MUMBAI, India, July 11 -- Intellectual Property India has published a patent application (202541060673 A) filed by K Kavita; and BVRIT Hyderabad College Of Engineering For Women, Hyderabad, Telangana, on June 25, for 'attendify: automated real-time attendance tracking.'
Inventor(s) include K Kavita; Bvrit College Engineering For Women; Boppana Sri Neha; Tayyaba Shaik; D. S. K. Manognya; and Yatirajulu Hansika.
The application for the patent was published on July 11, under issue no. 28/2025.
According to the abstract released by the Intellectual Property India: "An automated attendance tracking system is disclosed, designed to replace manual roll calls and mitigate human error in educational or other group settings. The system utilizes real-time image processing and linear algebra principles to capture and identify individuals within a given environment, such as a classroom. Facial images of individuals are represented as vectors or matrices of pixel values. Principal Component Analysis (PCA) is applied to these image data to reduce dimensionality and extract salient facial features, including but not limited to the shape of the face, eyes, and nose. These reduced-dimensional feature vectors are then compared against a preexisting database of registered individuals using matrix multiplication for real-time identification. Attendance is continuously tracked and dynamically updated through the generation of a binary matrix, where a value of "1" indicates presence and "0" indicates absence. The system compares real-time image snapshots of the group with the expected list of attendees to ascertain presence or absence. To account for dynamic environments, an individual is marked as present only if their presence is verified for at least 80% of the monitored duration. To optimize data processing and reduce computational complexity, particularly in large groups, the system incorporates techniques such as Singular Value Decomposition (SVD) and other dimensionality reduction methods. The system also supports multi-camera integration, employing linear algebra to merge data from various cameras for comprehensive attendance tracking across large spaces. The disclosed system aims to enhance efficiency, accuracy, and convenience in attendance management. However, successful deployment necessitates addressing technical considerations such as image accuracy under varying conditions (e.g., poor lighting, occlusions), real-time processing capabilities for large datasets, hardware limitations (e.g., camera resolution), and critical ethical concerns pertaining to privacy and secure handling of biometric data."
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