Automated Waste Segregation System Using Robotic Arm

Abstract

Waste management has become a critical environmental and social challenge due to rapid urbanization and population growth. Improper segregation of waste reduces recycling efficiency and increases health risks for workers involved in manual sorting. This paper presents an Automated Waste Segregation System using a Robotic Arm, designed to segregate waste into metal and non-metal categories. The proposed system uses an inductive proximity sensor for metal detection, a microcontroller-based control unit, and a servo motor driven robotic arm for physical segregation. The system minimizes human intervention, improves safety, and provides a compact and cost-effective solution suitable for small-scale applications. Experimental results show reliable detection and accurate placement of waste materials into respective bins.

Introduction

The text describes a low-cost automated waste segregation system designed to improve recycling efficiency and reduce the risks of manual waste handling.

It begins by highlighting the growing problem of waste generation due to urbanization and industrial growth. Since waste is often mixed (plastic, metal, paper, organic, etc.), manual segregation is inefficient, unsafe, and inconsistent. Workers face health hazards, and poor sorting reduces recycling quality, leading to more landfill waste.

To address this, the project proposes an automated system using sensors and a robotic arm to separate waste—specifically focusing on distinguishing between metal and non-metal waste. This approach aims to improve safety, accuracy, and efficiency while keeping the system affordable for small-scale use such as homes, offices, and institutions.

The literature review explains that:

• Manual methods are slow and unsafe.
• Sensor-based systems improve accuracy but can be complex and limited in classification.
• Robotic arm systems reduce human involvement but are often expensive and bulky.
• Existing solutions rarely focus specifically on metal vs. non-metal segregation.

The proposed system addresses these gaps by being compact, low-cost, and focused on metal/non-metal classification using simple sensors and automation.

The system works in stages:

1. A proximity/IR sensor detects waste presence.
2. An inductive sensor identifies whether it is metal or non-metal.
3. A microcontroller processes the data and makes decisions.
4. A robotic arm physically sorts the waste into appropriate bins.

Conclusion

The Automated Waste Segregation System Using a Robotic Arm successfully demonstrates an efficient and hygienic approach to basic waste management by automating the segregation of metal and non-metal waste. The system integrates sensors, an ESP32 microcontroller, and a servo-driven robotic arm to accurately detect, identify, and place waste into the appropriate bins in real time, thereby reducing human involvement and associated health risks. Experimental results show reliable sensor performance, smooth robotic arm operation, and consistent segregation under controlled conditions. The compact design, low-cost components, and ease of implementation make the system suitable for small-scale applications such as households, institutions, and recycling units. Overall, the project establishes a strong foundation for future advancements in smart and intelligent waste segregation systems that support environmental sustainability and improved recycling efficiency.

References

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Copyright

Copyright © 2026 Masira Ali, Tanmay Selote, Tejas Bhoyarkar, Vaibhav Dewangan, Dr. Jaya Bhattad. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.