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@article{178628,
        author = {Ramander Singh and Iqra Khan and Harsh Vardhan Singh and Roshan Saifi},
        title = {SMART HABIT TRACKER: A THEORETICAL ANALYZES OF DATA-DRIVEN BEHAVIOURAL CHANGE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {4718-4727},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178628},
        abstract = {Our daily habits shape our productivity, health and overall well being. Many people struggle to build and maintain good habits due to lack of motivation, no organized tracking and absence of personalized guidance. While traditional habit trackers help to some extent they mostly require manual input and do not provide meaningful insights into progress. This paper explores the concept of a Smart Habit Tracker that uses artificial intelligence, behavioural psychology and data analytics to improve habit formation. By analyzing user behaviour providing real time feedback and adapting to individual patterns this system can help users stay on track more properly. Also addresses common challenges faced like loss of motivation, privacy concerns and the reliability of AI driven suggestions. The paper also discusses the future possibilities which consists of smartwatch integration, gamification and emotion based tracking which could make habit building more reliable and practical. This research discusses the importance of smarter data driven habit trackers that monitor habits and also regularly support users in achieving their goals.},
        keywords = {Habit Tracking, Behavioural Psychology, Data Analytics, AI-Based Feedback, Smart Tracking, Predictive Analytics, Motivation, Gamification, Personalized Recommendations.},
        month = {May},
        }