SMARTLAB AI-Driven Attendance and Power Automation System

In today's educational institutions, managing class attendance and optimizing energy usage in classrooms are critical challenges.Traditional attendance tracking methods are time-consuming and prone to errors, while classrooms often remain powered on even when unoccupied, leading to energy wastage.SmartLab offers a dual-purpose solution, automating attendance and power management using AI-driven facial recognition and real-time human detection with people counting.The system employs the Haar Cascade algorithm for face detection and the Local Binary Pattern Histogram (LBPH) algorithm for face recognition to automate attendance marking.Furthermore, it integrates a pre-trained frozen inference graph for human detection, allowing for effective counting of individuals in the classroom.This solution addresses both attendance management and energy efficiency by turning off devices when classrooms are unoccupied.SmartLab significantly reduces manual effort in attendance tracking and promotes energy conservation through automated power management.Future enhancements may involve integrating deeper learning models to improve performance in crowded and low-light scenarios.