Developing a Data-Driven Personalized Fitness Web Application for Obese and Sedentary Individuals with Django

Rukayat Balogun; Professor Celestine Iwendi

doi:10.1007/978-3-032-35516-4_40

Developing a Data-Driven Personalized Fitness Web Application for Obese and Sedentary Individuals with Django

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Developing a Data-Driven Personalized Fitness Web Application for Obese and Sedentary Individuals with Django

Rukayat Balogun Professor Celestine Iwendi

Machine Intelligence and Data Science : First International Conference, MIDAS 2025, Paralakhemundi, India, March 21–22, 2025, Proceedings, pp.496-506

Machine Intelligence and Data Science (MIDAS-2025) (Paralakhemundi, India, 21/03/2025–22/03/2025)

18/08/2026

: https://doi.org/10.1007/978-3-032-35516-4_40

Personalised fitness

gradient boosting

Django

sedentary behavior

real-time recommendations

BMI prediction

Machine Learning

Obesity

This paper presents the development of a data-driven personalized fitness web application aimed at combating obesity and sedentary behavior. The web application leverages machine learning algorithms, particularly Gradient Boosting, to provide individualized fitness and dietary recommendations based on user input, such as BMI, activity levels, and health data. Built on the Django framework, the application ensures scalability, security, and ease of use. Key features include real-time adaptive recommendations, a user-friendly interface, and a feedback loop that personalizes fitness plans according to user progress. The machine learning models were trained on a large dataset and tested against several models, with Gradient Boosting achieving the highest prediction accuracy (R² = 0.9975). Initial user feedback indicated high satisfaction, particularly due to the system’s adaptability to evolving health conditions. Future research directions include enhancing algorithm performance, expanding data sources, and incorporating wearable devices for more precise realtime recommendations.

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Developing a Data-Driven Personalized Fitness Web Application for Obese and Sedentary Individuals with Django7.26 MB

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https://midas2024.cutm.ac.in/

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https://ub-ir.bolton.ac.uk/view/delivery/44UOBO_INST/126900730008841/136900720008841

: Developing a Data-Driven Personalized Fitness Web Application for Obese and Sedentary Individuals with Django
: Rukayat Balogun - University of Greater Manchester
Professor Celestine Iwendi - University of Greater Manchester, Computing
: Machine Intelligence and Data Science : First International Conference, MIDAS 2025, Paralakhemundi, India, March 21–22, 2025, Proceedings, pp.496-506
: Machine Intelligence and Data Science (MIDAS-2025) (Paralakhemundi, India, 21/03/2025–22/03/2025)
: Springer Cham
: 9930507308841; 1865-0929; 1865-0937; 9783032355157; 1865-0937
: Copyright The Author(s), under exclusive license to Springer Nature Switzerland AG 2027
: Computing
: Conference proceeding
: 2027
: 18/08/2026
: Hybrid conference organized by School of Engineering and Technology Centurion University of Technology and Management, Paralakhemundi, Odisha, India