Multi sensor system for pedestrian tracking and activity recognition in indoor environments

Abstract

The widespread use of mobile devices and the rise of Global Navigation Satellite Systems (GNSS) have allowed mobile tracking applications to become very popular and valuable in outdoor environments. However, tracking pedestrians in indoor environments with Global Positioning System (GPS)-based schemes is still very challenging. Along with indoor tracking, the ability to recognize pedestrian behavior and activities can lead to considerable growth in location-based applications including pervasive healthcare, leisure and guide services (such as, hospitals, museums, airports, etc.), and emergency services, among the most important ones. This paper presents a system for pedestrian tracking and activity recognition in indoor environments using exclusively common off-the-shelf sensors embedded in smartphones (accelerometer, gyroscope, magnetometer and barometer). The proposed system combines the knowledge found in biomechanical patterns of the human body while accomplishing basic activities, such as walking or climbing stairs up and down, along with identifiable signatures that certain indoor locations (such as turns or elevators) introduce on sensing data. The system was implemented and tested on Android-based mobile phones. The system detects and counts steps with an accuracy of 97% and 96:67% in flat floor and stairs, respectively; detects user changes of direction and altitude with 98:88% and 96:66% accuracy, respectively; and recognizes the proposed human activities with a 95% accuracy. All modules combined lead to a total tracking accuracy of 91:06% in common human motion indoor displacements