(2025) Campelo, Ananda Julia Galvão; Shinohara, Kevin Nagayuki; Machado, Luca Cazzolato; Sousa, Thiago Gonçalves Guadagnoli de
Supermarkets and large retailers strive to understand customer flow to optimize store layouts
and increase sales. While technologies like SLAM and smartphone data crowdsourcing
have been explored for indoor mapping, the specific context of supermarkets and the
use of high-precision technologies such as Ultra-Wideband (UWB) remain largely underexplored.
This project proposes the creation of supermarket maps using the trajectories
of shopping carts tracked by UWB, a technology that offers greater spatial accuracy than
methods based on Wi-Fi or Bluetooth. The proposal also includes generating heatmaps
that visualize the frequency of cart movement. The ongoing methodology addresses outlier
treatment through data cleaning, trajectory rasterization, and the concept of density
matrices. The generated maps are expected to be accurate representations of the supermarket’s
floor plan, and the density heatmaps should precisely translate customer flow
within each sector. The proposed solution serves as a basis for an Indoor Positioning
System (IPS), consumer behavior analysis, and shopping route optimization.
