MARC details
| 000 -LEADER |
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| fixed length control field |
03279nam a22003377a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250714183118.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250714b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
TUPM |
| Language of cataloging |
English |
| Transcribing agency |
TUPM |
| Modifying agency |
TUPM |
| Description conventions |
rda |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
BTH TK 870 |
| Item number |
B47 2025 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Bernado, Julius Nikolai D. |
| Relator term |
author |
| 245 ## - TITLE STATEMENT |
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| Title |
Geopavenet: |
| Remainder of title |
Automated road pavement damage classifaction and severity identification with geolocation using jetson nao and yolov8/ |
| Statement of responsibility, etc. |
Julius Nikolai D. Bernado, Victor Sebastian D. Bondoc, Renato Jr. T. Panis, Efren Jr. D. Pastores, Gary Clyde T. Rabe, and Jevon A. Silvano.-- |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Manila: |
| Name of publisher, distributor, etc. |
Technological University of the Philippines, |
| Date of publication, distribution, etc. |
2025. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
ix, 138pages: |
| Dimensions |
29cm. |
| 336 ## - CONTENT TYPE |
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| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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| Source |
rdacarrier |
| 500 ## - GENERAL NOTE |
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| General note |
Bachelor's thesis |
| 502 ## - DISSERTATION NOTE |
|---|
| Dissertation note |
College of Engineering.-- |
| Degree type |
Bachelor of science in electronics engineering: |
| Name of granting institution |
Technological University of the Philippines, |
| Year degree granted |
2025. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographic references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
In the Philippines, road pavement damage poses significant threats to road safety,<br/>often leading to accidents, vehicular damage, and increased maintenance costs. Existing<br/>road survey methods that check pavement damage can take time, require significant<br/>labor, can be expensive, and make subjective evaluations, hurting accuracy and efficiency<br/>through delay in maintenance and repair on the damage that is occurring. GeoPaveNet is<br/>designed to innovate the traditional method of inspecting road pavement damages by<br/>using deep learning models, and geolocation; creating an automated, real-time system<br/>shifting traditional road pavement assessments using artificial intelligence (AI). Intended<br/>to be a potential adaptation by the Department of Public Works and Highways (DPWH),<br/>offering an innovative approach in improving road condition assessments and streamline<br/>maintenance planning processes. Using a moving vehicle, a high resolution camera is<br/>mounted capturing images of road pavement damages in real-time, processed by the<br/>NVIDIA Jetson Nano, YOLOv8 as the deep-learning model classifying road pavement<br/>damage classes: potholes, cracks, alligator cracks, pumping and depression, with severity<br/>levels determined based on the criteria provided in the DPWH Guides and Standards for<br/>Labelling Road Damage, which include factors such as crack width, depth, deformation,<br/>and damage pattern. A VK-162 GPS module was included to geotag each detected road<br/>damage by taking longitudinal and latitude location coordinates in real time for accurate<br/>location mapping and comprehensive reporting of the conditions of the roads. The trained<br/>object detection model had a mean Average Precision (mAP) of 0.423 after 100 epochs of<br/>training, which reflects the model's ability to detect and classify multiple types of<br/>pavement defects for practical, real-world deployment. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Pavement detection |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Damage classification |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Geolocation tracking |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Bondoc, Victor Sebastian D. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Panis, Renato Jr. T. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Pastores, Efren Jr. D. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Rabe, Gary Clyde T. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Silvano, Jevon A. |
| Relator term |
author |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Bachelor's Thesis COE |
| Suppress in OPAC |
No |