AUTOMATIC WASTE SEGREGATION USING IMAGE PROCESSING

AUTOMATIC WASTE SEGREGATION USING IMAGE PROCESSING

Registration ID: IJNRD_200068

Published ID: IJNRD2306489

DOI: Click Here to Get

Haritha K N , Gopika S Pillai , Jyothi Krishnan M

Image Processing, Municipal Solid Waste (MSW), Machine learning, Waste Classification, CNN

Waste management and systematic sorting of them are considered to be a significant role in ecological development around the world. The procedure in which the garbage is segregated is by splitting the garbage into divergent components. This is regularly done by handpicking physically which sometimes causes hazardous and dreadful impact on human health if not appropriately done. Currently used waste sorting technologies have limitations on the composition of recyclable waste, which makes them specialized. Thus, the preliminary sorting of Municipal Solid Waste (MSW) is a necessary step, increasing the efficiency of using municipal solid waste as a resource. Our project aims to create an automated waste segregation system using image processing techniques. The ultimate objective is to segregate the waste into two main categories- recyclable and non-recyclable. This would help in easy recovery of useful and recyclable items. The sorting unit performs detection and classification of waste components on a conveyor belt. Unpacked MSW is supplied to the conveyor belt as a sparse feed so that cases of objects overlapping are rare. Images are gathered from a camera and fed to a neural network input, which determines the position and type of detected objects. A L-Shaped structure is used as the sorting unit to move the MSW from the conveyor and classify them to the corresponding bin. The L-Shaped structure which can place the waste materials like cardboard, glass, metal, paper, plastic, and trash waste can be properly dumped in the corresponding recyclable and non-recyclable bin. The wastes are classified primarily into two levels such as recyclable and non-recyclable. These two main classes can be further classified into categories depending on their reusability. The hardware system is a conveyor, camera, L-shaped clamp and Arduino UNO for controlling conveyor, and the software is an image classification algorithm based on machine learning process. To train the neural network we use a database of municipal solid waste images.

Published Paper   E-Certificate

"AUTOMATIC WASTE SEGREGATION USING IMAGE PROCESSING", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 6, page no.e750-e756, June-2023, Available :https://ijnrd.org/papers/IJNRD2306489.pdf

Volume 8 Issue 6, June-2023

Pages : e750-e756

Paper Reg. ID: IJNRD_200068

Published Paper Id: IJNRD2306489

Downloads: 000121280

Research Area: Automation & Control Power System 

Country: Kottayam, Kerala, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2306489.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2306489

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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