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

A complete contextual marketing platform including an indoor positioning system (IPS) for smartphones is proposed and evaluated to later be deployed in large infrastructures, such as malls. To this end, we design and implement a novel methodology based on location-as-a-service (LAAS), comprising all...

Full description

Saved in:
Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-05, Vol.21 (10), p.3495
Main Authors: López-Pastor, José-Antonio, Ruiz-Ruiz, Antonio-Jesús, García-Sánchez, Antonio-Javier, Gómez-Tornero, José-Luis
Format: Article
Language:English
Subjects:
Accuracy
Advertising campaigns
Algorithms
area-level positioning
contextual marketing
Customer relationship management
Customer services
Data acquisition
Digital mapping
Fingerprints
indoor location system
Infrastructure
Marketing
Occupancy
Radio frequency identification
Sensors
smartphone location
Smartphones
Support vector machines
Wi-Fi fingerprint
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A complete contextual marketing platform including an indoor positioning system (IPS) for smartphones is proposed and evaluated to later be deployed in large infrastructures, such as malls. To this end, we design and implement a novel methodology based on location-as-a-service (LAAS), comprising all the required phases of IPS generation: mall digital map creation, the tools/procedures for offline calibration fingerprint acquisition, the location algorithm, the smartphone app acquiring the fingerprint data, and a validation procedure. To select an appropriate fingerprint location algorithm, a comparison among K-nearest neighbors (KNN), support vector machine (SVM), and Freeloc is accomplished by employing a set of different smartphones in two malls and assessing different occupancy levels. We demonstrate that our solution can be quickly deployed at shop level accuracy in any new location, resulting in a robust and scalable proposal.
ISSN:1424-8220
1424-8220
DOI:10.3390/s21103495