By the Numbers
Emotion Categories
Detection Accuracy
Report Generation
Alert Response Time
How It Works
We configure camera positions and lighting for optimal facial capture. The FER model is calibrated for your environment to ensure consistent emotion classification accuracy.
An initial monitoring period collects baseline emotion data for your population. This establishes normal patterns against which future deviations will be measured and reported.
We set up alert thresholds, notification recipients, and report schedules. Mailgun email templates are customized with your branding and the specific metrics you want highlighted.
The system runs continuously, classifying emotions and generating weekly reports every Friday. Automated alerts fire in real time whenever thresholds are exceeded for any individual.
The FER model classifies facial expressions into seven emotions: happy, sad, angry, surprised, fearful, disgusted, and neutral. Real-time classification enables immediate response to emotional shifts.
Llama 3.3-70B generates comprehensive weekly emotion analysis reports from aggregated data. Reports include trends, notable patterns, and actionable recommendations written in natural language.
When negative emotions are detected seven or more times in a week, the system triggers an automatic alert. Designated staff receive email notifications via Mailgun with detailed context.
Interactive dashboards chart emotion distributions over time per individual and group. Spot emerging patterns, compare periods, and correlate emotional trends with external events.
Emotion data is aggregated and anonymized before reporting. Raw images are processed in real time and discarded immediately, ensuring compliance with data privacy regulations.
Alert thresholds, report schedules, and emotion categories can be customized per organization. Administrators control sensitivity levels and notification recipients through a simple dashboard.
Use Cases
A childcare center monitors children's emotional states throughout the day. Staff receive alerts when a child shows persistent negative emotions, enabling early intervention and parent communication.
A company tracks aggregate emotional trends across teams to gauge workplace morale. Weekly reports help HR identify departments that may need support or recognize positive shifts after interventions.
A school uses emotion analysis to understand student engagement during different activities. Teachers receive insights on which approaches generate the most positive emotional responses in their classrooms.
A childcare center monitors children's emotional states throughout the day. Staff receive alerts when a child shows persistent negative emotions, enabling early intervention and parent communication.
A company tracks aggregate emotional trends across teams to gauge workplace morale. Weekly reports help HR identify departments that may need support or recognize positive shifts after interventions.
A school uses emotion analysis to understand student engagement during different activities. Teachers receive insights on which approaches generate the most positive emotional responses in their classrooms.
Technology Stack
Let's discuss how this solution fits your business.