EduSense - A Real-Time IoT-Augmented Explainable Ensemble Learning Framework With Face-Verified Attendance For Early Academic Risk Detection In Engineering Education

Abstract

Engineering colleges across India face a critical challenge, with approximately 28% of enrolled students failing to complete their degrees on time. In regions like Vidarbha, Maharashtra, this rate is exacerbated by localized financial stress, first-generation academic backgrounds, and constrained support systems. Traditional College Management Systems (CMS) are strictly reactive, flagging academic distress only after semester results are declared—months too late for meaningful intervention. Furthermore, standard institutional data tracking suffers from critical gaps: paper registers yield zero analytical insights , and standard RFID-based attendance logging is highly vulnerable to rampant proxy attendance, where cards are passed between peers. Consequently, key behavioral indicators from attendance, laboratory engagement, and continuous assessments (CA) are never correlated, leaving both faculty and at-risk students unaware of structural failure trajectories until they become irreversible. The system establishes a dual-capture attendance node at the classroom door using a Raspberry Pi Zero W integrated with an RC522 RFID reader and a Pi Camera. When a student taps an RFID card, the system reads the roll number and instantly triggers a face capture within one second. Using an OpenCV preprocessing pipeline and a local face_recognition (dlib) and DeepFace framework, the live face embedding is compared against a pre-enrolled 128-dimensional mathematical vector using a Cosine Similarity threshold of 0.6. Verified logs are saved as PRESENT_VERIFIED to a local SQLite database via MQTT over Wi-Fi , while mismatches blink a red hardware LED and dispatch real-time proxy alerts to faculty via WhatsApp. The system effectively maps directly onto the Dr. Babasaheb Ambedkar Technological University (BATU) Semester VI B.E. CSE curriculum, demonstrating immediate academic and institutional validation through a scheduled two-week live classroom pilot. Beyond its primary deployment as an internal early-warning dashboard with automated Twilio SMS and WhatsApp alerts , EduSense establishes the foundation for a scalable EdTech SaaS enterprise viable for India’s 10,000+ engineering colleges. Future iterations will expand this framework by replacing weekly snapshot ensembles with Long Short-Term Memory (LSTM) recurrent networks to capture gradual temporal disengagement, and incorporating federated learning paradigms to securely scale model training across multiple institutions simultaneously without consolidating raw student data.