Manually monitoring the behavior of students is not just distracting but tedious too for the educators. Our computer vision and ML powered systems observe the students and engagement throughout the day. It tracks movements, interactions and engagement levels to maintain a focused learning environment.
It’s a challenge for teachers to identify which students are disengaged or distracted in the class.
Our system monitors facial expressions and movements to provide real-time analytics into student attentiveness.
Ensuring student safety and quickly identifying anomalies, esp. in large classrooms or campus areas is difficult.
AI continuously monitors hallways, cafeterias and classrooms to detect behaviors and safety risks, and alerts in real-time.
Disruptions when go undetected negatively impact learning environment and overall classroom dynamics.
AI system instantly detects behavior like excessive wandering or loitering and lets educators intervene promptly.
Without real-time monitoring of each student, teachers can miss signs of students who are falling behind.
AI analyzes participation patterns, engagement levels and trends to provide performance insights to the teachers.
Student activity monitoring is done by educational environments as they seek student engagement for better learning outcome and ensure safety across the campus.
We integrate the existing classroom and common area cameras to the AI platform.
AI model is trained to recognize behavior patterns, engagement cues and safety risks for educational settings.
Live monitoring tracks student behavior and gives alerts for potential disruptions or safety concerns.
Get detailed analytics on engagement trends and safety incidents with actionable insights for the educators.
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