The world of urban mobility is changing fast, and cities are grappling with the impact on safety. A rapid growth in urban populations, combined with more cars, trucks and public transport vehicles, makes the task of providing safe mobility a complex challenge. The task is further complicated by unsafe driving behaviour. India records 5 lakh road accidents every year, one of the highest in the world, in which about 1.5 lakh people die and another 3 lakh become crippled. Therefore, enhancing road safety is a paramount concern when considering the development of smart cities. 

Indian entrepreneurs and startups are rising to the occasion by integrating artificial intelligence for inventing smart mobility solutions. Here we present three such case studies of AI-driven tools – by Nayan, PathPartner and Netradyne – that are helping to enhance road safety in India.

• AI for smart monitoring of roads, infrastructure and traffic: Nayan's AI-powered engine for high-precision monitoring of roads and traffic uses video feed from smartphone apps of drivers. It is a useful model for smart mobility that can be used for enhancing road safety and planning smart cities. Nayan crawls billions of datapoints on the roadways in search of traffic violations, infrastructural issues and road hazards. It is a crowdsourcing application that needs to be downloaded by commuters on their smartphone, which can then be kept on their vehicle’s dashboard to function as a mobile camera. Other ways for real-time data collection include sources such as street cameras, drone cameras and highway CCTVs. Anyone who uses the app for providing visual monitoring through their mobile device is paid digitally on a daily basis. Nayan has entered into strategic partnerships with various government departments in India, such as Delhi Police, Ministry of Road Transport and Highways, and Ministry of Micro, Small and Medium Enterprises. It also counts Dubai Police as an important international partner. Read more...
• Boosting road safety by detecting drowsy and distracted drivers through AI: PathPartner’s Driver Monitoring System uses advanced computer vision algorithms to detect, predict and prevent driver distraction. An in-car camera is capable of precise monitoring of driver's facial expressions and eye movements, including driver Identification, drowsiness detection and prediction, driver distraction alert, driver action classification, driver emotion estimation, and in-cabin occupancy. Advanced analysis is possible even under unfavourable operating conditions such as poor illumination, dark glasses and different camera positions. It is suitable to be integrated into a wide range of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) applications. PathPartner DMS is platform agnostic and works on hybrid architectures including ARM, DSP, GPU, FPGA & vision accelerators. PathPartner Driver Monitoring Solution has achieved 95% accuracy in detecting scenarios of driver distraction. It is a powerful solution to be deployed by commercial fleet owners, automotive vendors and Original Equipment Manufactures (OEMs). Read more...
• AI for reducing the number of road accidents: Netradyne’s efforts are focused towards reducing the number of accidents and improving safety culture through AI-enabled tools. The on-road behaviour of drivers of commercial vehicles forms an important part of road safety, where speed and proper management of following distance can be the difference between a minor dent and a catastrophic collision. Driveri is an AI-driven fleet safety platform that captures and analyses 100% of driving time, delivering real-time insights and alerts and identifying areas for improvement. Driveri is the most advanced driver safety camera, with artificial intelligence and edge computing embedded in the device to capture and analyse data in real-time. Unlike legacy platforms that rely on g-force triggers to record video to then be uploaded to the cloud and reviewed by humans, thousands of data point are analysed directly on the Driveri device, delivering real-time insights and alerts. This provides a more complete safety picture, identifying potential events before they happen and capturing the true cause of driving events. The result is deep insight into the driving environment and timely delivery of meaningful data, with a focus on positive driver recognition. Read more...

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