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Industrial Research And Consultancy Centre
Video analytics for compliance and quality monitoring in MoRD skill development centres
Video analytics for compliance and quality monitoring in MoRD skill development centres

Deen Dayal Upadhyaya Grameen Kaushalya Yojana (DDU-GKY) is a placement linked skill development scheme for rural poor youth by the Ministry of Rural Development (MoRD). It is an important component of the National Skill Development Policy. The DDU-GKY skilling ecosystem consists of MoRD; State missions; project implementing agencies or training partners; and technical support agencies. Both generic (soft skills, English and Information Technology) and trade-specific training is offered to youth at various training centers in partnership with the third-party training agencies.

To enable monitoring and assessment of quality of training offered at these centers, these skill development centers are equipped with CCTV cameras for 24X7 surveillance. DDU-GKY is looking forward to use modern technology-based solutions to help ensure compliance and quality standards in the various training centers. They approached us for our help on automated or semi-automated Person counting analysis of videos from the surveillance cameras installed at these skill development centers by leveraging state-of-the-art machine learning and computer vision techniques for video analytics. The expected outcome of this project is a software solution and its deployment for automated analysis of security camera footage videos from the skill development centers across India, the results of which will be accessible via a dashboard web application.

We are actively working on building state-of- the-art machine learning models which, given classroom footages, will help identify name of trainer (face recognition), how late a class started (motion detection), number of students wearing boys / girls uniform (apparel detection, counting), presence / absence of DDU-GKY signage (object
detection) and so on. We have already built some prototypes around some of these problems.

Prof. Ganesh Ramakrishnan