International Journal of Forensic Research(IJFR)
ISSN: 2767-2972 | DOI: 10.33140/IJFR
Impact Factor: 1.9
Neha Bansal
School of Computer Science and Engineering, Geeta University, Panipat, 132103, India
Publications
-
Research Article
Integration of FastAPI-Based Machine Learning Model with Android Application for Real-Time Calories Burnt Prediction
Author(s): Neha Bansal and Bhawna Singla*
This paper presents the design and implementation of a system integrating a FastAPI backend serving a machine learning model for predicting calories burnt with a native Android application. The backend uses a Random Forest Regressor trained on health and exercise data to deliver accurate calorie estimations. The Android application interacts with the API to send user input and receive real-time predictions. The system demonstrates seamless communication between Python-based APIs and mobile platforms, facilitating personalized fitness monitoring on portable devices... Read More»