The development of positive habits plays a crucial role in improving personal productivity, health, and overall lifestyle. However, many individuals struggle to maintain consistent habits due to lack of motivation, monitoring, and personalized guidance. Traditional habit-tracking applications mainly focus on recording daily activities but do not provide intelligent analysis or behavioral insights. To address this limitation, this research proposes SmartHabit AI – an Intelligent Behaviour Transformation System that utilizes Artificial Intelligence to analyze user behavior and support sustainable habit development. The proposed system collects user activity data related to daily habits such as exercise, study time, sleep patterns, and productivity tasks. Using machine learning techniques, the system analyzes behavioral patterns, predicts the probability of habit success or failure, and provides personalized recommendations to improve consistency. SmartHabit AI also generates motivational notifications and adaptive goals based on user performance. The system aims to transform the conventional habit-tracking approach into an intelligent guidance platform that helps users develop positive behaviors and eliminate negative habits. The proposed model can be applied in areas such as healthcare, education, personal productivity, and mental wellness. By integrating artificial intelligence with behavioral analytics, SmartHabit AI provides an effective solution for long-term behavior transformation and self-improvement.
SmartHabit AI, Artificial Intelligence, Behaviour Transformation, Habit Tracking, Machine Learning, Behaviour Analytics, Personal Productivity, Intelligent Recommendation System.
IRE Journals:
Stewak I., Dr. S. Saraswathi "SmartHabit AI – Intelligent Behaviour Transformation System" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 929-935 https://doi.org/10.64388/IREV9I9-1715113
IEEE:
Stewak I., Dr. S. Saraswathi
"SmartHabit AI – Intelligent Behaviour Transformation System" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1715113