A Comparative Approach to Classification of Locomotion and Transportation Modes Using Smartphone Sensor Data
Anindya Das Antar, Masud Ahmed, Mohammad Shadman Ishrak, Md Atiqur Rahman Ahad · 2018
In this paper, we have used a smartphone sensor-based benchmark Sussex-Huawei Locomotion-Transportation (SHL) dataset for rich locomotion and transportation analytics. We have shown a comparison of different sensor-based features for the identification of a specific activity level. Besides, we have proposed a "Mod technique" method, which increases the accuracy of classifier outputs in offline processing method. We have assumed that the minimum switching time from one transportation activity to another is 1-minute as a base of this technique. Based on this assumption we have been able to correct the wrong prediction of the classifier outputs in each 1-minute data frame. Our proposed method brings 4.56% accuracy increase in the Random Forest (RnF) classifier output. Our team, "Confusion Matrix" has developed this algorithm pipeline for the "Sussex-Huawei Locomotion-Transportation (SHL) recognition challenge".