Internet of Things (IoT) & Big Data Analytics Training




IoT overview

IoT history and evolution

Standards and requirements

IoT enabling technologies

Market trends

Functionalities and structure


Big Data for IoT

4V- Volume, velocity, variety and veracity of Big Data

Why Big Data is important in IoT

Big Data vs legacy data in IoT

Hadoop for IoT-when and why?

Storage technique for image, Geospatial and video data

Distributed database

Parallel computing basics for IoT


Big Data Analytics Techniques

Introduction to R (statistical tool)

Data exploration

Data preparation and visualization

Cluster analysis and Decision Trees

End to End Analytics


Architecture of IoT

Key components

Hardware and firmware

Device drivers and  application software

Cloud connectivity

Sensors systems

Networking protocol structure

Semantic Web 3.0 Standard for M2M and IoT


IoT technologies

Bluetooth Smart Technology

IEEE 802.15.4, IEEE 802.15.4e, 802.11ah

Relay Access Point (AP)

Sensor networks

ZigBee and RFID

Target Wake Time (TWT)

SuperSpeed USB Inter-Chip (SSIC)


Lowpower SoC


IoT Communication and Networking

Serial communication

Power consumption and optimization

Wired connectivity


Grouping of stations

Augmented Realit

Machine Learning in Small-Data


IoT Deployment and management

Mobile integration

Convergence with Social Networks

Value chain and Business models

User centric cloud based services

Data Visualization

Lifecycle solution management

Real-time response and delay

End-to-end security


New IoT product- Product requirement document  for IoT

State of the present art and review of existing technology in the market place

Suggestion for new features and technologies based on market analysis and patent issues

Detailed technical specs for new products- System, software, hardware, mechanical, installation etc.

Packaging and documentation requirements

Servicing and customer support requirements

High level design (HLD) for understanding of product concept

Release plan for phase wise introduction of the new features

Skill set for the development team and proposed project plan -cost & duration

Target manufacturing price


Machine learning for intelligent IoT

Introduction to Machine learning

Learning classification techniques

Bayesian Prediction-preparing training file

Support Vector Machine

Image and video analytic for IoT

Fraud and alert analytic through IoT

Bio –metric ID integration with IoT

Real Time Analytic/Stream Analytic

Scalability issues of IoT and machine learning

What are the architectural implementation of Machine learning for IoT


Security in IoT implementation

Why security is absolutely essential for IoT

Mechanism of security breach in IOT layer

Privacy enhancing technologies

Fundamental of network security

Encryption and cryptography implementation for IoT data

Security standard for available platform

European legislation for security in IoT platform

Secure booting

Device authentication

Firewalling and IPS

Updates and patches


 Cloud based IoT platforms

SQL vs NoSQL-Which one is good for your IoT application

Open sourced vs. Licensed Database

Available M2M cloud platform







CISCO M2M platform

AT &T M2M platform

Google M2M platform


Common IoT systems

Home automation

Energy optimization in Home



Smart Smoke alarm

BAC ( Blood alcohol monitoring ) for drug abusers under probation

Pet cam for Pet lovers

Wearable IOT

Mobile parking ticketing system

Indoor location tracking in Retail store

Home health care

Smart Sports Watch