Police in Hyderabad, over the past few weeks, have identified around 10,000 cases of COVID-19 mask violations through Closed-Circuit Television (CCTV) cameras installed across the city. The three commissionerates — Hyderabad, Cyberabad and Rachakonda — in the city have ramped up their efforts to fine mask violators through the use of artificial intelligence (AI) tools, as COVID-19 cases in the city began to rise in the last month or so.
There are 375,000 lakh cameras fixed within the Hyderabad district limits and 650,000 cameras installed in Hyderabad, Cyberabad and the Rachakonda Commissionerates collectively, according to Telangana Home Minister Mr. Mohammed Mahmood Ali. However, according to a reliable source it is reported that around 2,000 CCTV cameras have been enabled with artificial intelligence under the Greater Hyderabad area to monitor mask violators.
The spokesperson said, “If all the cameras are enabled to track mask violators, then in a day around 50,000 to 60,000 challans may be generated — which is not good. Our focus (by limiting AI to 2,000 cameras) is just to create awareness. If a case is booked against someone, automatically the other person will wear a mask.” It is important to note that this number is only for the Greater Hyderabad limits. Earlier, in 2020, across the three commissionerates, only 335 cameras were AI enabled.
Over a month ago, the Telangana government issued orders directing citizens to wear masks in public places in view of the rising cases in the country. As a result, the city police has deployed artificial intelligence tools as part of its CCTV network to identify mask violators.
In Cyberabad alone, the police have identified over 6,000 mask violators in just a week, Cyberabad Police Commissioner Mr. VC Sajjanar said. He added that, across Telangana there may be around 24,000 cases that have been registered through this system. “We are able to do it through facial recognition and various artificial intelligence algorithms. We have integrated it through the e-challan system.” he said.
