Abstract: Mobile technologies, particularly smartphones, have become integral to human life, influencing nearly every aspect of daily activities. Their ubiquity and advanced capabilities have led to them being a solution to a wide range of problems. Recent research has focused on leveraging the existing sensors in smartphones to supplant more costly and less accessible dedicated hardware. In this vein, we introduce MobiScale, a novel system designed to measure the weight of light objects using the built-in accelerometer and vibration motor of smartphones. This system utilizes advanced feature extraction techniques to effectively capture the temporal and spectral characteristics of the weight data. The core of MobiScale is its CNN-LSTM architecture, which processes these features to estimate weights accurately. The implementation of various regularization techniques has been vital in enhancing the system's ability to generalize, thereby improving its performance. Tested across multiple devices and under various conditions, MobiScale has shown consistent and precise performance, achieving a mean square error of just 12 grams in weight estimation, underscoring its potential as a versatile and reliable tool for weight measurement using smartphone technology.
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