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

Event Overview

The conference focuses on the Internet of Things (IoT), a platform enabling networks of devices, sensors, smart meters, and other systems to communicate, analyze data, and process information collaboratively for individuals or organizations. IoT networks generate large volumes of data in diverse formats and protocols, which can be efficiently stored and processed in the cloud.

Big Data (BD), characterized by volume, velocity, variety, and veracity, can be combined with machine learning, AI, statistical methods, and advanced analytical techniques to extract valuable insights. Such integration enables organizations to perform forecasting, deep analysis, and optimization, helping identify weaknesses and implement improvements.

ICBMI provides a premier platform for researchers, practitioners, and educators to exchange knowledge, discuss innovations, and explore practical applications in Big Data, Machine Learning, and IoT. 

This event is organized by the International Research Forum for Scientific Research in 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