Readers who are interested in delving further into the field of indoor positioning would do well to explore the following articles:
- C. Feng et al., "Received-Signal-Strength-Based Indoor Positioning Using Compressive Sensing," IEEE Trans. Mobile Computing, Dec. 2012, pp. 1983–1993; http://doi.ieeecomputersociety.org/10.1109/TMC.2011.216.
- P.M. Dudas, M. Ghafourian, and H.A. Karimi, "ONALIN: Ontology and Algorithm for Indoor Routing," Proc. IEEE Int'l Conf. Mobile Data Management, 2009, pp. 720–725; http://doi.ieeecomputersociety.org/10.1109/MDM.2009.123.
- C. Fischer and H. Gellersen, "Location and Navigation Support for Emergency Responders: A Survey," IEEE Pervasive Computing, Jan./Mar. 2010, pp. 38–47; http://doi.ieeecomputersociety.org/10.1109/MPRV.2009.91.
- H. Vathsangam, A. Tulsyan, and G.S. Sukhatme, "A Data-Driven Movement Model for Single Cellphone-Based Indoor Positioning," Int'l Workshop on Wearable and Implantable Body Sensor Networks, 2011, pp. 174–179; http://doi.ieeecomputersociety.org/10.1109/BSN.2011.33.
- Hua Lu,Xin Cao,Christian S. Jensen, "A Foundation for Efficient Indoor Distance-Aware Query Processing," Proc. IEEE Int'l Conf. Data Engineering, 2012, pp. 438–449; http://doi.ieeecomputersociety.org/10.1109/ICDE.2012.44.
- A. Mulloni et al., "Indoor Positioning and Navigation with Camera Phones," IEEE Pervasive Computing, April/June 2009, pp. 22–31; http://doi.ieeecomputersociety.org/10.1109/MPRV.2009.30.
- I. D'Souza, W. Ma, and C. Notobartolo, "Real-Time Location Systems for Hospital Emergency Response," IT Professional, Mar/Apr 2011, pp. 37–43; http://doi.ieeecomputersociety.org/10.1109/MITP.2011.31.
- B. Hagedorn et al., "Towards an Indoor Level-of-Detail Model for Route Visualization," Proc. IEEE Int'l Conf. Mobile Data Management, 2009, pp. 692–697; http://doi.ieeecomputersociety.org/10.1109/MDM.2009.118.