About AeroWave AI
AeroWave AI is a Data-Driven Weather Predictor and Ambient Sound Synthesizer. It bridges the gap between machine learning and generative audio engineering by transforming real-time climate metrics into an immersive, mathematically synthesized acoustic experience.
System Pipeline & Utility
- Live Data Ingestion: The Flask backend connects with global meteorological APIs to fetch real-time climate parameters instantly.
- Predictive Intelligence: A custom Scikit-Learn Regression model processes this data to forecast future weather trends accurately.
- Procedural Audio: NumPy and SciPy engines translate these predictions into wave equations, generating loopless ambient sounds.
- Automation & Zero-Storage: Fully automated web pipeline generating audio purely via mathematical synthesis and real audio samples without heavy audio files.
Project Team (Group ALPHA)
Developed as a 3rd Semester project at SIET, Nilokheri (Guided by Ms. Diksha).
Backend & API
Kumar Saurabh
Machine Learning
Jayita
Audio Synthesis
Khushbu
Frontend UI
Simran