Green Stop: a Mumbai commute reset that runs on a local open-weight model

Описание и применение

Green Stop помогает жителям Мумбаи использовать свободное время в пути, предлагая конкретные зеленые места, которые можно пройти за отведённые минуты, без использования облачных сервисов.

Задача

Mumbai commuters lose hours to traffic: a 1‑hour trip becomes 3. Telling tired people to "go touch grass" after that doesn't work, since nobody wants a detour.

Результат

Green Stop provides commuters with a precise green spot that can be reached within their spare time, reducing extra commute time and improving mood.

Рабочий процесс

• User enters current location and minutes spare
• Python geocodes location via OpenStreetMap Nominatim
• Python matches to hand‑picked CSV spots and OSM parks/gardens/beaches
• Python calculates walk distance (to spot + 5 min break + back) using straight‑line distance ×1.3 at 5 km/h
• Python builds facts card
• Gemma 3 4B via Ollama generates a 2‑sentence friendly note
• Gradio UI displays card and Google Maps walking‑directions link

Доказательства

Mumbai commuters lose hours to traffic: a 1-hour trip becomes 3.

Источник

Green Stop takes where you are and how many minutes you can spare. It finds a green spot you can walk to and back in that time and gives you: the spot's name and full address, walking time and total time needed, live temperature and AQI, a Google Maps walking-directions link, a short friendly note from a local LLM, in English, Hindi or Marathi

Источник

Python finds the facts and the LLM only adds a human note.

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The model runs on my laptop and the app has no accounts, no tracking and no cloud LLM. The place cache stays local.

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I tested Green Stop on my own commute from [10th Oct]. Here is a real run: Input: Marine Lines Station, Mumbai, [50] minutes, English

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The address was not precise. OpenStreetMap's reverse lookup returned "Mumbai Coastal Road - Phase I, Navjeevan Wadi, Kalbadevi..." instead of "Marine Drive".

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