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An Automatized Contextual Marketing System Based on a Wi-Fi Indoor Positioning System.

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A new location-as-a-service (LAAS) methodology enables rapid deployment of indoor positioning systems (IPS) for smartphones in large venues like malls. This robust and scalable solution achieves shop-level accuracy for contextual marketing.

Keywords:
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Area of Science:

  • Computer Science
  • Engineering
  • Geographic Information Science

Background:

  • Contextual marketing requires precise user location data within large indoor spaces.
  • Existing indoor positioning systems (IPS) often lack scalability and ease of deployment.
  • Large infrastructures like malls present unique challenges for accurate indoor navigation.

Purpose of the Study:

  • To propose and evaluate a complete contextual marketing platform centered on an indoor positioning system (IPS).
  • To develop a novel location-as-a-service (LAAS) methodology for efficient IPS generation and deployment.
  • To compare the performance of different fingerprint location algorithms for smartphone-based IPS.

Main Methods:

  • Designed and implemented a LAAS methodology covering mall digital map creation, fingerprint acquisition, and location algorithms.
  • Compared K-nearest neighbors (KNN), support vector machine (SVM), and Freeloc algorithms using diverse smartphones and occupancy levels in two malls.
  • Developed a smartphone application for acquiring fingerprint data and a validation procedure for system assessment.

Main Results:

  • The proposed LAAS methodology facilitates quick deployment of IPS at shop-level accuracy in new locations.
  • The system demonstrated robustness and scalability across different smartphones and varying occupancy levels.
  • Algorithm comparison provided insights into optimal fingerprint location strategies for indoor positioning.

Conclusions:

  • The developed contextual marketing platform with its IPS is a robust and scalable solution for large infrastructures.
  • The LAAS approach simplifies and accelerates the deployment of accurate indoor positioning.
  • The findings support the practical application of this IPS for enhanced marketing and navigation in malls.