The Smart Task Scheduler with Motivation Mode is an AI
Prof. Priti P. Tijare
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering And Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra
prititijareis@gmail.com
Unnati C. Shrikhande
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering And Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra
unnaatishrikhande@gmail.com
Samata V. Ingole
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering And Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra
samataingole003@gmail.com
Abhijit R. Ingole
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering And Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra
abhijitingole2003@gmail.com
Sumit G. Dholwade
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering And Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra
sumitdholwade24@gmail.com
Abstract
Effective task management and sustained motivation are essential for improving productivity in academic, professional, and personal environments. However, most existing task scheduling applications focus primarily on basic to-do list creation and reminders, while ignoring intelligent prioritization and the psychological factors that influence user performance.
The proposed machine integrates assignment scheduling, AI-primarily based totally precedence analysis, and mood-orientated motivational guide inside a unmarried platform. Developed using Android (Java/XML) and Firebase Realtime Database, the application enables users to create tasks, receive intelligent priority suggestions, and track progress through visual productivity analytics. A Pomodoro-primarily based totally paintings timer and personalised motivational messages are integrated to enhance cognizance and decrease intellectual fatigue Experimental observations indicate improved task completion rates, enhanced user engagement, and reduced procrastination. The results demonstrate that combining structured task planning with motivational feedback provides a more effective and user-centric productivity solution.
Keywords - AI-driven Prioritization, Task Scheduling, Android Application Development, Firebase Realtime Database, Productivity Analytics, Motivation Mode, Pomodoro Technique2. Introduction
