SALA: Smartphone-Assisted Localization Algorithm for Positioning Indoor IoT Devices
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This paper proposes a Smartphone-Assisted Localization Algorithm (SALA) for the localization of Internet of Things (IoT) devices that are placed in indoor environments (e.g., smart home, smart office, smart mall, and smart factory). This SALA allows a smartphone to visually display the positions of IoT devices in indoor environments for the easy management of IoT devices, such as remote-control and monitoring. A smartphone plays a role of a mobile beacon that tracks its own position indoors by a sensor-fusion method with its motion sensors, such as accelerometer, gyroscope, and magnetometer. While moving around indoor, the smartphone periodically broadcasts short-distance beacon messages and collects the response messages from neighboring IoT devices. The response messages contains IoT device information. The smartphone stores the IoT device information in the response messages along with the message’s signal strength and its position into a dedicated server (e.g., home gateway) for the localization. These stored trace data are processed offline through our localization algorithm along with a given indoor layout, such as apartment layout. Through simulations, it is shown that our SALA can effectively localize IoT devices in an apartment with position errors less than 20 cm in a realistic apartment setting.
KeywordsIndoor Localization Algorithm Smartphone IoT Device Trajectory
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2014006438). This work was also partly supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) [10041244, SmartTV 2.0 Software Platform].
- 1.Cook, D. J., Youngblood, M., Heierman, III, E. O., Gopalratnam, K., Rao, S., Litvin, A., & Khawaja, F. (2003). MavHome: An agent-based smart home. In PerCom, Fort Worth, TX, USA, March 2003. IEEE.Google Scholar
- 2.AllJoyn Framework. AllSeen Alliance: A leading internet of things initiative. https://allseenalliance.org/framework.
- 3.Shala, U., & Rodriguez, A.. (2011). Indoor positioning using sensor-fusion in android devices. Technical report, 2011. http://hkr.diva-portal.org/smash/get/diva2:475619/FULLTEXT02.
- 4.Chintalapudi, K., Padmanabha Iyer, A., & Padmanabhan, V. N. (2010). Indoor localization without the pain. ACM Mobicom, September 2010.Google Scholar
- 5.He, X., Badiei, S., Aloi, D., & Li, J. (2013). WiFi iLocate: WiFi based indoor localization for smartphone. In Wireless telecommunications symposium. April 2013.Google Scholar
- 7.Otsason, V., Varshavsky, A., LaMarca, A., & de Lara, E. (2005). Accurate GSM indoor localization. In International conference on ubiquitous computing. September 2005.Google Scholar
- 9.Liu, K., Liu, X., & Li, X. (2013). Guoguo: Enabling fine-grained indoor localization via smartphone. In MobiSys. ACM, June 2013.Google Scholar
- 10.Hsu, H.-H., Peng, W.-J., Shih, T. K., Pai, T.-W., & Man, K. L. (2014). Smartphone indoor localization with accelerometer and gyroscope. In International conference on network-based information systems, September 2014.Google Scholar
- 11.Liu, J., Chen, R., Pei, L., Guinness, R., & Kuusniemi, H. (2012). A hybrid smartphone indoor positioning solution for mobile LBS. In Sensors, December 2012.Google Scholar
- 12.Li, F., Zhao, C., Ding, G., Gong, J., Liu, C., & Zhao, F. (2012). A reliable and accurate indoor localization method using phone inertial sensors. In Proceedings of the 2012 ACM conference on ubiquitous computing, UbiComp ’12, pages 421–430, New York, NY, USA, 2012. ACM.Google Scholar
- 13.Jun, J., Gu, Y.., Cheng, L., Sun, J., Zhu, T., & Niu, J. (2013). Social-Loc: Improving indoor localization with social sensing. In SenSys. ACM, November 2013.Google Scholar
- 14.Priyantha, N. B., Chakraborty, A., & Balakrishnan, H. (2000). The cricket location-support system. In MOBICOM. ACM, August 2000.Google Scholar
- 15.Niculescu, D., & Nath, B. (2003). Ad hoc positioning system (APS) using AOA. In INFOCOM. IEEE, March 2003.Google Scholar
- 17.Chen, H., Sezaki, K., Deng, P., & Cheung So, H. (2008). An improved DV-Hop localization algorithm for wireless sensor networks. IEEE, In ICIEA. June 2008.Google Scholar
- 18.Yu, N., Wan, J., Song, Q., & Wu, Y. (2006). An improved DV-hop localization algorithm in wireless sensor networks. In ICIA. IEEE, August 2006.Google Scholar
- 19.Chen, H., Sezaki, K., Deng, P., & Cheung So, H. (2012). Improved DV-hop localization algorithm for wireless sensor networks. In SISY., IEEE, September 2012.Google Scholar
- 20.Zhong, Z., & He, T. (2009) Achieving range-free localization beyond connectivity. In SenSys, November 2009.Google Scholar
- 21.Zhong, Z., Zhu, T., Wang, D., & He, T. (2009). Tracking with unreliable node sequences. In INFOCOM., IEEE, April 2009.Google Scholar
- 23.Koweerawong, C., Wipusitwarakun, K., & Kaemarungsi, K. (2013). Indoor localization improvement via adaptive RSS fingerprinting database. In ICOIN., IEEE, January 2013.Google Scholar
- 24.Chen, Y., Lymberopoulos, D., Liu, J., & Priyantha, B. (2012). FM-based indoor localization. In MobiSys., ACM, June 2012.Google Scholar
- 25.Matic, A., Papliatseyeu, A., Osmani, V., & Mayora-Ibarra, O. (2010). Tuning to your position: FM radio based indoor localization with spontaneous recalibration. In PerCom., IEEE, March 2010.Google Scholar
- 26.Ruiz-Ruiz, Antonio J., Canovas, Oscar, Rubio Muñoz, Ruben A., & Lopez de Teruel Alcolea, Pedro E. (2012). Using SIFT and WiFi signals to provide location-based services for smartphones. LNICST, 104, 37–48.Google Scholar
- 27.Nirjon, S., Dickerson, R. F., Asare, P., Li, Q., Hong, D., Stankovic, J. A., Hu, P., Shen, G., & Jiang, X. (2013). Auditeur: A mobile-cloud service platform for acoustic event detection on smartphones. In MobiSys., ACM, June 2013.Google Scholar
- 28.Martin, P., Ho, B.-J., Grupen, N., Muñoz, S., & Srivastava, M. (2014). An iBeacon primer for indoor localization. In BuildSys., ACM, November 2014.Google Scholar
- 30.OMNeT++. Discrete Event Simulator for Networks. https://omnetpp.org/.
- 32.Chung, J., Donahoe, M., Schmandt, C., Kim, I.-J., Razavai, P., & Wiseman, M. (2011). Indoor location sensing using geo-magnetism. In Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services, MobiSys ’11, pp.141–154, New York, NY, USA, 2011. ACM.Google Scholar
- 33.Raspberry Pi. IoT Devices. https://www.raspberrypi.org/.