Integrated Big Data & IoT Analytics Laboratory
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The Integrated Big Data & IoT Analytics Laboratory (IBIoT-Lab) is a research-driven initiative led by Dr. Shwet Ketu, dedicated to advancing the frontiers of intelligent systems through the integration of Big Data Analytics, Internet of Things (IoT), and Next-Generation Network Technologies.
The lab's Core Research Areas include:
Smart Healthcare Data Analytics
Internet of Health Things (IoHT)
IoT-enabled Systems and Architectures
Big Data Processing and Stream Analytics
Wireless Sensor Networks (WSN)
Machine Learning for IoT and Smart Systems
The IBIoT-Lab thrives on a multidisciplinary approach, combining data-driven modeling, algorithm design, and real-world prototyping. Research activities emphasize simulation, data experimentation, and field-level validation using modern tools and platforms.
The lab encourages innovation, project-based learning, and collaborative research among undergraduate, postgraduate, and doctoral students. IBIoT-Lab aims to produce impactful research outcomes in the domains of smart environments, intelligent healthcare, and emerging network technologies—aligning with national and global research priorities.
Copyright (2025). All Rights Reserved.
What we've done
What we've done
Hybrid Internship Program (June–August 2026 Batch)
Hybrid Internship Program (June–August 2026 Batch)
The Integrated Big Data & Internet of Things Analytics (IBIoT) Lab successfully conducted a Hybrid Internship Program designed to provide students with practical exposure to emerging technologies and research-oriented problem solving.
The program offered a blended learning environment combining online expert sessions, hands-on laboratory activities, guided projects, and interactive mentoring. Participants gained practical experience in areas such as Artificial Intelligence, Machine Learning, Internet of Things (IoT), Big Data Analytics, Data Science, and Smart Healthcare applications.
Through structured technical sessions and project-based learning, interns were encouraged to transform theoretical knowledge into practical solutions for real-world challenges. The program also emphasized research methodology, data analysis, technical documentation, presentation skills, and innovation, helping participants develop both technical and professional competencies.
The Hybrid Internship Program reflects the IBIoT Lab's commitment to creating a research-driven, industry-oriented, and innovation-focused learning ecosystem for students and aspiring researchers.
Key Highlights
Hybrid mode combining online learning and hands-on activities
Expert-led technical sessions and mentoring
Practical exposure to AI, ML, IoT, Big Data, and Data Science
Project-based learning and real-world problem solving
Research-oriented guidance and technical skill development
Opportunities for innovation, collaboration, and interdisciplinary learning
Development of technical documentation and presentation skills
Lab PPT.pptx
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