Publications / 2022 Proceedings of the 39th ISARC, Bogotá, Colombia

Development of Framework for Highway Lawn Condition Monitoring using UAV Images

Yeseul Kim, Seongyong Kim, Yosuke Yajima, Javier Irizary and Yong K. Cho
Pages 444-450 (2022 Proceedings of the 39th ISARC, Bogotá, Colombia, ISBN 978-952-69524-2-0, ISSN 2413-5844)

Planning, monitoring, and maintenance of highway assets is an essential, long-term operation for successful civil infrastructure management. These monitoring and maintenance activities are usually carried out manually, suffering from time-consuming, costly, potentially dangerous tasks. The advancements in Unmanned Aerial Vehicles (UAVs) and computer vision technologies have demonstrated the potential to enable automation of the monitoring workflows. Existing UAS-based approaches are used for various management; however, there was no study to examine the feasibility of aerial image-based computer vision algorithms for the purpose of lawn condition monitoring. This study aims to provide periodic and easy-to-use UAV technology for civil infrastructure maintenance. We developed the comprehensive framework from UAS data collection to build a deep learning model suitable to distinguish areas of interest with vague boundaries robustly, process the outputs into geo-database, and visualize them through a Geographic Information Systems (GIS) platform. The outcome of the proposed framework displays the overall mowing quality in the highway environment in an intuitive way to support decision-making in the management.

Keywords: Civil infrastructure management; Computer-vision; UAVs; Deep Learning; Lawn mowing condition assessment