How mayanksh0311/smart-waste-segregation-system works
This Raspberry Pi system detects an item, captures and classifies it locally, then moves servos to sort it. The README also describes Firebase-backed monitoring through a web dashboard. The main runtime is shown from its source; cloud upload and dashboard behavior are included only as documented capabilities, since their wiring is not shown in the sampled Python. Note that the checked-in model.tflite and labels.txt differ from the filenames main.py expects.
Main entry points: main.py Main controller · model.tflite TFLite model · labels.txt Class labels · dashboard.html Live dashboard
Components 11
Detection and classification
- Main controller
main.py - Image classifier
main.py - TFLite model
model.tflite - Class labels
labels.txt
Physical sorting
- Sorting sequence
main.py
IoT monitoring
- Firebase database
- Live dashboard
dashboard.html
Other components
- Waste item
- IR sensor
- Pi camera
- Servo motors
Connections 10
- Waste item → IR sensor: triggers
README.md - IR sensor → Main controller: signals detection
main.py - Main controller → Pi camera: captures image
main.py - Main controller → Image classifier: requests classification
main.py - Image classifier → TFLite model: runs inference
main.py - Image classifier → Class labels: resolves class
main.py - Main controller → Sorting sequence: sorts prediction
main.py - Sorting sequence → Servo motors: moves
main.py - Main controller → Firebase database: uploads classification
README.md - Firebase database → Live dashboard: provides live data
README.md