Automatic Phone Slip Detection System
نویسندگان
چکیده
Mobile phones are becoming increasingly advanced and the latest ones are equipped with many diverse and powerful sensors. These sensors can be used to study different position and orientation of the phone which can help smartphone manufacture to track about their customers handling from the recorded log. The inbuilt sensors such as the accelerometer and gyroscope present in our phones are used to obtain data for acceleration and orientation of the phone in the three axes for different phone vulnerable position. From the data obtained appropriate features are extracted using various feature extraction techniques. The extracted features are then given to classifier such as neural network to classify them and decide whether the phone is in a vulnerable position to fall or it is in a safe position .In this paper we mainly concentrated on various case of handling the smartphone and classified by training the neural network. Keywords— variance, zero crossing rate, fast Fourier transform, pattern net neural network, fit net neural network, Cascade neural network.
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ورودعنوان ژورنال:
- CoRR
دوره abs/1802.04252 شماره
صفحات -
تاریخ انتشار 2017