Projecte assignat
Títol: Design and Implementation of a Cross-Platform Indoor Positioning System based on Wi-Fi RTT and Fingerprinting
Director/a: ZOLA, ENRICA VALERIA
Departament: ENTEL
Títol: Design and Implementation of a Cross-Platform Indoor Positioning System based on Wi-Fi RTT and Fingerprinting
Data inici oferta: 26-06-2026 Data finalització oferta: 26-02-2027
Estudis d'assignació del projecte:
GR ENG SIS TELECOMUN- GR ENG TELEMÀTICA
| Tipus: Individual | |
| Lloc de realització: EETAC | |
| Segon director/a (UPC): MARTIN ESCALONA, ISRAEL | |
| Paraules clau: | |
| IEEE 802.11, Indoor positioning, Wi-Fi RTT, Cross-platform implementation | |
| Descripció del contingut i pla d'activitats: | |
| Indoor Positioning Systems (IPS) have been the subject of intense research for decades due to the ineffectiveness of satellite systems (such as GPS) inside buildings. Traditional solutions based on Bluetooth Low Energy (BLE) beacons or Ultra-Wideband (UWB) require the deployment of dedicated and expensive hardware. However, the development of the IEEE 802.11mc standard has equipped modern Wi-Fi networks with the ability to estimate distances between devices with high precision using the time-of-flight technique, or Wi-Fi RTT (Round-Trip Time). This meets a long-awaited demand without the need for infrastructure other than the access points (APs) themselves.
Recent research shows that combining Wi-Fi RTT measurements with signal fingerprinting techniques allows for highly accurate user localization using a very small number of access points. This mitigates the AP density problem required in purely trilateration-based systems, significantly favoring scalability and reducing the deployment costs of the localization system. The fundamental objective of this project is the design and implementation of a cross-platform fingerprinting-based positioning system that utilizes Wi-Fi RTT technology. The system must be comprehensive, covering the entire data lifecycle: from the collection of field measurements, through the algorithmic calculation of the position on the server or device, to the real-time visualization of the user's location. The resulting ecosystem must be capable of operating and being visualized in, at least, Web environments and Android mobile devices, thus ensuring its cross-platform accessibility. OBJECTIVES General Objective: To develop a cross-platform indoor positioning system (Web and Android) that combines Wi-Fi RTT technology with fingerprinting techniques to achieve high algorithmic accuracy with a low density of access points. Specific Objectives - State of the Art: Evaluate the performance, architectures, and capabilities of current open-source indoor positioning systems (e.g., OpenHPS and Anyplace), identifying their strengths, limitations, and suitability for integration with a Wi-Fi RTT-based positioning system. - Architecture Design: Design the technical architecture of the Wi-Fi RTT positioning system proposed in [1], including the communication interfaces required to enable interaction among its components. This design will determine whether the system should be developed from scratch or integrated as a module within one of the previously evaluated platforms. - Data Collection Module (Fingerprinting): Develop a client-side tool for collecting Wi-Fi RTT measurements and generating the fingerprinting data required for positioning. - Positioning Engine: Implement the positioning model defined in [1], enabling the comparison of real-time Wi-Fi RTT measurements against the previously generated radio map to estimate the user's position with high accuracy. - Visualization Module: Develop graphical user interfaces for Web and Android environments that display an indoor map of the target building and the real-time location of the tracked device. - Validation and Testing: Deploy the system in a real-world test environment, evaluate its positioning accuracy (in meters) and overall performance, and document the experimental results. [1] N. G. Diaz, E. Zola and I. Martin-Escalona, "A Novel Framework for Scalable and Low-Complexity Wi-Fi RTT Positioning for IoT Devices," in IEEE Internet of Things Journal, vol. 13, no. 7, pp. 14188-14202, 11 April, 2026, doi: 10.1109/JIOT.2025.3648310. |
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| Orientació a l'estudiant: | |
| - Understanding of network architectures and fundamentals of Wi-Fi protocols (IEEE 802.11 family).
- Advanced level in languages such as Python and/or JavaScript/TypeScript. |
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| Requereix activitats hardware: No | |
| Requereix activitats software: Sí Sistema operatiu: Disc (Gb): | |
| Horari d'atenció a estudiants per a l'assignació de projecte: Send me an email (enrica.zola@upc.edu) |
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