| 000 -LEADER |
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02813nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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ft8860 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20251209135157.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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251209b ||||| |||| 00| 0 eng d |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
T58.7 G83 2025 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 245 ## - TITLE STATEMENT |
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| Title |
Smartsuri: A mobile-based item recycling classifier application utilizing convolutional neural network with event notification and recommendation system |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2025 |
| 300 ## - PHYSICAL DESCRIPTION |
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Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 336 ## - CONTENT TYPE |
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| Source |
text |
| Content type term |
text |
| Content type code |
text |
| 337 ## - MEDIA TYPE |
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unmediated |
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unmediated |
| Media type code |
unmediated |
| 338 ## - CARRIER TYPE |
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| Source |
volume |
| Carrier type term |
volume |
| Carrier type code |
volume |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
ABSTRACT: The growing ineffectiveness and inaccuracy of recycling add to the pollution of recycling streams, decreasing the ability to manage waste effectively. This solution is accompanied by insufficient advanced technological solutions, and a general minimization of waste separation and classification by the user. This study presents the development and evaluation of SMARTSURI, an artificial intelligence (AI0-enabled computer vision/image recognition system based on convolution neural network (CNN) for enabling more accurate and efficient recycling in real-time. SMARTSURI helps minimize contamination and improve recycling with its classification of recyclable waste, biodegradable waste, and residual waste. CNN-based classification, real-time notifications, and recommendation systems are defined. The core components will be implemented with Flutter, Python and Django. SMARTSURI using features to bring the public into the recycling process. A CNN-based classification system facilitates effective analysis by automatically evaluating visual data, such as images, to detect and classify patterns, objects, or features with high accuracy, thereby supporting recycling processes and improving waste management efficiency. A notification system alerts users to local recycling and donation events, and a recommendation feature offers suggestions for repurposing recyclables. Real-time notification keeps the users informed about recycling campaigns, hence ensuring their active participation in sustainability. These elements serve to bridge the gap between knowledge and action, and motivate improved waste disposal habits. The application augments the potential for users to take part in sustainability initiatives, by providing the exact information needed at the right time at a localized level. SMARTSURI could be widely deployed in the future to reduce pollution in recycling streams for a cleaner environment. |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
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| Classification |
Filipiniana |
| 655 ## - INDEX TERM--GENRE/FORM |
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| Genre/form data or focus term |
academic writing |
| 942 ## - ADDED ENTRY ELEMENTS |
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| Source of classification or shelving scheme |
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| Item type |
Thesis/Dissertation |