B.Tech student at MANIT Bhopal and BS Data Science student at IIT Madras. Built and deployed machine learning models.

github

Mayank Saini  • Peerlist

<h3>PitVision AI: Revolutionizing Formula 1 Strategy with Machine Learning</h3>Leveraging the power of advanced machine learning, PitVision AI offers unparalleled insights into Formula 1 pit stop strategy. Our sophisticated Random Forest models are meticulously trained on extensive real-world F1 race telemetry, enabling highly accurate predictions for optimal pit stop timing. This tool is engineered to provide a significant strategic edge to teams and enthusiasts alike.<ul><li>ML Predictions: Utilizes a Random Forest classifier trained on authentic F1 telemetry data to predict optimal pit windows with exceptional confidence.</li><li>Data Driven Analysis: Analyzes thousands of race laps across multiple seasons, considering critical factors such as tire degradation, track position dynamics, and compound wear rates.</li><li>Real-Time Recommendations: Delivers instant strategy recommendations by processing current race conditions in milliseconds.</li><li>Strategic Edge: Facilitates the comparison of aggressive, balanced, and conservative strategies, complete with confidence scoring and risk assessment.</li></ul>The system architecture involves processing raw race data through feature engineering, feeding it into a robust Random Forest model, and exposing the predictions via a Flask API to a dynamic dashboard. Key technologies powering PitVision AI include Python, Scikit-Learn, Pandas, NumPy, Flask, and Plotly.js, ensuring a powerful and efficient analytical experience.