Open AccessMonitoring of road damage detection systems using image processing methods and Google Map
Author(s) -
Riny Sulistyowati,
Andy Suryowinoto,
Hari Agus Sujono,
I Iswahyudi
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1010/1/012017
Subject(s) - global positioning system , upload , raspberry pi , computer science , geotagging , road surface , speed limit , digital mapping , enhanced data rates for gsm evolution , computer vision , image processing , artificial intelligence , real time computing , geography , transport engineering , remote sensing , computer security , image (mathematics) , engineering , telecommunications , world wide web , civil engineering , internet of things
In the traffic environment, accidents often occur due to road conditions with holes. This can be fatal for motorcycle riders and car drivers. Therefore, this paper aims to provide a road contour damage information system by detecting potholes on the highway and reporting damage on Google’s maps. So road users, especially vehicle drivers, can be careful when they want to pass that road. The method used in this paper, which uses Werner D. Streidt algorithm threshold values and edge detection in digital image processing to detect holes in the road, as well as mark the coordinates of hole locations and uploads them on Google’s maps, using the Raspberry Pi two embedded devices as a management center data, with a 6M NEO U-box Global Positioning System (GPS) sensor, as geotagging location and CSI camera interface. A A raspberry pi 2 for taking pictures of road surface contours. System testing is carried out in several stages at different times. In daytime conditions, in sunny weather, the system’s success rate in detecting potholes is 83.2%. Whereas with tree barriers, the success rate is 67%, with detection failure 33%. In conclusion, this system succeeded in showing all points of the hole location by giving a mark on the Google Map display application.