ML Based Smart Garbage Sorting and Monitoring System / (Record no. 611882)

000 -LEADER
fixed length control field 01916nam a22001817a 4500
003 - CONTROL NUMBER IDENTIFIER
control field NUST
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240926132736.0
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 621.382,AHM
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Ahmad, Haseeb
9 (RLIN) 19090
245 ## - TITLE STATEMENT
Title ML Based Smart Garbage Sorting and Monitoring System /
Statement of responsibility, etc. Haseeb Ahmad, Avez Qadeer, Muneeba Tahir.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. MCS, NUST
Name of publisher, distributor, etc. Rawalpindi
Date of publication, distribution, etc. 2024
300 ## - PHYSICAL DESCRIPTION
Extent 65 p
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Garbage collection, sorting and recycling are major issues in the present-day world. This existing projects sort or recycle after the collection of garbage at one place that requires a lot of human effort and is inefficient. With the urbanization of the world, such a system can prove to be inefficient causing a lot of losses and disease spread. This Project focuses on developing a Machine Learning based Garbage Sorting and Monitoring System to deal with the inefficiencies of manual waste sorting. The project aims to automate waste sorting processes, reduce errors, and enable real-time monitoring in waste management. By leveraging machine learning algorithms and sensor integration, the system targets improved recycling efficiency, reduced contamination, and data-driven waste management decisions. Challenges include algorithm accuracy in diverse conditions and real-time processing on resource-constrained devices. The project has made significant progress in dataset collection, preprocessing, and supervised learning, with upcoming milestones including hardware design, IoT-based monitoring system implementation, mobile application development and system integration. The mobile application will help the management of public areas to monitor garbage levels and take actions accordingly. This innovative approach promises to revolutionize waste management practices for environmental sustainability.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element UG EE Project
9 (RLIN) 118090
651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME
Geographic name BEE-57
9 (RLIN) 125983
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Supervisor Dr. Javed Iqbal
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Project Report

No items available.

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