Spaces:
Sleeping
Sleeping
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,44 @@
|
|
| 1 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
|
| 3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
title: Smart FuelTech: AI-Powered Combustion Efficiency Monitor
|
| 2 |
+
emoji: 🔥
|
| 3 |
+
colorFrom: red
|
| 4 |
+
colorTo: purple
|
| 5 |
+
sdk: gradio
|
| 6 |
+
sdk_version: "4.18.0"
|
| 7 |
+
app_file: app.py
|
| 8 |
+
pinned: false
|
| 9 |
+
---
|
| 10 |
|
| 11 |
+
# Smart FuelTech 🔥
|
| 12 |
+
|
| 13 |
+
This tool predicts **combustion efficiency (%)** using a machine learning model trained on coal parameters like:
|
| 14 |
+
|
| 15 |
+
- Volatile Matter (%)
|
| 16 |
+
- Ash Content (%)
|
| 17 |
+
- Total Sulfur (%)
|
| 18 |
+
- Gross Calorific Value (kcal/kg)
|
| 19 |
+
|
| 20 |
+
It also uses **Groq's LLaMA model** to provide **AI-generated suggestions** for improving combustion efficiency.
|
| 21 |
+
|
| 22 |
+
---
|
| 23 |
+
|
| 24 |
+
### How It Works
|
| 25 |
+
|
| 26 |
+
✅ Enter coal properties
|
| 27 |
+
✅ Click "Submit"
|
| 28 |
+
✅ Get predicted efficiency and AI recommendations
|
| 29 |
+
|
| 30 |
+
---
|
| 31 |
+
|
| 32 |
+
### Developed For
|
| 33 |
+
|
| 34 |
+
🚀 **Hackathon Project**
|
| 35 |
+
Organized by **PEC, iCodeGuru, Aspirate Pakistan & Pak Angels**
|
| 36 |
+
|
| 37 |
+
---
|
| 38 |
+
|
| 39 |
+
### Technologies Used
|
| 40 |
+
|
| 41 |
+
- Python
|
| 42 |
+
- Gradio
|
| 43 |
+
- scikit-learn (Random Forest)
|
| 44 |
+
- Groq API (LLaMA model)
|