Behavior and emotion tracking uses video, audio sensors, wearables, geolocation markers, and other data sources to track and infer people's emotions and behaviors. For example, facial recognition based on machine vision and machine learning technologies can translate data into emotional and behavioral insights. The use of sensor data to analyze the same situation from different perspectives provides richer insights. Existing case studies of implementations of this use case include consumer focused applications such as shopper insights, social media analytics, crowd safety and survillence, and localized product marketing insights.
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