Around three years after the Gurugram Metropolitan Development Authority (GMDA) mooted a project for a closed-circuit television cameras-based Surveillance and Adaptive Traffic Management System for the Millennium City, its first phase is expected to be completed by March this year with the installation of around 1,200 CCTV cameras.
It will have artificial intelligence and features such as traffic signal violation detection, overspeeding detection, face recognition and reading of number plates at 200-odd places, including major intersections.
Another 800 cameras would be installed during the Phase-II of the project.
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P.K. Aggarwal, adviser, Smart City, GMDA, told
The laying of captive optical fibre for the project began in 2018 and the work of camera installation started last year. “We have a captive optical fibre network of around 400 km. It is our own network. We have not hired it from anyone. It connects all these cameras to the GMDA’s Integrated Command and Control Centre (ICCC), monitored by our Smart City team. It is also used by many other agencies, including the police,” said Mr. Aggarwal.
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These cameras with artificial intelligence are not only used for surveillance and traffic monitoring, but are also capable of other functions such as crowd detection, detection of unidentified objects and face recognition of criminals. It helps the police in detecting violation of traffic signal, overspeeding and driving without a helmet.
“It also helps in tracking of vehicles with a particular colour and registration number. The police have provided us the registration number of stolen vehicles and the same have been fed into the system. The moment any of these stolen vehicles is detected, the location of the vehicle is identified and the culprits are arrested,” said Mr. Aggarwal.
It makes Gurugram one of the first cities in the country to have a robust surveillance system in place with the help of CCTV cameras with artificial intelligence. The administration has also used the cameras for COVID-19-related surveillance to ensure social distancing, wearing of masks and avoiding gatherings. Nippon Electric Company (NEC) is the GMDA’s main contractor for the project as a master system integrator.
These cameras are a mix of four different types: fixed cameras, red light violation detection (RLVD) cameras, automatic number plate reading (ANPR) cameras and dome cameras. “While the fixed cameras are mostly used for surveillance, the RLVD and ANPR cameras are installed together. At each intersection, there is usually one RLVD camera and three ANPRs with one for each lane. We are installing 315 RLVD and ANPR cameras. The dome cameras are for face recognition at crowded places such as metro stations, railway stations, shopping malls and temples,” said Mr. Aggarwal.
GMDA’s sub-contractor for the project, Vehant Technologies, a pioneer in artificial intelligence/ machine learning-based security surveillance, has already started the work for installing the 315 RLVD and ANPR cameras at 29 major intersections, including Bakhtawar Chowk, Rezangla Chowk, Mehrauli-Gurgaon Road, Galleria Market, Jharsa Chowk, IFFCO Chowk, HUDA City Center, ABW Tower, Rajiv Chowk, Subhash Chowk, Bristol Chowk, Vatika Chowk, Signature Tower, Hero Honda Chowk, IMT Manesar Chowk, Atul Kataria Chowk, and Sector 55/56 crossing. The total cost of this project is ₹60 crore.
E-challan generation
The system automatically encrypts and transfers the data of violation to the centralised server at Traffic Police headquarters in Sushant Lok-I, besides the GMDA’s ICCC. The system also facilitates e-challan generation along with photo/video evidence which is then sent to the violators’ mobile phone through SMS. The system is capable of 24×7 operations. This solution will have an overview camera to capture the zoomed-out picture of an entire area when there has been a red-light violation. The ANPR will read the number plate of the offending vehicle and store it in the database.
Anoop G. Prabhu, CTO and co-founder, Vehant Technologies, said these cameras had a special feature to capture images at night and even during bad weather. This will help the city in making roads safer and reducing traffic accidents.