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SmartHabit AI – Intelligent Behaviour Transformation System
Subject area: Science,Engineering and Technology · Area of research: AI-Based Behavior Change Systems
Abstract
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.
Keywords
SmartHabit AI, Artificial Intelligence, Behaviour Transformation, Habit Tracking, Machine Learning, Behaviour Analytics, Personal Productivity, Intelligent Recommendation System.
References
[1] P. Lally, C. H. van Jaarsveld, H. W. Potts, and J. Wardle, “How habits are formed: Modelling habit formation in the real world,” European Journal of Social Psychology, vol. 40, no. 6, pp. 998–1009, 2010.
[2] H. Oinas-Kukkonen and M. Harjumaa, “Persuasive Systems Design: Key Issues, Process Model, and System Features,” Communications of the Association for Information Systems, vol. 24, no. 1, pp. 485–500, 2009.
[3] W. Wood and D. Runger, “Psychology of Habit,” Annual Review of Psychology, vol. 67, pp. 289–314, 2016.
[4] H. Khezri, R. Shahnazi, and A. H. Ghapanchi, “AI-based Behavioral Change Systems: A Review of Personalized Habit Formation Applications,” Journal of Medical Internet Research, vol. 23, no. 5, e24940, 2021.
[5] A. M. Alaa and M. van der Schaar, “Personalized Machine Learning for Habit and Behaviour Prediction,” IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 12, pp. 2340–2353, 2018.
[6] B. J. Fogg, “A Behavior Model for Persuasive Design,” in Proc. 4th International Conference on Persuasive Technology, 2009, pp. 40–47.
[7] S. Michie, M. M. van Stralen, and R. West, “The Behaviour Change Wheel: A New Method for Characterising and Designing Behaviour Change Interventions,” Implementation Science, vol. 6, no. 1, p. 42, 2011.
How to cite this paper
@article{1715113,
author = {Stewak I., Dr. S. Saraswathi},
title = {SmartHabit AI – Intelligent Behaviour Transformation System},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {929-935},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715113.pdf},
abstract = {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.},
keywords = {SmartHabit AI, Artificial Intelligence, Behaviour Transformation, Habit Tracking, Machine Learning, Behaviour Analytics, Personal Productivity, Intelligent Recommendation System.},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1715113}
}