Dr. Ravi Kiran Sarvadevabhatla, Associate Professor at IIIT Hyderabad (IIITH), outlines several mobility-focused solutions developed at the institute to address challenges in the Indian transportation sector.
The increasing role of artificial intelligence (AI) in daily life has influenced various industries, including education, healthcare, manufacturing, and transportation. While autonomous vehicles have drawn significant attention, the mobility ecosystem has expanded to include broader applications. The i-Hub Data Center, located on the IIITH campus, has been actively involved in interdisciplinary research to address mobility-related challenges.
One of the key initiatives focuses on detecting abnormal traffic patterns and violations, such as riding without helmets, triple riding, and wrong-side driving. Traditional systems use CCTV cameras mounted at intersections to capture and analyse such violations. However, these fixed cameras lack the element of surprise, which can reduce their effectiveness. To address this, IIITH leveraged Bodhyaan, an advanced research vehicle equipped with multiple sensors, to capture traffic data. This mobile system collects videos of violations, categorises them, and makes the footage available for challan generation by the police.
To address widespread wrong-side driving violations by two-wheelers, IIITH utilised dashcams mounted on city cabs and buses to capture traffic footage. This distributed approach ensures data collection across the city, adding an element of surprise and reducing reliance on static cameras. The recorded videos are processed to identify violations, which are then used to issue challans.
A platform similar to Bodhyaan has been developed for two-wheelers to improve safety. It includes technologies to detect falls, provide rider assistance, and develop smart helmets. Additionally, the platform measures riding behavior and generates riding scores, which could be used by insurers or dealers to incentivise safe driving through adjusted premiums or discounts.
In collaboration with multiple research centers at IIITH, a project was initiated to automate infrastructure assessment using drones. Current manual methods of building safety evaluation involve measuring parameters such as height, number of windows, and roof load. The new approach uses drones equipped with computer vision to automatically collect this data, significantly reducing the time required for such assessments. The software developed for this project is user-friendly and can be operated by non-technical personnel.
Another initiative involved assessing the success of tree plantation drives by measuring tree density in specific areas. A two-wheeler fitted with a GoPro camera and GPS was used to collect images and geolocation data. This information was compiled into a dashboard to visualise tree cover across different regions. A similar methodology was employed to map city potholes, with the results also displayed on a dashboard for better road management.
The Intelligent Solutions for Road Safety Through Technology and Engineering (i-RASTE) project, initiated in Nagpur and later extended to Telangana, aims to reduce road accidents using AI. Advanced Driver Assistance Systems (ADAS) with dashcams were installed in city buses to monitor driver behavior, potential collision alerts, and road conditions. This data was combined with road safety awareness sessions for drivers, resulting in fewer recorded alerts and accidents.
The i-Hub Data Center, established under the National Mission on Interdisciplinary Cyber-Physical Systems, is dedicated to developing scalable solutions for mobility-related issues. With an engineering division focused on real-world deployment, the center ensures that research initiatives move beyond prototypes to practical applications.
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