Smartsuri: A mobile-based item recycling classifier application utilizing convolutional neural network with event notification and recommendation system

By: Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
Language: English Publisher: . . c2025Description: Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025Content type: text Media type: unmediated Carrier type: volumeGenre/Form: academic writingDDC classification: . LOC classification: T58.7 G83 2025
Contents:
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.
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Item type Current location Home library Collection Call number Status Date due Barcode Item holds
Thesis/Dissertation PLM
PLM
Filipiniana Section
Filipiniana-Thesis T58.7 G83 2025 (Browse shelf) Available FT8860
Total holds: 0

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.

Filipiniana

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