Gurgaon: Commuters flouting lane discipline and heavy vehicles entering the city during restricted hours may soon face automated challans.GMDA is planning to expand the use of its integrated command and control centre (ICCC) for technology-driven enforcement.ICCC serves as the city’s central surveillance and monitoring hub, integrating feeds from CCTV cameras installed across major roads and intersections.The proposed traffic enforcement system — being developed in coordination with Gurgaon traffic police — will use artificial intelligence (AI) and the city’s existing CCTV network to detect lane driving violations.GMDA chief executive officer PC Meena said the authority is leveraging technology to improve both civic service delivery and enforcement. “The proposed AI-based systems are expected to enhance compliance with traffic regulations, improve road safety and allow more efficient monitoring of heavy vehicle movement. It will further strengthen the smart city infrastructure and technology-enabled urban management,” Meena said.Once the system is implemented, motorists found violating lane discipline will be issued e-challans based on camera footage, with notices sent to their registered addresses.At present, traffic police issue challans through both manual enforcement and CCTV-based systems. However, camera-based enforcement is presently limited to Dwarka Expressway and NH8, where the intelligent traffic management system (ITMS) is operational.On these stretches, violations are detected automatically through cameras, although manual enforcement is also carried out. Between Jan 1 and July 15 this year, 61,650 camera-generated challans were issued for lane-changing violations.Manual challans, however, are issued across the city, including sector roads and other arterial roads such as Golf Course Road, where traffic personnel physically detect violations and generate e-challans using the official app.According to traffic police, lane driving violations attract a Rs 500 fine for the first offence, while every subsequent violation carries a penalty of Rs 1,500.GMDA and traffic police are also working on an AI-based mechanism to regulate the movement of heavy vehicles within city limits during restricted hours.Under the proposed system, CCTV cameras will automatically identify vehicles entering the city during “no-entry” periods.Heavy vehicles with valid permissions issued by traffic police will be exempted, while those operating without authorisation will be issued system-generated online challans, a GMDA official said.Alongside the proposed traffic surveillance measures, the authority has integrated the city’s garbage collection fleet with ICCC to allow real-time monitoring of waste transportation across the city.GMDA has integrated all 31 municipal solid waste collection vehicles transporting garbage to the landfill site with ICCC. The registration numbers of these vehicles have been mapped with the city’s CCTV surveillance network, allowing the civic body to monitor their movement in real time.Officials said the integration will help improve oversight of waste transportation, ensure greater accountability and enable quicker intervention in case of operational issues. The system will also help authorities identify instances of littering or improper disposal of waste during transit by tracing the movement of the vehicles through CCTV footage.“The integration of waste collection vehicles with the ICCC will strengthen monitoring of sanitation operations, improve operational efficiency and ensure greater accountability in waste transportation. It will also help us respond more effectively to operational issues and enhance overall service delivery,” Meena said.With the help of ICCC, the monitoring of helmet violation, parking violation, speeding vehicle, accident detection, vehicles of interest (number plate, speed & colour), wrong way and abandoned object is being conducted. At present, around 1,200 CCTV cameras are connected to the ICCC, enabling real-time monitoring of traffic movement. Under Phase II, GMDA is installing an additional 2,700 cameras.
