Update README.md

README.md

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 license: mit
 short_description: Range safety calculator simulating realistic EV behaviour
 ---
+# Range Safe Mode Prototype
 
+## Overview
+Range Safe Mode is an early functional prototype developed for **Project 2** in  
+*Design and Deployment of AI/ML Systems*.  
+The prototype helps EV drivers quickly determine whether they have enough battery  
+to safely complete a trip using a simple **Safe / Marginal / Unsafe** indicator.
+
+This prototype is designed to test user understanding of multi factor energy  
+prediction not to provide exact real world accuracy.
+
+---
+
+## What the Prototype Does
+The system estimates trip energy using:
+
+- Distance (km)
+- Elevation gain (m)
+- Average speed (km/h)
+- Temperature (°C)
+
+Then compares the required energy against:
+
+- Available battery (kWh)
+- Reserve buffer (kWh)
+
+The output includes:
+
+- **SAFE TO PROCEED**  
+- **MARGINALLY SAFE**  
+- **CHARGING REQUIRED**
+
+A short explanation and a confidence bar are also provided.
+
+---
+
+## Why the Margin Threshold is 5 kWh
+A **5 kWh safety margin** was chosen for the prototype because:
+
+- Most EVs consume **0.15–0.22 kWh per km**, so 5 kWh = ~25–30 km buffer.  
+- It accounts for unexpected factors: sudden speed changes, weather shifts, detours.  
+- Many OEMs recommend keeping a 5-10% buffer for battery health and uncertainty.  
+- It prevents a route from being labeled “safe” when the margin is razor thin.
+
+This number is not meant to be exact, it is a **reasonable, user-friendly buffer**  
+for a prototype that communicates the idea of confidence vs. risk.
+
+---
+
+## How to Use
+1. Enter the battery and trip parameters.  
+2. Click **Submit**.  
+3. Read the safety classification and explanation.  
+4. Adjust inputs to test different scenarios.
+
+---
+
+## Limitations
+This prototype does **not** include:
+
+- Real map routing
+- Live elevation APIs
+- Weather or traffic data
+- Battery aging / degradation
+- Regenerative braking
+- Real EV calibration
+
+Energy estimates are **simulation-based** and meant for conceptual testing only.
+
+---
+
+## Tech Stack
+- Python  
+- Gradio UI  
+- Lightweight simulated EV energy model
+
+---
+
+## Future Extensions
+- Integrate elevation API (OpenElevation)  
+- Add visual "range bubble" map overlay  
+- Recommend fallback chargers  
+- Combine with team features (queue prediction, congestion forecasting)
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference