Aerowave-AI

Data-Driven Weather Predictor & Ambient Sound Synthesizer

Product Requirements Document

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1. Overview

Aerowave-AI is a web application that predicts weather conditions using real-time and historical data, then dynamically generates or selects an ambient soundscape that matches the forecasted or current weather. Instead of just reading a forecast, users experience it — rain sounds for rain, wind for storms, birdsong for clear skies — turning weather data into an immersive audio layer for focus, relaxation, or ambience.

2. Problem Statement

Weather apps present data (temperature, precipitation %, wind speed) in a purely visual/numeric format. This is functional but not experiential — it doesn't help users feel the conditions outside, and it offers no secondary utility beyond information lookup. Meanwhile, ambient sound apps (for focus, sleep, relaxation) require users to manually pick a soundscape, disconnected from their actual environment.

Aerowave-AI bridges these two categories: it uses live weather data to automatically drive an ambient sound experience, giving users a reason to keep it open beyond a quick forecast check.

3. Goals

• Provide accurate, easy-to-read weather predictions (current + short-term forecast).
• Automatically generate/select ambient audio that matches the weather condition in real time.
• Create a calming, immersive user experience suitable for focus, relaxation, or background ambience.
• Keep the interface minimal and fast — weather + sound, no clutter.

Non-Goals

• Aerowave-AI is not intended to replace full-featured weather services (e.g. radar maps, severe weather alerts, long-range 10-day forecasting).
• Not a full music streaming or playlist platform — sound is generative/ambient, not song-based.
• No native mobile app in this version (web-only, though responsive).

4. Target Users

Persona	Need
Remote workers / students	Background ambience that reflects the outside world while focusing
Relaxation / sleep users	Calming, weather-themed soundscapes
Weather-curious users	A more engaging way to check conditions than a plain forecast card

5. Core Features

5.1 Weather Prediction Engine

• Fetches real-time weather data (temperature, precipitation, wind, humidity, cloud cover) from a weather data API.
• Displays current conditions and short-term forecast (e.g. next few hours / days).
• Location-based (auto-detect or manual city search).

5.2 Ambient Sound Synthesizer

• Maps weather conditions to corresponding ambient audio layers:
  • Rain → rainfall sounds (light/heavy variants based on intensity)
  • Thunderstorms → rain + distant thunder
  • Wind → wind/breeze layers scaled to wind speed
  • Clear/sunny → light ambient tones, birdsong
  • Snow → soft, muted ambient layer
  • Cloudy/overcast → subdued ambient hum
• Smooth crossfade transitions when weather conditions change (no jarring audio cuts).
• Layered audio system — multiple conditions (e.g. wind + rain) can blend simultaneously.

5.3 User Controls

• Play/pause ambient audio.
• Volume control.
• Manual override — user can preview other weather-sound combinations regardless of actual conditions.
• Location switching.

6. User Flow

1. User opens Aerowave-AI in browser.
2. User enters a city.
3. Weather data is fetched and displayed (current + forecast).
4. Sound engine automatically selects/blends the matching ambient soundscape.
5. Audio begins playing (or waits for user play action, depending on autoplay policy).
6. As weather updates (polling interval), audio crossfades to reflect new conditions.

7. System Architecture (High-Level)

[Weather API] → [Backend/Data Layer] → [Prediction Logic] → [Frontend]
                                                              ├── Weather Display UI
                                                              └── Audio Engine (Web Audio API)

• Frontend: Web app UI rendering forecast data and audio controls.
• Data Layer: Fetches and normalizes weather data from external API(s).
• Sound Mapping Logic: Rules/model mapping weather state → audio layer selection and blend weights.
• Audio Engine: Handles playback, looping, and crossfading of ambient tracks (e.g. via Web Audio API).

(Fill in specific stack, hosting, and API providers used in your implementation.)

8. Data Sources

• Weather data: third-party weather API (e.g. OpenWeatherMap, WeatherAPI, or equivalent) — specify which one is used.
• Audio assets: royalty-free ambient/nature sound library or procedurally generated audio.

9. Success Metrics

• Session duration (avg. time app/audio stays open).
• Return visits / retention.
• Accuracy of weather data vs. source API.
• Smoothness of audio transitions (no perceptible gaps/clicks — qualitative).

10. Risks & Considerations

Risk	Mitigation
Browser autoplay restrictions block audio on load	Require explicit user play action on first load
Weather API rate limits / downtime	Cache last known data, graceful fallback UI
Audio looping sounds repetitive over long sessions	Use varied/layered loops, subtle randomization
Inaccurate weather → mismatched sound	Rely on trusted API source, clear "last updated" timestamp

11. Status

✅ Project completed — core weather-to-sound mapping and playback implemented.

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This document outlines product intent and scope for reference and onboarding purposes.