SEVA aims to leverage cutting-edge computer vision and AI technologies to create ethical, inclusive and resilient communities. The TAG focuses on human-centric solutions to serve society with smart technologies and easy accessibility while simultaneously monitoring and sustaining natural and urban environments. Through advanced visual analytics, SEVA enables data-driven insights for urban planning, smart cities, environmental monitoring and disaster management. Research emphasizes smart solutions with privacy-preserving, explainability and fair AI systems that serve society responsibly. By fostering interdisciplinary research across engineering, environmental studies and generative AI techniques for collective well-being, the TAG promotes innovation that is both impactful and scalable. Ultimately, SEVA promotes transforming cities, communities and environments into smart, sustainable, safe and responsible ecosystems, aligned with NEP 2020, the Smart Cities Mission, and the UN Sustainable Development Goals
The mission of Smart Society & Environment through Vision Analytics TAG is to design, develop, and deploy advanced vision-based intelligent models on optical images, satellite images and drone images, etc. to address challenges in building smart cities, societies and environments. The TAG aims to build privacy-preserving, scalable and explainable frameworks for edge and mobile devices that enable smart urban services, environmental monitoring and disaster resilience. By integrating multimodal vision data and real-time vision systems, SEVA supports data-driven decision-making for inclusive smart cities and sustainable ecosystems. Through strong collaboration with academia, industry, and governance bodies, the TAG aims to translates research outcomes into deployable solutions for collective well-being and public good.
Smart
environment
Smart
society
Disaster
monitoring
TAG Coordinator &
Assistant Professor(Sl.Gd)
Ongoing research and research domian:Small object detection and recognition in images, Facial craniotomy using images.
Assistant Professor
Ongoing research and research domian: ML/DL in remote sensing image processing, 3D-object detection using DL
Assistant Professor(OC)
Ongoing research and research domian: Small object detection and recognition in images