Abstract
Recently, there have been a wide range of mobile computing and crowd-sourcing applications that leverage the proliferating sensing capabilities of smartphones. Many of these place a paramount importance on accurate user heading estimation. Such applications include dead-reckoning-based localization and many crowd-sensing applications where the user typically carry her phone in arbitrary positions and orientations relative to her body and her transportation mode. However, there is no general solution available to estimate the user’s heading as current state-of-the-art focus on improving the phone orientation estimation, require the phone to be placed in a particular position, require a fixed transportation mode, require user intervention, and/or do not work accurately indoors. In this paper we present Humaine, a novel ubiquitous system that reliably and accurately estimates the user orientation relative to the Earth coordinate system. Humaine works accurately whether the user is riding a vehicle or walking indoors/outdoors for arbitrary cell phone positions and orientations relative to the user body. Moreover, it requires no prior-configuration nor user intervention. The system intelligently fuses the different inertial sensors widely available in off-the-shelf smartphones and employs statistical analysis techniques to their measurements to estimate the user orientation. Implementation of the system on different Android devices with 300 experiments performed at different indoor and outdoor testbeds shows that Humaine significantly outperforms the state-of-the-art in diverse scenarios, achieving a median accuracy of 14∘ and 16∘ for indoor and outdoor pedestrian users and 20∘ for in-vehicle users over a wide variety of phone positions. This is better than the-state-of-the-art by 523% and 594% for indoor and outdoor pedestrian users and 750% for in-vehicle users. This accuracy highlights the ubiquity of Humaine and its robustness against the various noise sources.
Similar content being viewed by others
Notes
An earlier version of this paper appeared in the proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services 2014 (MobiQuitous’14).
References
Abadi M J, Luceri L, Hassan M, Chou C T, Nicoli M (2014) A collaborative approach to heading estimation for smartphone-based pdr indoor localisation IPIN. IEEE
Abdelnasser H, Mohamed R, Elgohary A, Farid M, Wang H, Sen S, Choudhury R, Youssef M (2015) Semanticslam: Using environment landmarks for unsupervised indoor localization. IEEE Trans Mob Comput
Aly H et al (2015) semMatch: Road semantics-based accurate map matching for challenging positioning data ACM SIGSPATIAL
Mohamed R et al (2014) Accurate and efficient map matching for challenging environments ACM SIGSPATIAL
Aly H, Youssef M (2013) Dejavu: an accurate energy-efficient outdoor localization system SIGSPATIAL. ACM
Aly H, Basalamah A, Youssef M (2014) Map++: A crowd-sensing system for automatic map semantics identification SECON. IEEE
Aly H, Basalamah A, Youssef M (2015) Lanequest: an accurate and energy-efficient lane detection system 2015 IEEE International conference on pervasive computing and communications (PerCom). IEEE, pp 163–171
Aly H, Basalamah A, Youssef M (2015) Robust and ubiquitous smartphone-based lane detection. Pervasive Mob Comput
Alzantot M, Youssef M (2012) Crowdinside: automatic construction of indoor floorplans ACM SIGSPATIAL GIS
Alzantot M, Youssef M (2012) Uptime: Ubiquitous pedestrian tracking using mobile phones WCNC. IEEE
Beauregard S (2007) Omnidirectional pedestrian navigation for first responders Proceedings of workshop on positioning navigation and communication. IEEE
Blum J R, Greencorn D, Cooperstock JR (2012) Smartphone sensor reliability for augmented reality applications MobiQuitous
Combettes C, Renaudin V (2015) Comparison of misalignment estimation techniques between handheld device and walking directions International conference on indoor positioning and indoor navigation (IPIN). IEEE, pp 1–8
Constandache I, Choudhury R R, Rhee I (2010) Compacc: Using mobile phone compasses and accelerometers for localization. INFOCOM
Constandache I, Choudhury R R, Rhee I (2010) Towards mobile phone localization without war-driving INFOCOM. IEEE
Cui Y, Ge SS (2003) Autonomous vehicle positioning with gps in urban canyon environments. IEEE Trans Robot Autom
Deng Z A, Wang G, Hu Y, Wu D (2015) Heading estimation for indoor pedestrian navigation using a smartphone in the pocket. Sensors 15(9):21,518–21,536
Goldstein H (1980) Classical mechanics, Addison-Wesley
Hamilton W, Hamilton W (1866) Elements of quaternions. Green, & Company, Longmans
Hemminki S, Nurmi P, Tarkoma S (2013) Accelerometer-based transportation mode detection on smartphones Proceedings of the 11th ACM conference on embedded networked sensor systems. ACM, p 13
Hofmann-Wellenhof B, Lichtenegger H, Collins J (1993) Global Positioning System: Theory and Practice. Springer
Hoseinitabatabaei S A, Gluhak A, Tafazolli R (2011) Udirect: A novel approach for pervasive observation of user direction with mobile phones PerCom. IEEE
Hoseinitabatabaei S A, Gluhak A, Tafazolli R, Headley W (2014) Design, realization, and evaluation of udirect–an approach for pervasive observation of user facing direction on mobile phones. IEEElTMC
Hu S, Su L, Li S, Wang S, Pan C, Gu S, Al Amin M T, Liu H, Nath S, Choudhury R R et al (2015) Experiences with enav: a low-power vehicular navigation system Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 433–444
Jiang Z, Liu C, Zhang G, Wang Y, Huang C, Liang J (2013) Gps/ins integrated navigation based on ukf and simulated annealing optimized svm 2013 IEEE 78th vehicular technology conference (VTC Fall). IEEE, pp 1–5
Kourogi M, Kurata T (2003) A method of personal position-ing based on sensor data fusion of wearable camera and self-contained sensors IEEE international conference on multisensor fusion and integration for intelligent system
Kourogi M, Kurata T (2003) Personal positioning based on walking locomotion analysis with self-contained sensors and a wearable camera International symposium on mixed and augmented reality. IEEE
Kourogi M, Kuratta T (2003) A wearable augmented reality system with personal positioning based on walking locomotion analysis ISMAR. IEEE
Kunze K, Lukowicz P, Partridge K, Begole B (2009) Which way am i facing: Inferring horizontal device orientation from an accelerometer signal International symposium on wearable comps. IEEE
Li F, Zhao C, Ding G, Gong J, Liu C, Zhao F (2012) A reliable and accurate indoor localization method using phone inertial sensors Ubicomp. ACM
Merrill R T, McElhinny W, McFadden P (1998) The magnetic field of the earth: paleomagnetism, the core and the deep mantle. International geophysics series, Academic Press
Mohamed R, Aly H, Youssef M (2016) Accurate real-time map matching for challenging environments IEEE T-ITS
Oshman Y et al (1985) Attitude determination from vector observations: Quaternion estimation. IEEE Trans Aerosp Electron Syst 1:128–136
Qian J, Ma J, Ying R, Liu P, Pei L (2013) An improved indoor localization method using smartphone inertial sensors International conference on indoor positioning and indoor navigation (IPIN). IEEE, pp 1–7
Renaudin V, Combettes C (2014) Magnetic, acceleration fields and gyroscope quaternion (magyq)-based attitude estimation with smartphone sensors for indoor pedestrian navigation. Sensors 14(12):22,864–22,890
Roy N, Wang H, Choudhury R R (2014) I am a smartphone and i can tell my user’s walking direction Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services. ACM, pp 329–342
Schall G (2013) Mobile Computing: Mobile Augmented Reality for Human Scale Interaction with Geospatial Models: the Benefit for Industrial Applications. Springer
Steinhoff U, Schiele B (2010) Dead reckoning from the pocket-an experimental study PerCom. IEEE
Sun Z (2012) Polaris: getting accurate indoor orientations for mobile devices using ubiquitous visual patterns on ceilings. ACM HotMobile
Sun Z, Pan S, Su Y C, Zhang P (2013) Headio: zero-configured heading acquisition for indoor mobile devices through multimodal context sensing. ACM, UbiComp
Wang H, Sen S, Elgohary A, Farid M, Youssef M, Choudhury R R (2012) No need to war-drive: Unsupervised indoor localization MobiSys. ACM
Wang Q, Zhang X, Chen X, Chen R, Chen W, Chen Y (2010) A novel pedestrian dead reckoning algorithm using wearable emg sensors to measure walking strides UPINLBS. IEEE
Youssef M, Yosef M A, El-Derini M (2010) Gac: Energy-efficient hybrid gps-accelerometer-compass gsm localization GLOBECOM. IEEE
Zhang L, Tiwana B, Qian Z, Wang Z, Dick R P, Mao Z M, Yang L (2010) Accurate online power estimation and automatic battery behavior based power model generation for smartphones IEEE/ACM/IFIP International Conference CODES+ISSS
Zhang M, Sawchuk A A (2012) Motion primitive-based human activity recognition using a bag-of-features approach ACM SIGHIT international health informatics symposium
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mohssen, N., Momtaz, R., Aly, H. et al. Humaine: a ubiquitous smartphone-based user heading estimation for mobile computing systems. Geoinformatica 21, 519–548 (2017). https://doi.org/10.1007/s10707-017-0300-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10707-017-0300-7