Custom Dual Transportation Mode Detection by Smartphone Devices Exploiting Sensor Diversity

by   Claudia Carpineti, et al.

Making applications aware of the mobility experienced by the user can open the door to a wide range of novel services in different use-cases, from smart parking to vehicular traffic monitoring. In the literature, there are many different studies demonstrating the theoretical possibility of performing Transportation Mode Detection (TMD) by mining smart-phones embedded sensors data. However, very few of them provide details on the benchmarking process and on how to implement the detection process in practice. In this study, we provide guidelines and fundamental results that can be useful for both researcher and practitioners aiming at implementing a working TMD system. These guidelines consist of three main contributions. First, we detail the construction of a training dataset, gathered by heterogeneous users and including five different transportation modes; the dataset is made available to the research community as reference benchmark. Second, we provide an in-depth analysis of the sensor-relevance for the case of Dual TDM, which is required by most of mobility-aware applications. Third, we investigate the possibility to perform TMD of unknown users/instances not present in the training set and we compare with state-of-the-art Android APIs for activity recognition.


EnTrans:Leveraging Kinetic Energy Harvesting Signal for Transportation Mode Detection

Monitoring the daily transportation modes of an individual provides usef...

Transportation Modes Classification Using Feature Engineering

Predicting transportation modes from GPS (Global Positioning System) rec...

Mobile Sensor Data Anonymization

Data from motion sensors such as accelerometers and gyroscopes embedded ...

Smart Web Services (SmartWS) -- The Future of Services on the Web

The past few years have been marked by an increased use of sensor techno...

Please sign up or login with your details

Forgot password? Click here to reset