Blockchain + Big Data + AI + IoT Integration

©2019 Xanadu Big Data, LLC All Rights Reserved www.xanadubigdata.com
Blockchain + Big Data + AI + IoT
Integration
January 16, 2019
Alex G. Lee (alexglee@xanadubigdata.com)

©2019 Xanadu Big Data, LLC All Rights Reserved
Contents
-Blockchain Components
-Blockchain Reference Architecture
-Blockchain Platforms: Ethereum
-Blockchain Platforms: Hyperledger
-Blockchain Use Cases
-Blockchain 3.0
-Emerging Blockchain Technology
-Big Data Introduction
-Big Data Analysis Flow
-Big Data Use Cases
-IoT Introduction
-IoT Use Cases
-IoT Analytics
-Challenges of IoT Big Data Analytics Applications

-Artificial Intelligence Overview
-Artificial Intelligence Revolution
-Deep Learning Introduction
-Deep Learning Use Cases
-Automated Skin Cancer Classification
-Automated Diabetic Retinopathy Classification
-Portable Ultrasound Devices
-Big Data in IoT & Deep Learning
-The Fourth Industrial Revolution?
-AI Investment
-IoT Startups by Industry & Patents
-AI Startups by Industry & Patents
-Blockchain Startups by Industry & Patents

-Blockchain + IoT Integration
-Blockchain + IoT Use Cases: IIoT & SCM
-Blockchain + AI Integration
-Blockchain + AI Integration Demo
-Blockchain + Big Data Integration
-Blockchain + Big Data + AI+ IoT Integration Example

Blockchain Components
source: Building Blockchain Apps using Ethereum & Hyperledger@Udemy

Blockchain Reference Architecture

Blockchain Platforms: Ethereum
source: Blockchain Applications: A Hands-On Approach@A. Bahga & V. Madisetti

Blockchain Platforms: Hyperledger
source: ChainDigit

Blockchain Use Cases
How blockchain can streamline healthcare: Link
Restart Energy Democracy - Blockchain Infrastructure for Energy Supply:
Link
Walmart's food safety solution using IBM Food Trust built on the IBM
Blockchain Platform: Link
Blockchain Insurance Industry Initiative: Link
Blockchain 3D printing 'Smart Manufacturing': Link
Blockchain's Vast Potential To The World Of Music: Link

Blockchain 3.0
source: Dimitri D. Jonghe@Ocean

Emerging Blockchain Technology
source: Blockchain for Business: The New Industrial Revolution @Udemy

Alibaba Group founder and executive chairman Jack Ma:
“The era of Data Technology (DT) is here and
it will surpass the Information Technology era.”
Lots of data is being collected and warehoused:
Web data, E-commerce, Bank/Credit Card transactions, Social Networks
Google processes 20 PB a day (2008)
Facebook has 2.5 PB of user data + processes 15 TB/day (2009)
eBay has 6.5 PB of user data + 50 TB/day (5/2009)
CERN’s Large Hydron Collider (LHC) generates 15 PB a year
Key enablers growth of Big Data:
Increase of low cost storage capacities
Increase of high performance processing power
Availability of data
Big Data Introduction

Big Data Analysis Flow

Big Data Use Cases
How Netflix Leverages Big Data: Link

A. IoT Components
IoT devices: Devices that can sense/recognize their surrounding environments
(including position/movement/identification) and communicate with other devices
Networks: Connecting/communicating medium/infrastructure that can
interconnect devices and connect devices to the internet
IT systems: Back-end or embedded systems that can process information
(data) obtained by the IoT devices (e.g. cloud computing/big data analytics) and provide
the value added services exploiting the information
B. IoT Application Value Propositions
Automation: Providing various automation services for the customers’ job
to be done (e.g., order the out of stock product automatically; self-driving car)
Care: Caring for customers (e.g., monitor person’ s body status and provide
various health care services; control customer’s home cooling and heating/
lighting system for energy savings)
Business/Industry Intelligence: Providing better working/production
tools/environments (e.g., analyze customers’ shopping behavior for proactive
promotion/advertisement; industrial assets management)
Entertainment: Providing fun to customers (e.g., augmented reality games)
Internet of Things Innovation: Link
IoT Introduction

According to Industrial Internet Insights Research Report from GE and
Accenture, the Industrial Internet — the combination of Cloud Big Data, AI
with the Internet of Things — will produce huge opportunities for
companies in Aviation, Oil and Gas, Transportation, Power Generation
and Distribution, Manufacturing, Healthcare and Mining industries.
Big Data with the Internet of Things will help manufacturing sector to
design new business models and facilitate cost effective operation and
supply chain solutions.
IoT Use Cases

IoT Analytics
source: DATA Science for IoT@Ajit Jaokar

How to provide interoperability among heterogenious IoT data streams in
formats, velocities, and semantics?
How to provide data reliability by taking into account noisy and
incomplete nature of IoT data streams?
How to process nearly real-time streaming IoT data?
How to deal with temporal and special dependences of IoT data?
How to comply with security and privacy requirements of IoT data?
Challenges of IoT Big Data Analytics Applications

Artificial Intelligence Overview
Source: https://www.geospatialworld.net/blogs/difference-between-ai%EF%BB%BF-machine-learning-and-deep-learning/

Artificial Intelligence Revolution
AI Research Trends
Large-scale machine learning
Deep learning
Reinforcement learning
Computer vision
Natural Language Processing
Robotics
Internet of Things (IoT)
Collaborative autonomous systems
AI BY DOMAIN
TRANSPORTATION
Smarter cars
Self-driving vehicles
Transportation planning
On-demand transportation
Interacting with people
HOME/SERVICE ROBOTS
Vacuum cleaners
Home robots
HEALTHCARE
The clinical setting
Healthcare analytics
Healthcare robotics
Mobile health
Elder care
EDUCATION
Teaching robots
Intelligent Tutoring Systems (ITS) and online
learning
Learning analytics
PUBLIC SAFETY AND SECURITY
EMPLOYMENT AND WORKPLACE
ENTERTAINMENT

Deep Learning Introduction
Convolutional Neural Networks (CNNs): image/video analysis
Source: Deep Learning A-Z™: Hands-On Artificial Neural Networks by SuperDataScience@udemy
Recurrent Neural Networks (RNNs):time series analysis
Reinforcement Learning (RL): automatically determine the ideal behaviour
within a specific context, in order to maximize its performance for a specific goal
Source: Reinforcement Learning in Python by Lazy Programmer Inc.@udemy

Deep Learning Use Cases
CNN + RNN
Source: SoftPoint Consultores S.L.
Deep RL
Source: Mobileye

Dermatologist-level classification of skin cancer with deep
neural networks by Stanford University researchers
Train Inception v3 CNN using a dataset of 129,450 clinical consisting of 2,032
different diseases: Test its performance against 21 board-certified
dermatologists on biopsy-proven clinical images with two critical binary
classification use cases: malignant carcinomas versus benign seborrheic
keratoses; and malignant melanomas versus benign nevi. The deep learning
CNN outperforms the average of the dermatologists at skin cancer
classification .
Automated Skin Cancer Classification
source: https://cs.stanford.edu/people/esteva/nature/

Google's Research In Artificial Intelligence Helps In
Preventing Blindness Caused by Diabetes
Google Brain has collaborated with doctors in India and US to help them
diagnose DR. The team has collected over 128,000 images that were each
evaluated by 3-7 ophthalmologists from a panel of 54 ophthalmologists. These
images were fed to a deep learning algorithm for creating a model to detect
Diabetic Retinopathy. The predictions from Google Brain’s neural network
algorithm were so close that it is considered to be on par with the
diagnosis of experienced ophthalmologists.
Automated Diabetic Retinopathy Classification
source: https://www.youtube.com/watch?v=oOeZ7IgEN4o

Portable Ultrasound Devices

Big Data in IoT & Deep Learning
Big Data IoT Deep Learning
Volume:
Size of Data
Very large volumes of
data from sensors and
connected devices
Increase in algorithm
complexity and
computing time
Velocity:
Data Processing Speed
Real time streaming data
of very shot time scales,
high frequencies, high
ingestion rates
Difficulty in data learning
process in a timely
manner
Variety:
Different Types of Data
Heterogeneous datasets
from geographically
distributed diverse IoT
sensors and connected
devices
Increase in data
processing diversity for
different data
characteristics and
behavior
Veracity:
Truthfulness of Data
Noisy & incomplete data
which are characterized
by uncertainty; Data
security issues
Significant increase in
pre-processing of data

What is happening now in technological breakthroughs?
Self-learning machines can analyze big data from business
& from digitized real world (IoT) rapidly and objectively than
human beings (AI) to create additional value (Big Data).
The Fourth Industrial Revolution?
Industry 4.0 Industrial Internet

AI Investment

IoT Startups by Industry & Patents

AI Startups by Industry & Patents

Blockchain Startups by Industry & Patents

Blockchain + IoT Integration
source: IoT and Blockchain Convergence@Ahmed Banafa
IoTeX, Decentralized Network for Internet of Things: Link

Blockchain + IoT Use Cases: IIoT & SCM

Ocean, Decentralized Data Exchange Protocol to Unlock Data for AI
Overview of Ocean Protocol: Link
Cortex, Decentralized AI Computing System
AI On the Blockchain: Link
SingularityNET, Decentralized Global AI Network
SingularityNET is building the world's first AI-as-a-Service platform: Link
Blockchain + AI Integration

Blockchain + AI Integration Demo

Blockchain + Big Data Integration
source: BigChainDB white paper; Dimitri D. Jonghe@BigChainDB

Example of Blockchain + Big Data + AI+ IoT Integration System

Thank you
Xanadu Big Data, LLC

Blockchain + Big Data + AI + IoT Integration

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