An Automated Class Intimation System for Educational Institutions using Artificial Neural Networks

This study presents a novel solution aimed at enhancing communication between educational institutions and their faculty and students by leveraging Artificial Neural Network (ANN) algorithm integrated with Java programming. The primary objective is to develop an automated system capable of predicting and notifying teachers and class representatives about their upcoming class schedules via SMS notifications. The integration of the ANN algorithm with Java offers a unique and revolutionary approach, enabling accurate prediction and timely dissemination of class schedules. Users are empowered with functionalities to add, update, and create class schedules dynamically, facilitating efficient management of academic timetables. Additionally, the system allows for the inclusion of teacher and class representative contact information for personalized notifications. A broadcast receiver tool is implemented to efficiently deliver SMS messages to the relevant recipients, ensuring effective communication and timely reminders. Through this innovative approach, the study aims to provide an effective and efficient means of keeping all stakeholders informed about their class schedules, thereby minimizing the risk of missed classes and optimizing academic engagement. The proposed system showcases the efficacy of utilizing ANN in Java as an invaluable tool for both teachers and students, offering seamless management and recall of class schedules, and fostering improved academic productivity and attendance.