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Indian Police Roll Out Intelligent Traffic Management System in Bengaluru

The Bengaluru traffic police are rolling out an Intelligent Traffic Management System (ITMS). Artificial intelligence (AI)-enabled cameras will detect traffic violations and issue fines through text messages on offenders’ phones.

The objective is to automatically detect traffic violations in a contactless manner and send auto-generated fines to the violators with minimum human intervention, the special commissioner of police stated. AI and machine learning (ML) technology are used in the ITMS to identify traffic violations automatically.

The ITMS has been implemented at 30 traffic junctions across the city, a report by the government’s AI portal informed. The cameras will detect speed limit violations and red light and stop lane breaches, and offences like helmet-less travel, driving without a seatbelt, triple-riding, and the use of mobile phones while driving.

The system has an AI-enabled solution with 250 automatic number plate recognition cameras and 80 red light violation detection cameras installed at 50 junctions. These cameras, which are active round-the-clock, are expected to save a lot of manpower, which can be redeployed for traffic management and regulation. The data collected with be stored on a server owned by traffic police. In the future, the police force plans to track vehicles without number plates and stolen vehicles.

States across the country are deploying technology to reduce and prevent road accidents and violations. Last year, the Karnataka State Road Transport Corporation (KSRTC) implemented AI-based technologies to limit road accidents and improve passenger safety in buses ]. The corporation floated a tender for the implementation of an AI-powered Collision Warning System (CWS) and Driver Drowsiness System (DDS) for 1,044 buses.

In April this year, under the second phase of the Ministry of Electronics and Information Technology (MeitY)’s Intelligent Transportation System Endeavor for Indian Cities initiative, an indigenous onboard driver assistance and warning system (ODAWS), a bus signal priority system, and a Common Smart IoT Connectiv (CoSMiC) software were launched.

As OpenGov Asia reported, ODAWS incorporates vehicle-borne sensors to monitor driver propensity and vehicle surroundings that send out acoustic and visual alerts. The project involves sub-modules such as the navigational unit, driver assistance console, and mmWave radar sensor. The positional and dynamic characteristics of surrounding vehicles are probed using the mmWave radar sensors. The navigational sensor provides a precise geospatial orientation of the vehicle as well as trends in driving behaviour. The ODAWS algorithm is used to interpret sensor data and offer real-time notifications to the driver, boosting road safety.

The bus signal priority system is an operational strategy that modifies normal traffic signal operations to better accommodate in-service public buses at signal-controlled intersections. Unlike blind priority, which is only used for emergency vehicles, the system operates using conditional priority. It will minimise person delay by providing priority to public transport buses, either through green extensions or red truncations, considering all vehicles approaching a signalised intersection.

CoSMiC is middleware software that provides the standard-based deployment of the Internet of things (IoT), which follows the oneM2M-based global standard. It facilitates users and application service providers in vertical domains to use application-agnostic open standards and interfaces for end-to-end communication with well-defined common service functionalities. The CoSMiC common service layer is used to interface with any vendor-specific standards and to increase interoperability with smart city dashboards.

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