A smart, sensor-driven conveyor system that sorts waste automatically: Conveyor Belt: Made from stitched foam, powered using a PVC pipe, 3D-printed coupling, and ball bearings. Inductive Proximity Sensor: Detects metal waste. Moisture Sensor: Detects wet waste. Servo Motor: Pushes waste into appropriate bins based on sensor input. Frame: Laser-cut plywood for structure and stability. This approach enables a low-cost, functional prototype that helps reduce human effort in sorting and promotes better waste management practices. 

Idea: The project proposes an automated waste sorting system that uses sensors and robotics to sort waste based on material type. Instead of relying on data-heavy machine learning and image recognition, the solution uses simple and effective sensor technologies to achieve sustainability goals in waste management. Solution Brainstorming Journey: Initial Concept: Use machine learning and computer vision to detect waste types. Challenge: Requires a large, high-quality dataset and significant computational power. Decision: Dropped due to complexity and resource constraints. Final Concept: Use sensor-based detection (instead of AI) for practical, reliable implementation.