AGDC: Automatic Garbage Detection and Collection
Siddhant Bansal, Seema Patel, Ishita Shah, Alpesh Patel, Jagruti, Makwana, Rajesh Thakker

TL;DR
This paper presents an AI-based robotic system for real-time garbage detection and collection, capable of distinguishing valuables from waste with high confidence and operating efficiently on low-cost hardware.
Contribution
The paper introduces an integrated AI-driven robotic system for automatic garbage detection and collection, demonstrating real-time performance on a Raspberry Pi.
Findings
Achieves 90%+ confidence in garbage detection
Operates at 3-4 frames per second on Raspberry Pi
Successfully distinguishes valuables from garbage
Abstract
Waste management is one of the significant problems throughout the world. Contemporaneous methods find it difficult to manage the volume of solid waste generated by the growing urban population. In this paper, we propose a system which is very hygienic and cheap that uses Artificial Intelligence algorithms for detection of the garbage. Once the garbage is detected the system calculates the position of the garbage by the use of the camera only. The proposed system is capable of distinguishing between valuables and garbage with more than 95% confidence in real-time. Finally, a robotic arm controlled by the microcontroller is used to pick up the garbage and places it in the bin. Concluding, the paper explains a system that is capable of working as a human in terms of inspecting and collecting the garbage. The system is able to achieve 3-4 frames per second on the Raspberry Pi, capable of…
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Taxonomy
TopicsAdvanced Neural Network Applications · Water Quality Monitoring Technologies · Video Surveillance and Tracking Methods
