Research & Initiatives

Internet of Things (IoT)

Medical Image Analysis

Computer Vision

Applications of Deep Learning in IoT Systems

Here at IoT Vision lab, we believe that the future is connected, and that the power of IoT lies in its ability to create intelligent systems that can communicate with each other, learn from each other, and adapt to changing circumstances. By combining IoT with computer vision, we're able to create systems that can not only collect and process data, but also make sense of it in real time.

See Publications

Ongoing Projects

Ulcerative Colitis Detection

Advancing AI-driven analysis of Whole Slide Images (WSIs) for Ulcerative Colitis using expert-annotated histopathological data. The project focuses on computational pathology and automated disease detection to support clinical research. Funded in collaboration with AIIMS Gorakhpur and AIIMS New Delhi.

Colonoscopy & Endoscopy Video Analysis

Developing intelligent video analysis systems for Ulcerative Colitis detection and severity grading using colonoscopy and endoscopy data. The project leverages deep learning and computer vision for gastrointestinal disease assessment. Funded research project.

Person Re-identification

Developing computer vision techniques to identify and match individuals across multiple cameras and varying viewpoints. The project explores deep learning-based visual representations for intelligent surveillance and multi-camera tracking applications.

Jal Jeevan Mission

Exploring AI and data-driven technologies to support water supply monitoring and infrastructure management. The project focuses on intelligent solutions for efficient and sustainable water resource management. Funded by the Government of India under the Jal Jeevan Mission.

PCB Defect Detection

Developing deep learning-based solutions for automated Printed Circuit Board (PCB) defect detection and classification. The project focuses on improving manufacturing quality inspection, reliability, and intelligent automation. Funded by ISRO (Indian Space Research Organisation).

Intelligent PCOS Healthcare Platform

Exploring artificial intelligence and machine learning approaches for Polycystic Ovary Syndrome (PCOS) detection and analysis. The project focuses on leveraging medical data and imaging features to support intelligent healthcare and diagnostic research.