Integrated Academic Management & Learning Hub With AI Chatbot and Surveillance

Registration ID: IJNRD_311657

Published ID: IJNRD2601082

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Harshavardhan pandey, Dr. Malatesh S H, Kshitiz Kannojia, Aman Kumar, Ajeet kumar Pandey

attendance management in educational institutions is a crucial yet time-consuming task when handled manually, often resulting in inaccuracies, proxy attendance, and increased administrative workload. To address these challenges, this project presents a Face Recognition–Based Automated Attendance System that utilizes computer vision and machine learning techniques to record attendance accurately and efficiently without human intervention. The proposed system captures real-time facial images using a standard camera and detects faces using the Viola–Jones Haar Cascade algorithm. For face recognition, the Local Binary Pattern Histogram (LBPH) algorithm is employed due to its robustness and suitability for real- time applications. The system operates through three main phases: dataset creation, training, and testing. During dataset creation, multiple facial images of each individual are captured and stored with a unique identifier. In the training phase, the LBPH algorithm is trained on the collected dataset to generate an effective recognition model. During testing, live images are processed to identify registered individuals, and attendance is automatically recorded in the database upon successful recognition.

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Harshavardhan pandey, Dr. Malatesh S H, Kshitiz Kannojia, Aman Kumar, & Ajeet kumar Pandey (January-2026). Integrated Academic Management & Learning Hub With AI Chatbot and Surveillance. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(1), a637-a640. https://ijnrd.org/papers/IJNRD2601082.pdf

Volume 11 Issue 1, January-2026

Pages : a637-a640

Paper Reg. ID: IJNRD_311657

Published Paper Id: IJNRD2601082

Research Area: Other area not in list

Author Type: Indian Author

Country: BENGALURU, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2601082.pdf

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