Reuben Balasabas | Zyvell Ann Dayapera | Patricia Anne Lapitan
With the increasing environmental problems that humans are facing, numerous methods of recycling and waste management have been implemented all over the world. This research developed a system that follows the method of a reverse vending machine that rewards the user in every recycling act performed. Image processing was used to detect the inputs while the method of Deep Learning was used to identify the validity of the inputs. Raspberry Pi 3 B+ was used as the main controller unit because of its capability and suitability on performing image processing. The Raspberry Pi camera, as the secondary component on detection, was used to take shots of the input to be processed and identified by the microcontroller with the applied deep learning method in it. For the mechanism of a reverse vending machine implemented, a weight sensor was used to compute the rewards of the user. Since bottles are light objects, a simple database was used for the users to save their accumulated points and to claim them when they wanted to. Applying these concepts, the project resulted in a system with the ability to detect and identify an object and to take part in the waste segregation promoted by the government.
ISSN 1908-3866 (Print)
Philippine E-Journals
