The system processes up to 56 thousand screenshots per hour
Last winter in Moscow, three neural networks were tested and implemented, which detect uncleared roads in screenshots from city surveillance cameras, as well as icicles, ice and snow on the roofs of houses. The press service of the Moscow Department of Information Technologies spoke about this.
For several months, neural networks helped specialists from the Center for Automated Recording of Administrative Offenses (CAFAP) identify 15.5 thousand such shortcomings and transmit information about them to the capital’s services. Over the past season, more than 24.9 thousand winter problems were corrected with the help of artificial intelligence.
Head of the city video surveillance department of the capital's DIT Alexey Kornikov said:
Artificial intelligence in the capital’s video surveillance system helps city services identify shortcomings, promptly transfer requests and monitor the execution of work. It processes up to 56 thousand screenshots per hour, relieving specialists from viewing such a colossal volume of images. Thanks to new neural networks in winter, TsAFAP employees could quickly find areas where there is ice, icicles or uncollected snow, including on the roofs of buildings. On behalf of the Mayor of Moscow, we will continue to develop artificial intelligence services to help public utilities, so that the city becomes even cleaner and more comfortable.