New Delhi, Dec 21: Union Minister of State for Science & Technology; MoS PMO, Personnel, Public Grievances, Pensions, Atomic Energy, and Space, Dr Jitendra Singh on Thursday provided an update on several “Artificial Intelligence” (AI) initiatives during his reply in the Rajya Sabha.
Responding to a specific query about AI projects under the Department of Atomic Energy (DAE) in the last five years, Dr Singh highlighted a range of initiatives. He said the Department of Atomic Energy (DAE) has actively pursued AI and Machine Learning (ML) research in the last five years, covering areas such as AI-based content verification, anomaly detection, physical intrusion detection, biometric and face recognition, vehicle identification and management, and application behavior and anomaly detection.
Dr Singh mentioned other AI-related research domains, including human interface development, robotics, image processing, medical and biomedical applications, AI/ML development platforms and hardware, high-performance computing, nuclear knowledge management, and optimization problems in nuclear environments. Various AI and ML algorithms/methodologies are employed in machine vision-based inspection systems for nuclear fuel and nuclear fuel assembly components, among other applications, he said.
The minister said the collaboration between the Department of Atomic Energy and academic institutions has led to projects like early detection of breast cancer using thermal/infrared imaging, AI applications for lesion classification, diabetic eye diseases detection using Convolutional Neural Network (CNN), unsupervised radiation field mapping inside cyclotron vault, unsupervised area surveillance by drone, Indian sign language coder and decoder, video compression for low bit-rate video conferencing, and neutron-gamma separation for DAQ system.
“Over the past five years, the Department of Atomic Energy has invested in three projects costing Rs 180 crores, with around Rs 53 crores utilized. These projects have significantly contributed to AI and ML research, empowering the processing of large volumes of data and leading to applications across various domains, including security and cybersecurity,” Dr Jitendra said.
“Indigenous products like the Secured Network Access System (SNAS) have become integral to the cybersecurity infrastructure, monitoring millions of events generated daily in the vast DAE network. The development of AI-based video analytics and cybersecurity tools has matured into reliable technologies, contributing to continuous vigilance and timely insights, operational 24/7,” he added.
