Mining Users' Significant Driving Routes with Low-power Sensors

TL;DR

This paper introduces a passive, low-power route recognition system using smartphone gyroscope and accelerometer data, enabling energy-efficient identification of users' significant routes comparable to GPS-based methods.

Contribution

The study presents a novel passive route sensing framework that reduces energy consumption while maintaining high recognition accuracy, independent of phone orientation and traffic conditions.

Findings

Achieves similar route recognition accuracy as GPS-based methods.

Reduces energy consumption by an order of magnitude.

Works independently of phone orientation and traffic conditions.

Abstract

While there is significant work on sensing and recognition of significant places for users, little attention has been given to users' significant routes. Recognizing these routine journeys, opens doors to the development of novel applications, like personalized travel alerts, and enhancement of user's travel experience. However, the high energy consumption of traditional location sensing technologies, such as GPS or WiFi based localization, is a barrier to passive and ubiquitous route sensing through smartphones. In this paper, we present a passive route sensing framework that continuously monitors a vehicle user solely through a phone's gyroscope and accelerometer. This approach can differentiate and recognize various routes taken by the user by time warping angular speeds experienced by the phone while in transit and is independent of phone orientation and location within the vehicle, small detours and traffic conditions. We compare the route learning and recognition capabilities of this approach with GPS trajectory analysis and show that it achieves similar performance. Moreover, with an embedded co-processor, common to most new generation phones, it achieves energy savings of an order of magnitude over the GPS sensor.