International Conference on Big data, Machine Learning and IOT (ICBMI)

Event Overview

The International Conference on Big Data, Machine Learning and IoT (ICBMI) will be held on 12 February 2026 in Ahmedabad, Gujarat, India. The Internet of Things (IoT) provides a platform that enables networks of devices—such as sensors and smart meters—to communicate, analyse data, and collaboratively process information for individuals and organizations. These IoT networks generate large volumes of data in diverse formats and through various protocols, which can be stored and processed using cloud technologies. Big Data (BD), characterized by its volume, velocity, variety, and veracity, plays a central role in deriving meaningful insights from this information. When combined with machine learning, AI, statistical models, and other advanced analytical techniques, Big Data enables deep analysis, forecasting, and informed decision-making. 

This integrated approach helps organizations identify weaknesses, optimize operations, and create significant value. The conference will be organized by the International Research Forum for Scientific Research in the city of Ahmedabad, Gujarat, India.

Key Information

Event Status

Active

Organizer

International Research forum for Scientific Research

Organizing Secretary

Conference Coordinator

Conference Inquiry Email-ID

info.irfsr@gmail.com

Program Schedule

Physical Schedule

08:30 AM – 09:00 AM On-Site Check-In & Welcome Coffee

09:10 AM – 09:30 AM Inaugural Address & Conference Overview

12:00 PM – 01:00 PM Networking Lunch

03:00 PM – 03:15 PM Closing Ceremony & Awards

Virtual Schedule

09:00 AM – 09:10 AM Virtual Check-In & Orientation

12:00 PM – 01:00 PM Break

03:00 PM – 03:15 PM Closing Ceremony & Digital Certificate Instructions

Organizer Information

International Research Forum for Scientific Research (IRFSR)

Email: info.irfsr@gmail.com

Website: irfsr.com

Major topics covered for this event

Big Data Architectures

Real-Time Data Processing

Distributed Storage Systems (HDFS, NoSQL)

Data Governance and Privacy

Scalable Data Analytics

Big Data for Smart Cities

Predictive Analytics

Data Quality and Integration

Cloud-Based Big Data Platforms

Data Visualization and Dashboards

Supervised and Unsupervised Learning

Deep Learning Frameworks (TensorFlow, PyTorch)

Federated and Transfer Learning

ML in Cybersecurity

Reinforcement Learning

Natural Language Processing (NLP)

ML in Computer Vision

Explainable AI (XAI)

ML for Healthcare and Finance

AutoML and Model Optimization

IoT System Architectures

Edge and Fog Computing

Sensor Networks and Embedded Systems

IoT Security and Privacy

Smart Homes and Buildings

Industrial IoT (IIoT)

IoT in Agriculture

Interoperability and Standardization

IoT Data Analytics

Blockchain for IoT