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Waste management is a critical challenge in
modern society, especially with the increasing amount of
municipal waste generated daily. Traditional waste
segregation methods are mostly manual, time-consuming, and
often lead to improper disposal due to lack of awareness and
human error. Improper segregation of wet and dry waste can
cause environmental pollution, health hazards, and inefficient
recycling processes. To address these issues, this project
presents a microcontroller-based Smart Trash Segregation
System that automates the process of waste classification
using sensors. The proposed system improves accuracy,
efficiency, and hygiene while reducing human intervention in
waste handling.
In this project, different sensors such as an IR sensor and a
moisture sensor are used to detect the presence and type of
waste. When waste is placed in the system, the IR sensor
detects the object, and the moisture sensor analyzes its
moisture content to determine whether it is wet or dry waste.
The sensor data is processed by a microcontroller like the
Arduino Uno, which makes decisions based on predefined
threshold values. According to the classification, a servo
motor is activated to direct the waste into the appropriate bin.
A display unit such as an LCD provides real-time feedback by
showing messages like “Wet Waste” or “Dry Waste,”
enhancing user interaction.
The Smart Trash Segregation System offers a cost-effective,
reliable, and user-friendly solution for efficient waste
management. It can be implemented in homes, public places,
and institutions to promote proper waste disposal practices.
The system also provides a foundation for future
enhancements such as IoT-based monitoring and advanced
waste classification techniques, making it a scalable and
environmentally beneficial solution.
"SMART TRASH SEGREGATION SYSTEM", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 3, page no.b543-b546, March-2026, Available :http://www.ijrti.org/papers/IJRTI2603160.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator