Which machine learning technique was first successfully deployed in 2019 to analyze in-store customer movement patterns without using cameras or personally identifiable information?

Machine learning has revolutionized scientific retail analytics in recent years. Advanced algorithms now help retailers understand customer behavior at unprecedented levels, optimize inventory based on complex variables, and even predict future shopping patterns with remarkable accuracy. This poll tests your knowledge of cutting-edge ML applications that are transforming the science of retail operations.

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Federated WiFi Triangulation Learning (FWTL)
Non-visual Ambient Sensing with Reinforcement Learning (NASRL)
Pressure-Sensitive Floor Mapping (PSFM)
Thermal Gradient Behavioral Analysis (TGBA)