Research on material identification of mobile phones falling to the ground

TL;DR

This paper introduces a neural network-based method to identify ground materials during mobile phone falls using accelerometer data, achieving a 96.75% accuracy without extra devices.

Contribution

It presents a novel approach leveraging accelerometer data and neural networks to identify ground materials during phone falls, filling a research gap.

Findings

Average identification rate of 96.75% for different ground materials

Method relies solely on built-in accelerometer data

Effective in analyzing mobile phone fall damage mechanisms

Abstract

The failure mode of the phone falling has a lot to do with the ground material. At present, the research on ground material and mobile phone damage is generally carried out through experiments, which is extremely costly. This paper presents a method to identify the material of mobile phones falling on the ground. The method determines the material of the mobile phone falling to the ground according to the data of the mobile phone accelerometer and can obtain the ground material of the mobile phone falling through a large number of user data. By analyzing the physical process of mobile phone falling, the accelerometer data interval which can reflect the characteristics of falling is reasonably intercepted. And the data features that can reflect the collision are extracted. Finally, based on the fully connected neural network, the method of determining the material of mobile phones falling on the ground is developed. The experimental results show that the method has a high identification rate, and the average identification rate for different ground materials is 96.75%. Instead of relying on auxiliary devices, the identification process only relies on the phone's built-in acceleration sensor. This paper fills the gap in the field of mobile phone falling ground material identification. It has a great contribution to the collection of user drop data, the analysis of the drop process, and the improvement of mobile phone design defects.