Raspberry pi waste segregator using convolutional neural network algorithm / (Record no. 30012)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02597nam a2200301 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | CSPC |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250814103523.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250814s2023 ph a b 000 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | CSPC |
| Language of cataloging | eng |
| Transcribing agency | CSPC |
| Description conventions | rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) | |
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) | UTH BSCS B644r 2023 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Bonza, Mary El F. |
| Relator term | author. |
| 245 10 - TITLE STATEMENT | |
| Title | Raspberry pi waste segregator using convolutional neural network algorithm / |
| Statement of responsibility, etc. | Mary El F. Bonza, Jazie T. Dante, and Anerol Leuna Alva S. Sergio |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 119 leaves. |
| 336 ## - CONTENT TYPE | |
| Source | rdacontent |
| Content type term | text |
| 337 ## - MEDIA TYPE | |
| Source | rdamedia |
| Media type term | unmediated |
| 338 ## - CARRIER TYPE | |
| Source | rdacarrier |
| Carrier type term | volume |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Undergraduate Thesis (BSCS) - Computer Science |
| Name of granting institution | Camarines Sur Polytechnic Colleges, 2023 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Includes bibliographic references. |
| 520 3# - SUMMARY, ETC. | |
| Summary, etc. | One of the most prevalent issues in schools nowadays is the enormous amount of waste generated. This issue affects waste management, which causes pollution and other infec-tious diseases that negatively affect daily life. This research was conducted to develop a prototype that would help to determine and classify waste through image processing using the CNN algorithm. The researchers used an experimental research design to perform re-search based on objectives. Also, the researchers collected a total of 5,721 image datasets in school and other images gathered from a reliable internet source. The evaluation method that is utilized in this study is Lobe, to build and train image processing models. Also, con-fusion matrix to evaluate the performance of the classification of the aforementioned algo-rithm. The Raspberry Pi camera is used to capture and detect waste accurately, the camera must be placed in a stable space. Once the waste is captured and detected the algorithm classifies if it is biodegradable, non-biodegradable, or hazardous then the LED light blinks based on the trash bin it belongs to. The model has achieved 45% accuracy. Therefore, the developed prototype successfully shows how efficient and effective the Convolutional Neural Network algorithm is used in image processing to classify waste images into three classifications. In addition, future researchers could utilize another existing algorithm in comparison with this research algorithm. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dante, Jazie T. |
| Relator term | author. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Sergio, Anerol Leuna Alva S. |
| Relator term | author. |
| 720 ## - ADDED ENTRY--UNCONTROLLED NAME | |
| Name | Benitez, Ian P. |
| Relator term | adviser. |
| 720 ## - ADDED ENTRY--UNCONTROLLED NAME | |
| Name | Fortuno, Kaela Marie N. |
| Relator term | chair, panelist. |
| 720 ## - ADDED ENTRY--UNCONTROLLED NAME | |
| Name | Oñate, Joseph Jessie S. |
| Relator term | panelist. |
| 720 ## - ADDED ENTRY--UNCONTROLLED NAME | |
| Name | Onesa, Rosel O. |
| Relator term | panelist. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Suppress in OPAC | No |
| Koha item type | Unpublished Materials |
| Classification part | B644r |
| Item part | BSCS |
| Call number prefix | UTH |
| Call number suffix | 2023 |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Copy number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Main Library | Main Library | Undergraduate Thesis Section | 08/14/2025 | UTH BSCS B644r 2023 | 006692UM | 08/14/2025 | 1-1 | 08/14/2025 | Unpublished Materials |