obtained from these devices is an important research topic today. The recognition of human activities can contribute to the solution of activity-related problems in areas such as health, patient follow-up, and safety. This study aims to identify human activities using machine learning methods on data obtained from smart sensors. In this study, models were created with Decision Tree, OneVsOne, and Multilayer Perceptron classifiers, and training and testing stages were carried out with the data set containing the activities. The obtained results were compared, and it was seen that the best result was achieved with the Multi-Layer Perceptron model.
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- Başlangıç: 2022
- Yayıncı: Sivas Cumhuriyet Üniversitesi