AI Article Synopsis
- The paper explores how to automatically classify sports shop customers based on their movement patterns within the store.
- Customer movements are tracked using coordinates collected every minute, creating a detailed path of their visit.
- This data allows for clustering different types of customers, understanding their in-store behavior, monitoring shop conditions, and predicting busy periods.
Article Abstract
This paper deals with the automatic classification of customers on the basis of their movements around a sports shop center. We start by collecting coordinates from customers while they visit the store. Consequently, any costumer's path through the shop is formed by a list of coordinates, obtained with a frequency of one measurement per minute. A guess about the trajectory is constructed, and a number of parameters are calculated before performing a Clustering Process. As a result, we can identify several types of customers, and the dynamics of their behavior inside the shop. We can also monitor the state of the shop, identify different situations that appear during limited periods of time, and predict peaks in customer traffic.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001414 | PMC |
| http://dx.doi.org/10.3390/s21062007 | DOI Listing |
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