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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Smart Attendance System |
| Authors Name: | Milind Rane , Sanskar Gundecha , Om Gujarathi , Asawari Jadhav , Sankalp Hatewar,Jayesh Chaudhari |
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| Author Reg. ID: |
IJNRD_196177
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| Published Paper Id: | IJNRD2305543 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | Traditional attendance tracking systems are often time-consuming, inefficient, and reliant on paperwork, leading to inaccuracies and administrative burdens. This research paper presents a novel mobile application developed using Flutter that utilizes location-based tracking and biometrics for automated attendance marking. The existing systems for attendance tracking typically involve manual processes, such as paper-based sign-in sheets or barcode scanning. These methods are prone to errors, require significant administrative efforts for data entry, and lack real-time monitoring. Additionally, traditional systems struggle to handle simultaneous attendance marking for multiple students, leading to delays and inefficiencies. To address these challenges, we developed a mobile application using Flutter, a cross-platform framework, which allows seamless integration across various devices and operating systems. Our system leverages the mobile device's location services and biometric authentication capabilities to automate the attendance tracking process. The application utilizes Node.js to develop robust APIs that facilitate communication between the frontend and a MongoDB database, ensuring efficient storage and retrieval of attendance data. The integration of location-based services enables real-time tracking and authentication, providing accurate attendance records for each student. Through comprehensive testing and evaluation, our system demonstrated enhanced efficiency and accuracy compared to traditional attendance tracking systems. Simultaneous attendance marking for multiple students became feasible, reducing the time required for data entry and minimizing administrative efforts. The integration of biometrics ensures secure authentication, eliminating the possibility of proxy attendance. |
| Keywords: | image processing, smart attendance, face recognition |
| Cite Article: | "Smart Attendance System", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.f234-f238, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305543.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2305543 Registration ID: 196177 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: f234-f238 Country: -, -, - Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305543 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305543 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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