# Analysis of pedestrian behaviors through non-invasive Bluetooth monitoring

## TL;DR

This study uses non-invasive Bluetooth detection to analyze pedestrian behavior patterns in Barcelona's historic shopping district, revealing increased exploration during sales periods through large-scale data analysis.

## Contribution

It introduces a large-scale Bluetooth-based monitoring method to study pedestrian behaviors, providing insights into mobility patterns during sales periods.

## Key findings

- Pedestrians explore wider areas during discount periods.
- Bluetooth detection captures large-scale behavioral data.
- Mobility patterns vary significantly before, during, and after sales.

## Abstract

This paper analyzes pedestrians' behavioral patterns in the pedestrianized shopping environment in the historical center of Barcelona, Spain. We employ a Bluetooth detection technique to capture a large-scale dataset of pedestrians' behavior over a one-month period, including during a key sales period. We focused on comparing particular behaviors before, during, and after the discount sales by analyzing this large-scale dataset, which is different but complementary to the conventionally used small-scale samples. Our results uncover pedestrians actively exploring a wider area of the district during a discount period compared to weekdays, giving rise to strong underlying mobility patterns.

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Source: https://tomesphere.com/paper/1702.00546