ROLLCALL an automatic and smart attendance marking and management system which uses Microsoft Azure’s Cognitive service at its core to create a system that could make sure that no human intervention is required and provides government the ability to monitor the attendance of the schools and helps the government officials in mark fake schools.

Human face detection and recognition is an important technology used in various applications such as video monitor system. Traditional method for taking attendance is Roll Number of student and record the attendance in sheet which takes a lot of time. Because of that systems like automatic attendance is used. To overcome the problems like wastage of time, incorrect attendance, the proposed system gives a method like when he enters the class room , system marks the attendance by extracting the image using Principal Component Analysis algorithm. The system will record the attendance of the student automatically. The student database is collected, it includes name of the students, there images and roll number. It carries an entry in log report of every student of each subject and generates a PDF report of the attendance of the student.

Purpose The purpose of this project is to apply and learn advanced software engineering concepts gathering requirements for a software application that schedules the hospital personnel and then derive use cases from them. This involves reviewing of already existing software and learning website and derive requirements and use cases based on the website primary features. The project also encompasses construction of, sequence diagram, design class diagram, Collaboration diagrams and other UML modeling diagrams based on the derived use cases. At the end, high level planning is done for the whole project based on derived use cases by Agile efforts estimation technique. Scope The project will consist of developing personnel scheduling software. Modules of the website include a login feature, a schedule checker and a schedule planner. Our innovative 100% web-based Scheduling & Open Shift Management (OSM) product can help managers efficiently schedule their staff, and also lets the staff help managers fill open shifts online, see schedules and changes, request time- off, swap shifts, etc, etc. All schedules, changes, approvals, and alerts not only happen online in real-time, but also are sent out as emails and text messages to cell phones. Our Software can cut manager time wasted on scheduling tasks by 50% or more and let them get back to MANAGING! Introduction to HMSS When workforce includes hundreds of employees, open shifts are inevitable. Without the right skills-based workforce management tools in place, nurse managers and staffing managers spend a disproportionate amount of time trying to fill scheduling gaps. Not only is this inefficient, but it leads to increased costs and reduced employee satisfaction. Advantages of having online scheduling system 2.1. ● Save Money Reduce premium labor costs by leveraging the most cost-effective, qualified staff to fill open shifts. Stop wasting time you don’t have on scheduling. Decrease the time it takes you to create a weekly schedule for your team by over 75 percent with HMSS. ● Save Time Save countless hours using instant communication strategies to fill open shifts. ● Keep Workers Happy Increase employee satisfaction by empowering them to choose when they want to work based on experience, competencies, and skills. ● Faster, Easier Scheduling Healthcare staff scheduling has never been easier. Spend minutes instead of hours organizing shifts for your nurses and other medical staff. ● Monitor Attendance Hospital Management System (Personal Scheduling System) – SWE 600 (Fall 2015) Prof. Instructors: Dr. R. Riehle & Q Asghar See which employees are coming in late or missing shifts. Send shift reminders automatically to make sure everyone is on the same page. ● Give Staff More Independence Take some work off your own plate with collaborative healthcare staff scheduling options. Allow your employees to request shift trades and swaps on their own so you don’t have to micromanage them. ● Avoid Human Error Humans make mistakes, but HMSS doesn’t. If you forget to fill a shift or overbook one, the software immediately notifies you of your error, allowing you to rectify it right away. ● Create Perfect Timesheets Export perfect timesheets to create perfect attendance and work reports. Better healthcare staff scheduling means easier payroll processing as well. To deliver the best care possible to patients, we must begin with the best possible workforce management solution for our staff. With HMSS, we help control labor costs, minimize compliance risk, improve workforce productivity, and deliver quality, cost-effective care. Here’s how: • Physician coverage scheduling enables the effective and equitable deployment of physicians and other clinician providers – your group, your rules, to build your schedules • Advanced staffing supports the safest and most appropriate assignment of caregiver staff to patients, and balances workload distribution in the best interests of patients and staff • Intelligently forecast volume to build optimal schedules helps ensure proper staff coverage for every shift, every day, across your entire organization • On-demand visibility with labor analytics controls labor costs and allows organizations to make evidence-based decisions • Mobile management supports paperless workflow and employee self-service for your on-the-go workforce

A security support and attendance system for St. Bernadette College of Alabang. This project uses RFID as the identification device of students and staffs. It monitors the visitation records of each person in the building through RFID readers with NodeMCU that communicates with the server through websockets. Students and staffs can tap their RFID cards and the system automatically records their time in as they enter the building and time out as they go out

"Automatic Attendance Monitoring System" To maintain the attendance record in schools colleges or any administrative sector through a conventional method by calling the name of every person is very difficult and time-consuming and even a chance of proxy attendance so the following system is based on face recognition to maintain the attendance record of the students and workers. In our implementation, we have tried to recognize faces and marking down the attendance using Haar Cascades with the 'Local Binary Pattern Histogram' technique. The graphic user interface is designed using the Tkinter library. This monitoring system gives the appropriate tracking of the students attending the schools/ colleges with real-time data stored in a separate file. On the contrary, this is an offline system which is the only limitation for this system. Picture Description: 1. Tkinter GUI of the system - 2. Face recognized using this system - 3. Record stored in real-time

This project covers the design, simulation, and demonstration of a prototype Smart Attendance Monitoring System. The primary objective was to build a secure, cost-effective, and uniform system to capture attendance data automatically. Utilizing dual-factor authentication (Face + Fingerprint)

This repository features an AI-powered attendance system that uses Faster R-CNN for face recognition, achieving 98.87% accuracy. The system captures real-time student images to automatically mark attendance and monitor classroom activity.

Smart Face Recognition Attendance System – Real-time employee attendance tracking using YOLOv8 and face_recognition. Automatically detects known faces, logs entry/exit times, and handles unknown faces with optional saving. High-speed detection, dynamic database updates, and full-screen/resizable interface for easy monitoring.

Key Features - Real-time face recognition through live camera - Works with existing CCTV or webcam setups - Automatic attendance tracking (IN / OUT capture) - Multi-person detection and recognition - Can be used for employee monitoring and theft prevention - Attendance data logging for analysis and reporting - Contactless and automated system

Face recognition is an important application it is used in numerous fields. This application is use for maintain and monitoring the attendance records. It is play important role in any organization. Marking and managing attendance is a difficult task by educational institutes, which is timing-consuming and leads to many student and teacher’s related issues. To solve these issues there should be an automatic system of managing and marking attendance. The purpose of this application Faces Recognition Base Attendance Management System. We made the system capable of identifying the faces of the students and base on the matched faced will give in the database and marked attendance automatically. The automatic system will maintain the record of attendance for future use it will also calculate the short attendance of the students.

A Chrome extension that automates the Google Meet attendance. It features a dual-engine detection system: a Chat Monitor for automatic ID submission and a unique Caption-Based Detector that watches live speech to alert you during verbal roll-calls.

The main purpose of this project is to build a face recognition-based attendance monitoring system for educational institution to enhance and upgrade the current attendance system into more efficient and effective as compared to before. The current old system has a lot of ambiguity that caused inaccurate and inefficient of attendance taking. Many problems arise when the authority is unable to enforce the regulation that exist in the old system. The technology working behind will be the face recognition system. The human face is one of the natural traits that can uniquely identify an individual. Therefore, it is used to trace identity as the possibilities for a face to deviate or being duplicated is low. In this project, face databases will be created to pump data into the recognizer algorithm. Then, during the attendance taking session, faces will be compared against the database to seek for identity. When an individual is identified, its attendance will be taken down automatically saving necessary information into a excel sheet. At the end of the day, the excel sheet containing attendance information regarding all individuals are mailed to the respective faculty.

An interactive attendance monitoring system using HTML, CSS, and JavaScript with automatic percentage calculation.

The Attendance and Payroll System, is a comprehensive attendance monitoring with an automatic payroll processing system for the employees. This proposed system will help to get the accurate working hours, to monitor the attendance of each employees and automatic computations for their corresponding salaries or payrolls

Python-based monitoring system that automatically tracks JIIT student portal data (attendance, marks, notices) and sends alerts via Telegram.

The Face Recognition Based Attendance Monitoring System designed to automate the attendance process using facial recognition technology. By capturing live video input through a camera, the system detects and identifies faces in real time, then marks attendance automatically with the person’s name, date, and timestamp.

A library attendance system using barcode scanning. Students scan their ID to log entry and exit, and attendance is recorded automatically in a secure database. It saves time, reduces errors, and allows easy monitoring of library usage.

This project implements a real-time face recognition system using Python, OpenCV, and the face_recognition library. It captures faces from a webcam feed, recognizes them, and marks attendance automatically. Ideal for monitoring attendance in classrooms or workplaces.

A smart anti-class bunking system that uses facial recognition and real-time camera surveillance to automatically monitor student attendance and detect unauthorized absence

Smart Exam Surveillance System using YOLO, and tracking to detect and record cheating behavior in real-time. Supports multiple students, live monitoring, and automatic alerts, with attendance system and using RAG as an Ai_assistant

Smart Exam Surveillance System using YOLO, and tracking to detect and record cheating behavior in real-time. Supports multiple students, live monitoring, and automatic alerts, with attendance system and using RAG as an Ai_assistant

The Online Class Attendance System uses face detection and WebRTC to track student presence and participation in real time. Instructors can monitor attendance live, with automatic updates if a student becomes inactive or leaves the frame.

This project is Smart Attendance & Class Utilization: a robust, privacy-aware system that automatically marks attendance via classroom cameras, monitors student engagement and movement, and optimizes use of teaching hours by detecting staff absence and recommending productive alternatives.

automatic and smart attendance marking and management system which uses Microsoft Azure’s Cognitive service at its core to create a system that could make sure that no human intervention is required and provides government the ability to monitor the attendance of the schools and helps the government officials in mark fake schools.

Student Monitoring System is a Flask & MySQL-based web app that manages attendance, internal marks, and academic progress for UG & PG students. It supports Admin, Staff, and Student roles, with secure access, automatic calculations, and semester-wise reports for efficient academic management.

The automatic attendance system is a web-based system whose goal is to record the attendance of students through their teacher in each course and that is done through a computer, phone or tablet connected to the Internet to access the system through the teacher to take attendance and absence for his students daily instead of the paper system and that To save time and to ensure reliability. Each teacher has several classes and can be taught for several stages. Also, each class has a number of students, and each student has his own information such as name, age, stage of study, class, and materials obligated to it at that stage. The person responsible for making every teacher who has a number of students is the college administration, as it gives each teacher the ability to record attendance and absence of students through the system and is monitored and supervised by the college.

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An automated student attendance system using machine learning and computer vision streamlines attendance tracking. It captures student images during class, employing convolutional neural networks for precise face recognition and identification. Attendance is logged automatically with date, time, and roll numbers.