Artificial Intelligence Uses Google Street View To Learn
Australian geospatial scientists have developed a new program to monitor street signs needing replacement or repair by tapping into Google Street View images.
Millions of street signs – including stop signs, speed limit signs, or traffic warnings – are scattered along roads everywhere you go. By nature, these massive infrastructures are challenging to monitor and maintain, currently requiring a time-consuming manual process carried out by workers.
In order to streamline this process, RMIT (Royal Melbourne Institute of Technology) scientists have created an AI-powered software program that’s capable of recognizing and identifying specific street signs by using the Google Street View database. This software has a 96% rate of correctly spotting the beaten down signs, and 98% accuracy in proper identification of the sign.
This technology provides an opportunity to reduce human error in spotting signs as well as significantly reducing costs and time. RMIT’s program creates a much more efficient system, and is able to pinpoint the exact coordinates of each sign in need of repair. This will save local governments time and labor costs that could instead be used to improve other areas of their infrastructures.
Although this is not an end-all solution to monitoring signage infrastructures, it is the first step in being able to easily keep track of and work towards improving the system. There have been a number of AI-driven software programs being developed recently that have related to this, and it will be interesting to see how these technologies advance over time.
Written by Dominick Ronan, Edited by Matthew Durborow & Alexander Fleiss