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@article{173269,
        author = {Dixit Manna KM and MohanaKrishna S and Senthamilarasi.N},
        title = {REVIVEFiT: AN AI FITNESS ASSISTANT USING NATURAL LANGUAGE PROCESSING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {2943-2948},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173269},
        abstract = {This paper introduces an innovative AI fitness assistant that leverages Natural Language Processing (NLP) to enhance user interactions and optimize personalized fitness experiences. The assistant utilizes advanced NLP techniques to understand and process user inputs, including fitness goals, preferences, and feedback, delivered through conversational interfaces such as voice or text. By integrating NLP with machine learning algorithms, the system can dynamically generate customized workout plans, offer real-time guidance, and adjust recommendations based on ongoing user interactions. This approach allows for a more intuitive and engaging user experience, as the AI can interpret natural language queries and adapt its responses accordingly. The paper discusses the system's architecture, including the NLP model's role in extracting and analyzing user intent, and how it integrates with fitness tracking data to provide actionable insights. Additionally, it evaluates the effectiveness of this NLP-driven assistant in improving user adherence to fitness programs and overall satisfaction. The study highlights the potential of combining NLP with AI to create a more personalized and interactive fitness solution, while also addressing challenges such as maintaining context and handling diverse user inputs.},
        keywords = {AI Fitness Assistant, Natural Language Processing (NLP), Personalized Fitness, Machine Learning Algorithms, Conversational Interfaces, Voice Interaction, Text-Based Interaction, Custom Workout Plans, Real-Time Guidance, User Adherence, Fitness Tracking Data, User Feedback, Interactive Fitness Solutions, User Experience, Context Management, Diverse User Inputs, Fitness Program Optimization, Intuitive Interaction},
        month = {March},
        }