Virtual Booth

SMART MOOD TRACKER & LIE DETECTOR: An AI-Powered Student Well-Being Monitoring System

Student mental health has become an increasingly important concern due to academic pressure, social challenges, and emotional stress. However, teachers often face difficulties in identifying students who require support because traditional monitoring methods rely mainly on observation and self-reporting. To address this issue, our team developed the Smart Mood Tracker & Lie Detector, an Artificial Intelligence (AI) and Internet of Things (IoT) based system designed to monitor students' emotional well-being and identify signs of stress and possible deception in real time.

The system integrates a Raspberry Pi 5, MAX30102 pulse oximeter sensor, and Raspberry Pi Camera Module 3 to collect biometric and behavioural data, including heart rate, facial expressions, hand movements, and responses from a 40-question emotional assessment. A machine learning Decision Tree Classifier processes these data to classify stress levels and estimate deception probability. The results are displayed through a secure web-based dashboard, allowing teachers to monitor students, review recorded sessions, and identify individuals who may require early intervention.

The innovation also includes user authentication, two-factor authentication (2FA), email notification services, an AI chatbot assistant, and class-based dashboards, providing a complete digital platform for educational institutions. By combining multiple sources of biometric and behavioural information into a single system, the project offers a more comprehensive and reliable approach to emotional monitoring than conventional methods.

The Smart Mood Tracker & Lie Detector has the potential to improve student well-being, support educators in making informed decisions, and promote early mental health intervention. This project demonstrates how AI and IoT technologies can be applied to create practical solutions for modern educational environments while contributing to Sustainable Development Goal (SDG) 3: Good Health and Well-Being, SDG 4: Quality Education, and SDG 9: Industry, Innovation and Infrastructure.

Keywords: Artificial Intelligence; Internet of Things; Student Well-Being; Stress Detection; Biometric Monitoring