Performance Evaluation of a Deep Learning Model for Time Series Prediction on Android Devices
Rika Sato, Masato Oguchi, Saneyasu Yamaguchi, Takeshi Kamiyama · 2021
In this paper, to verify the feasibility of an application implementation that predicts and controls traffic congestion on Android devices, we embed a deep learning model previously trained on the server side into a verification application using TensorFlow Lite and evaluate its performance by comparing it with the prediction accuracy and processing speed on the server.