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| title: Smart Bin AI | |
| emoji: ποΈ | |
| colorFrom: green | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: 4.44.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # Smart Bin AI β Waste Management Intelligence | |
| Two ML models for smart city waste management: | |
| **Model 1 β Fill Level Predictor** | |
| - Input: live ultrasonic + weight sensor readings | |
| - Output: exact fill %, GREEN/YELLOW/RED status, confidence score | |
| - Algorithm: Random Forest (300 trees) | |
| - Accuracy: 99%+ classification, MAE < 1% | |
| **Model 2 β Garbage Flow Forecaster** | |
| - Input: current sensor readings + fill trend | |
| - Output: predicted fill % at +6h and +12h | |
| - Algorithm: Gradient Boosting | |
| - Accuracy: R2 = 0.77 (6h), 0.70 (12h) | |
| **Dataset:** 72,000 rows (100 bins Γ 720 hours) with realistic IoT sensor simulation including rush hour patterns, weekend effects, zone differences, sensor drift, and collection events. | |
| **Validation:** GroupKFold cross-validation (zero bin leakage between train and test) |