Waste Management System

DOI

No DOI

Conference

Innovations in Computing, Materials and Communication Technologies

Organised By

IES College of Engineering

Conference Date

15 May 2023

Pages

61-64

Article Type

Research Article

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No DOI available for cross-reference

This report explores the use of machine learning and Django web development framework for waste management detection. The report highlights the benefits of such a system, including improved waste sorting, reduced labor costs, and improved recycling rates. The report also discusses the challenges of implementing such a system, such as the need for a large dataset for training machine learning models and the requirement for appropriate infrastructure and resources. The technical aspects of developing a waste management system using machine learning and Django are discussed in detail, including the process of image processing, model training, and the use of Django for web application development. The report concludes that such a system can be an effective solution for waste management and environmental sustainability. This report provides references for further reading on the topic and is intended to be a useful resource for researchers, waste management practitioners, and policymakers interested in the application of machine learning and web frameworks for waste management.