Sure, let’s sketch a tiny prototype. The idea is to combine physics with a bit of sentiment analysis. 1. **Data gathering** – collect real‑time weather data: temperature, humidity, aerosol content, wind speed, and sky clarity from a local weather API. 2. **Radiance model** – use a simplified Rayleigh‑Mie scattering function to compute the spectral distribution of light at each minute. 3. **Poetic score** – feed the spectral profile into a small neural net trained on human‑rated sunrise photos (color warmth, contrast, mood words). The net outputs a “poetic‑ness” score. 4. **Prediction loop** – run the model every minute, track the peak score, and alert when it surpasses a user‑defined threshold. In code form (Python‑ish pseudocode): ``` while True: weather = get_weather() spectrum = scattering_model(weather) score = poetic_net(spectrum) if score > threshold: notify_user() sleep(60) ``` You can tweak the neural net with more subjective labels—like “inspiring” or “melancholy”—to fine‑tune what feels poetic to you. The math is just a baseline; the art comes from the training data. Happy experimenting!