In today’s environments, whether educational, retail, or public spaces, the task of identifying and understanding emotions predominantly relies on human observation. This approach has several inherent limitations:

• Absence of Automated Emotion Identification: Apart from subjective human observations, there is a notable lack of automated tools capable of accurately identifying and analyzing emotions in real-time. This gap means that many nuanced emotional reactions are overlooked, potentially missing critical moments for intervention or engagement.

• Subjectivity and Inconsistency: Human observation of emotions is inherently subjective and can vary significantly from one observer to another. This inconsistency leads to a lack of reliable data on which to base decisions or actions.

• Limited Scalability: Relying on people to observe and report emotions is not scalable in larger or busier environments. As the number of individuals in a space increases, the ability to monitor everyone effectively and empathetically diminishes.

• Missed Opportunities for Engagement: Without the ability to systematically identify and respond to emotions, organizations miss out on opportunities to engage with individuals in a manner that is tailored to their emotional state, whether it’s providing support to a distressed student or enhancing a customer’s shopping experience.

• Lack of Continuous Monitoring: Human observers cannot provide continuous, 24/7 monitoring. Emotional states that manifest outside of observation periods or subtle changes over time are often missed, reducing the effectiveness of any interventions or support.