Mago
Autor: | Jonathan Huang, Ke-Yu Chen, Rahul C. Shah, Lama Nachman |
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Rok vydání: | 2017 |
Předmět: |
Engineering
Modality (human–computer interaction) Computer Networks and Communications business.industry Frame (networking) Wearable computer 020206 networking & telecommunications 02 engineering and technology Transmission system Accelerometer Signal Human-Computer Interaction Transmission (telecommunications) Hardware and Architecture Position (vector) 020204 information systems 0202 electrical engineering electronic engineering information engineering business Simulation |
Zdroj: | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 1:1-23 |
ISSN: | 2474-9567 |
Popis: | In this paper, we introduce Mago, a novel system that can infer a person's mode of transport (MOT) using the Hall-effect magnetic sensor and accelerometer present in most smart devices. When a vehicle is moving, the motions of its mechanical components such as the wheels, transmission and the differential distort the earth's magnetic field. The magnetic field is distorted corresponding to the vehicle structure (e.g., bike chain or car transmission system), which manifests itself as a strong signal for sensing a person's transportation modality. We utilize this magnetic signal combined with the accelerometer and design a robust algorithm for the MOT detection. In particular, our system extracts frame-based features from the sensor data and can run in nearly real-time with only a few seconds of delay. We evaluated Mago using over 70 hours of daily commute data from 7 participants and the leave-one-out analysis of our cross-user, cross-device model reports an average accuracy of 94.4% among seven classes (stationary, bus, bike, car, train, light rail and scooter). Besides MOT, our system is able to reliably differentiate the phone's in-car position at an average accuracy of 92.9%. We believe Mago could potentially benefit many contextually-aware applications that require MOT detection such as a digital personal assistant or a life coaching application. |
Databáze: | OpenAIRE |
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