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Indoor Positioning App

Project Aim

Develop an indoor positioning app in collaboration with Huawei, utilizing sensor fusion technology to integrate Pedestrian Dead Reckoning (PDR), Wi‑Fi, and GPS data with Particle Filter algorithms, enhancing location accuracy within indoor environments.

Background

High Demand for Indoor Positioning

With increasing applications in navigation, asset tracking, and personalized services, the demand for reliable indoor positioning systems has never been higher.

Application Areas

  1. Retail and Shopping Centres
  2. Airports and Transportation Hubs
  3. Hospitals and Healthcare Facilities

Problem Statement

  1. Single Data Source Limitations
  2. Environmental Interference
  3. Scalability and Flexibility Issues

High Level Application Block Diagram

High Level Application Block Diagram

User Interface

User Interface 1

User Interface 2

User Interface 3

User Interface 4

Fusion Algorithm Comparison

Particle Filter

  • Particle representation of possible positions
  • Convergence to accurate positioning
  • Dynamic sensor weighting

Extended Kalman Filter (EKF)

  • Flexibility with Arbitrary Distributions
  • Robustness to Initial State Uncertainty
  • Computational Efficiency
  • Handling Dynamic Environments

Batch Optimization

  • Computational Efficiency
  • Handling Dynamic Environments