11th EAI International Conference on Mobile Multimedia Communications

Research Article

Smartphone Internal Sensor-based Offline Displacement Estimation and An iOS App Development

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  • @INPROCEEDINGS{10.4108/eai.21-6-2018.2276641,
        author={Qingzhong Liu and James Taylor},
        title={Smartphone Internal Sensor-based Offline Displacement Estimation and An iOS App Development},
        proceedings={11th EAI International Conference on Mobile Multimedia Communications},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2018},
        month={9},
        keywords={dead reckoning; gps; magnetometer; ios iphone},
        doi={10.4108/eai.21-6-2018.2276641}
    }
    
  • Qingzhong Liu
    James Taylor
    Year: 2018
    Smartphone Internal Sensor-based Offline Displacement Estimation and An iOS App Development
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.21-6-2018.2276641
Qingzhong Liu1,*, James Taylor1
  • 1: Sam Houston State University
*Contact email: liuqzsc@gmail.com

Abstract

GPS, cell towers, Wi-Fi access points and beacons each can be used to determine location of a cellphone. However, each is an external piece of hardware to the cellphone, and each has limitations to the quality of service provided. For example, GPS signals can be compromised by a number of events - including solar activity, man-made interference and malicious faking of GPS signals [1]. As an alternative, an app can be made using only sensors internal to the phone. This paper details our iOS app for offline displacement estimation by only using common cellphone sensors such as the accelerometer and magnetometer, without any WiFi and GPS signals, to estimate a user’s location as they walk to any desired location. This research demonstrates the use of a modern approach to dead reckoning. The results show that the error in estimation using this approach can vary from 6cm to 15cm for every meter walked, with increasing inaccuracy for more intense activities.