Attendance marking in a classroom during a lecture is not only a onerous task but also a time consuming one at that. Due to an unusually high number of students present during the lecture there will always be a probability of proxy attendance(s).Attendance marking with conventional methods has been an area of challenge. The growing need of efficient and automatic techniques of marking attendance is a growing challenge in the area of face recognition. In recent years, the problem of automatic attendance marking has been widely addressed through the use of standard biometrics like fingerprint and Radio frequency Identification tags etc., However,these techniques lack the element of reliability. In this proposed project an automated attendance marking and management system is proposed by making use of face detection and recognition algorithms. Instead of using the conventional methods, this proposed system aims to develop an automated system that records the student’s attendance by using facial recognition technology. The main objective of this work is to make the attendance marking and management system efficient, time saving, simple and easy. Here faces will be recognized using face recognition algorithms. The processed image will then be compared against the existing stored record and then attendance is marked in the database accordingly. Compared to existing system traditional attendance marking system, this system reduces the workload of people. This proposed system will be implemented with 4 phases such as Image Capturing, Segmentation of group image and Face Detection, Face comparison and Recognition, Updating of Attendance in database.

Recognizing the impact of mathematical learning difficulties on student achievement, this research focuses on developing adaptive, technology-based solutions for those struggling with learning mathematics, including individuals with dyscalculia. Dyscalculia, a difficulty in understanding numbers and mathematics, can profoundly affect a child’s academic progress and self-confidence. Many interventions aim for broad effectiveness but often struggle to address individual learning differences. This research addresses this gap by employing Dynamic Bayesian Networks (DBNs) within intelligent tutoring systems to develop a personalized, gamified approach for improving mathematical skills in children with dyscalculia. We assessed 158 children aged 6–10 years using the Smartick Dyscalculia Assessment Tool to identify specific numerical cognition deficits. Based on these assessments, we have developed EDSense (Early Detection and Intervention for Insufficient Number Sense), an adaptive web-based learning tool. EDSense provides personalized support and targets skill refinement in mathematics learning. A pre-test and post-test design evaluates EDSense’s effectiveness and demonstrates significant improvements in numerical abilities. The findings highlight the crucial role of adaptive learning platforms in addressing dyscalculia. The EDSense platform demonstrates gamified, self-directed learning environments to enhance both engagement and learning outcomes by accommodating individual cognitive differences. We have proposed a technology-driven framework for personalized dyscalculia interventions, emphasizing early detection to support mathematical skill development.

Many ways of communications are used between human and computer, one of them includes using gesture which is considered to be one of the most natural ways in a virtual reality system. Because of its intuitiveness and its capability of helping the hearing impaired and speaking impaired. Hand gestures enable deaf people to communication during their daily lives rather than by speaking. A sign language is a language which, instead of using sound, uses visually transmitted gesture signs which simultaneously combine hand shapes, orientation and movement of the hands, arms, lip-patterns, body movements and facial expressions to express the speaker's thoughts. in order to bridge this gap of sign to speech, Voice fOr the Mute (VOM) aims to develop a system that will take real time images and convert them to speech with text as an intermediate taking into considerations all the limitations observed by a 2D system we will be considering only fingering spelling in our system i.e. Take input in the form of finger-spelling of alphabetic signs and providing the resultant voice output. The system will be using a webcam for the input and processing of the signs will be done using Microsoft Visual Studio as an IDE and OpenCv modules. With this proposed system we aims to help the speech impaired community.

Speech impaired people make use of sign language to communicate along with normal people. Common people also face difficulties to understand the gesture language. In order to minimize these real time issues, an attempt has been made to develop a system which consists of Flex sensors attached with the Data gloves along all fingers. These will be wearable gloves converts hand gestures into an audio output to interpret the expression. This reduces the communication gap that exists between mute and ordinary people. The proposed system plays corresponding recorded voice on an android phone connected to the hardware system via Bluetooth Module as an interpretation of the gesture. It is achieved by integrating flex sensor and 8051 microcontroller. The phone will use a text to speech converter to produce the output of corresponding gesture. This system offers high reliability and fast response as microcontroller works at a speed of 12 MHz. Processing time of microcontroller is much less than the time taken for a human to change from one gesture to another, the system works efficiently in real time scenario hence making the system faster.

The purpose of this study is to discuss the usage of computer vision in educational applications. In recent years, air writing has become one of the most challenging and exciting research areas in image processing and pattern recognition. The project employs object tracking techniques to construct a motion-to-text converter that might be used as software in the field of education to allow students and teachers to write in the air. The project generates letters on the screen by utilizing computer vision to trace the path of a finger or an object. The resulting text can be utilized for a variety of things, including solving graph-related challenges. Questions on logical reasoning (Mathematics), to write formulas or execute derivations, Kindergarten kids are being taught the alphabet, to replace chalk and board (dustless classroom) in offline classes, etc. For the deaf, it will be a strong way of communication.