Smartphone-based Indoor Navigation for Guidance in Finding Location Buildings Using Measured WiFi-RSSI

Liliek Triyono - Politeknik Negeri Semarang, Semarang, Indonesia
- Prayitno - Politeknik Negeri Semarang, Semarang, Indonesia
Mosiur Rahaman - Asia University, Taichung City 413, Taiwan
- Sukamto - Politeknik Negeri Semarang, Semarang, Indonesia
Amran Yobioktabera - Politeknik Negeri Semarang, Semarang, Indonesia

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This study investigates a Wi-Fi-based indoor navigation system to determine building locations. The system was developed using the fingerprint method from the Received Signal Strength Indication (RSSI) of each Access Point (AP). The main components of a smartphone-based system use data from Wi-Fi and the Global Positioning System (GPS). The system developed for navigation is designed and implemented as an element of a dynamic, seamless mobility planning and building location route guidance application. Building map data is collected from Google Map data and enhanced by coloring the geographic location of buildings displayed on mobile devices. Navigational aids collected from sensors provide trip orientation and position updates. The approach of measuring the distance between known positions is compared to those displayed in the application with the haversine formula to measure the accuracy of the position displayed. A series of experiments were conducted in the Politeknik Negeri Semarang area, Indonesia. The experiment results showed that the Wi-Fi-based indoor positioning system was accurate within 7.050 meters of the error for that location, thus proving the system's usefulness for determining the location of buildings in the campus area. The measurement has not adopted the maximum APs placement for signal coverage and strength, only using the existing APs positions. The temperature nor humidity was neither measured in each area where the AP was installed, which is discussed later. This system can help visitors without asking, even though they have only visited once.


Navigation; RSSI; positioning; smartphone; wireless technologies.

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I. Garcia and B. Sampaio, “Feature selection on database optimization for Wi-Fi fingerprint indoor positioning,†in 23rd International Conference on Knowledge-Based and Intelligent Information & Engineering 23rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 2019, vol. 00, doi: 10.1016/j.procs.2019.09.180.

A. K. Panja, S. F. Karim, S. Neogy, and C. Chowdhury, “A novel feature based ensemble learning model for indoor localization of smartphone users,†Eng. Appl. Artif. Intell., vol. 107, no. December 2020, p. 104538, 2022, doi: 10.1016/j.engappai.2021.104538.

P. Taylor, W. S. Jang, and M. J. Skibniewski, “A wireless network system for automated tracking of construction materials on project sites,†no. October 2014, pp. 37–41, 2010, doi: 10.3846/1392-3730.2008.14.11-19.

A. Guidara, G. Fersi, M. Ben, and F. Derbel, “Ad Hoc Networks A new deep learning-based distance and position estimation model for range-based indoor localization systems,†Ad Hoc Networks, vol. 114, no. January, p. 102445, 2021, doi: 10.1016/j.adhoc.2021.102445.

E. Hu, Z. Deng, M. Hu, L. Yin, and W. Liu, “Cooperative indoor positioning with factor graph based on FIM for wireless sensor network,†Futur. Gener. Comput. Syst., vol. 89, pp. 126–136, 2018, doi: 10.1016/j.future.2018.05.035.

J. Noonan, H. Rotstein, A. Geva, and E. Rivlin, “Global monocular indoor positioning of a robotic vehicle with a floorplan,†Sensors (Switzerland), vol. 19, no. 3, pp. 1–8, 2019, doi: 10.3390/s19030634.

J. Kunhoth, A. G. Karkar, S. Al-Maadeed, and A. Al-Ali, “Indoor positioning and wayfinding systems: a survey,†Human-centric Comput. Inf. Sci., vol. 10, no. 1, 2020, doi: 10.1186/s13673-020-00222-0.

N. M. Tiglao, M. Alipio, R. Dela Cruz, F. Bokhari, S. Rauf, and S. A. Khan, “Smartphone-based indoor localization techniques: State-of-the-art and classification,†Meas. J. Int. Meas. Confed., vol. 179, no. November 2020, p. 109349, 2021, doi: 10.1016/j.measurement.2021.109349.

V. Hromadová, J. Machaj, and P. Brída, “Impact of user orientation on indoor localization based on Wi-Fi,†Transp. Res. Procedia, vol. 55, no. 2019, pp. 882–889, 2021, doi: 10.1016/j.trpro.2021.07.056.

T. Janssen, R. Berkvens, and M. Weyn, “Benchmarking RSS-based localization algorithms with LoRaWAN,†Internet of Things (Netherlands), vol. 11, no. 1, p. 100235, 2020, doi: 10.1016/j.iot.2020.100235.

M. A. Nassar et al., “Wifi-based localisation datasets for No-GPS open areas using smart bins,†Comput. Networks, vol. 180, no. February, 2020, doi: 10.1016/j.comnet.2020.107422.

J. Chen, S. Song, and H. Yu, “An indoor multi-source fusion positioning approach based on PDR/MM/Wi-Fi,†AEU - Int. J. Electron. Commun., vol. 135, no. November 2020, p. 153733, 2021, doi: 10.1016/j.aeue.2021.153733.

S. Subedi and J. Y. Pyun, “A survey of smartphone-based indoor positioning system using RF-based wireless technologies,†Sensors (Switzerland), vol. 20, no. 24, pp. 1–32, 2020, doi: 10.3390/s20247230.

A. Guidara, G. Fersi, F. Derbel, and M. Ben Jemaa, “Impacts of Temperature and Humidity variations on RSSI in indoor Wireless Sensor Networks,†Procedia Comput. Sci., vol. 126, pp. 1072–1081, 2018, doi: 10.1016/j.procS.2018.08.044.

H. Rizk, M. Abbas, and M. Youssef, “Device-independent cellular-based indoor location tracking using deep learning,†Pervasive Mob. Comput., vol. 75, p. 101420, 2021, doi: 10.1016/j.pmcj.2021.101420.

Y. C. Lee, “SRS: Spatial-tagged radio-mapping system combining LiDAR and mobile-phone data for indoor location-based services,†Adv. Eng. Informatics, vol. 52, no. August 2021, 2022, doi: 10.1016/j.aei.2022.101560.

K. Al Nuaimi, A. Ain, and A. Ain, “A Survey of Indoor Positioning Systems and Algorithms,†pp. 185–190, 2011.

J. Xiao, Z. Zhou, Y. Yi, and L. M. Ni, “A Survey on Wireless Indoor Localization from the Device Perspective,†vol. 49, no. 2, 2016.

B. Murdyantoro, D. S. E. Atmaja, and H. Rachmat, “Application design of farmbot based on Internet of Things (IoT),†Int. J. Adv. Sci. Eng. Inf. Technol., vol. 9, no. 4, pp. 1163–1170, 2019, doi: 10.18517/ijaseit.9.4.9483.

C. Laoudias, A. Moreira, S. Kim, S. Lee, L. Wirola, and C. Fischione, “A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation,†IEEE Commun. Surv. Tutorials, vol. PP, no. c, p. 1, 2018, doi: 10.1109/COMST.2018.2855063.

M. Grossi, “A sensor-centric survey on the development of smartphone measurement and sensing systems,†measurement, no. December, 2018, doi: 10.1016/j.measurement.2018.12.014.

C. T. Li, J. C. P. Cheng, and K. Chen, “Automation in Construction Top 10 technologies for indoor positioning on construction sites,†Autom. Constr., vol. 118, no. June, p. 103309, 2020, doi: 10.1016/j.autcon.2020.103309.

R. Otero, S. Lagüela, I. Garrido, and P. Arias, “Automation in Construction Mobile indoor mapping technologies : A review,†vol. 120, no. August, 2020, doi: 10.1016/j.autcon.2020.103399.

K. A. Kordi, A. Alhammadi, M. Roslee, M. Y. Alias, and Q. Abdullah, “A Review on Wireless Emerging IoT Indoor Localization,†pp. 82–87, 2020.

R. C. Shit, “Precise Localization for Achieving Next-Generation Autonomous Navigation: State-of-the-Art, Taxonomy and Future Prospects,†Comput. Commun., 2020, doi: 10.1016/j.comcom.2020.06.007.

N. Hernández et al., “WiFiNet: WiFi-based indoor localisation using CNNs,†Expert Syst. Appl., vol. 177, 2021, doi: 10.1016/j.eswa.2021.114906.

Y. Tian, B. Huang, B. Jia, and L. Zhao, “Optimizing AP and Beacon Placement in Wi-Fi and BLE hybrid localization,†J. Netw. Comput. Appl., vol. 164, no. April, 2020, doi: 10.1016/j.jnca.2020.102673.

Z. A. Deng, Z. Qu, C. Hou, W. Si, and C. Zhang, “Wi-Fi positioning based on user orientation estimation and smartphone carrying position recognition,†Wirel. Commun. Mob. Comput., vol. 2018, 2018, doi: 10.1155/2018/5243893.

S. Woo et al., “Application of WiFi-based indoor positioning system for labor tracking at construction sites: A case study in Guangzhou MTR,†Autom. Constr., vol. 20, no. 1, pp. 3–13, 2011, doi: 10.1016/j.autcon.2010.07.009.

A. K. M. M. Hossain and W. Soh, “A survey of calibration-free indoor positioning systems,†Comput. Commun., 2015, doi: 10.1016/j.comcom.2015.03.001.

Navigine, “Navigine | Universal Platform for Navigation,†, 2021. .

A. Alsudais, W. Alotaibi, and F. Alomary, “Similarities between Arabic dialects : Investigating geographical proximity,†Inf. Process. Manag., vol. 59, no. 1, p. 102770, 2022, doi: 10.1016/j.ipm.2021.102770.