2017. 3. 10

Edge

Analytics for

IoT Device

Intelligence

1. IoT Trends

2. IoT Analytics

3. Edge Analytics Platform:

Kanga

4. Future Direction

14 1

IoT Trends - Business/Technology (1/3)

Google Cloud Platform

Google : IoT Solution Business using Google Could Platform

MS : Artificial Intelligence IoT Ecosystem based on Azure

GE : Predix Platform Solution & Service Business for Industrial Internet

Microsoft IoT Platform Services

14 2

IoT Trends – IoT Analytics (2/3)

IoT business models will exploit the information collected by “things” in many

ways - for example, to understand customer behavior, to deliver services,

to improve product, and to identify and intercept business moments.

However, IoT demands new analytic approaches: [Gartner, Jan 2016]

■ Tens of billions of connected “things”

The volume of data to be analyzed will increase dramatically

Demanding technologies such as machine learning to identify patterns

.■ Traditional IT approach to data analytics is not always desirable or practical in IoT context, new analytics architectures are emerging

To much data to store, so analysis of data stream must be conducted on the fly

Data filtering and analysis may sometimes distributed in gateways at the edge of the network or

in the “things” themselves to minimize communication over slow networks or when communications

have undesirable side effects, such as increasing battery consumption in sensory nodes.

■ New data types and analysis algorithms for “things” data

Time series data is very common, demanding filters and Fourier transforms

More data are location-aware, demanding geographic information processing

14 3

Cisco: IoT Reference Model & Edge Computing Architecture Suggestion (’14.10)

Intel: IoT Gateway Commercial Product for Real time Analytics ’15.4)

IBM: Edge Analytic Open Source Project Quarks(’16.2)

IBM-Cisco: A Global Partnership with Watson IoT & Cisco Edge Analytics(‘16.6)

IoT Trends - Business/Technology (2/3)

Cisco Edge Analytics Solution Concept Apache Open Source Project Intel Gateway Solutions for IoT

14 4

IoT Analytics – Model

Smart Health

Smart Home Smart Retail Smart

Education

SmartThings Sensors Samsung Gear Samsung Appliance 3rd Party Things

Samsung Hub Devices

14 5

IoT Analytics – Model

Things

Analyze self data of the thing. Things

Analytics

Answer,

Assisting,

Processed Knowledge

External Open Data/Knowledge/IoT Services

Analyze data of all related user/things and service, And provide the

optimal service in which it fits for the overall situation.

Cloud & Big Data Platform

User Query,

Context Information,

Filtered Log

Collect and analyze data of the

user/things which is in the inside of

specific space (ex. Home).

Samsung Hub Devices

Messaging Middleware (IoTivity)

14 6

IoT Analytics – Service Level

Samsung Hub Devices Smart car

Hub

Oven Printer Vehicle

Kitchen Room Classroom Garage

Home Office Factory School Car

Smart

Factory Hub

▶A Room

- Living room

- Kitchen

▶A Place

- Office

- Home

Wearable

Smart watch

3rd Party Service

Connectivity

Connectivity

▶Public

- People, Citizen

- Colleagues

▶A user & Family

- Me

- family

▶Private Things

- Wearable things

- Appliances

Rule market Samsung

Account Intelligence

Geographic Level Service target Level

Samsung IoT Service Platform

Big data

Analytics

▶Town & Country

- Nation, State

- Company

Components

Manufacturing

lines

Assembly

Office

Air Con. Black

Board

Mobile

User

Small brain Big brain Micro brain

14 7

IoT analytics using edge analytics F/W & Big Data Platform

Supporting user profiles/device knowledge for intelligence services

IoT Analytics – Platform & Benefit

Devices on IoT Cloud Storage & Broker

Customers

3rd-party services

Data

In/Out

Analytics

Model

Deploy

Web

/mobile

Data &

Knowledge

API

Analytics API

Edge Analytics F/W

Collect and analyze data of the

user/things which is in the inside of

specific space(Ex. Home). Analyze data of all related user/things and service,

and provide the optimal service in which it fits for the overall situation.

Hub Devices

Big Data

Platform

IoT Cloud

Connection

Server Registration

Server

Data

Storage Gateway

Server

Samsung

Account

Big

Data

Analytics

Real-time analytics Batch analytics

1. Context aware Home Watcher & Controller

using real-time stream data analytics

2. CE-RM & Remote Checkup using device

maintenance/prediction analytics

3. The Function and Content Recommendation

based on analysis of user life

Intelligent

Services

14 8

. User/Product/Market Profile & User & Product Integrated Profiles

Things-Integrated Profile

IoT Analytics – Data Perspective

14 9

Edge Analytics Platform – Kanga

Real-time

Dashboards Kanga IDE

Query Builder and Browser

Big Data Platform

Storage broker

Privacy Management

Library Store/Community

Data Mining

Analytics

model

Complex event script

(Kanga QL)

Event-In Event-Out

Analytics APIs

Logic

Topology

Edge Analytics

Management

Server

3rd Party

Library

Query Optimizer

On-demand

Event Processor Compiler

Continuous Stream I/O API

Stream Processing Engine Search Engine

Message Broker Platform

Plug-in

Manager Time

Series

Library

Statistical

Library

MLR

Library

Default plug-ins

Edge Analytics Framework (Kanga)

Base Library

Large-scale

data-processing engine

Open Source Site : Kanga Lite v1.0 (‘16. 10) : https://github.com/Samsung/Kanga

14 10

Edge Analytics Platform – Kanga Concept Architecture

Real-time Dashboards Kanga IDE

Query Builder and Browser

Query Optimizer

On-demand Event Processor Compiler

Continuous Stream I/O API

Streaming Query Processor

Storm / Node.js Event Processing Engine

Elasticsearch Search Engine

Kafka / ZeroMQ / MQTT Message Broker Platform

Spark / R / Python Large-scale

data-processing engine

14 11

Job Status/Monitoring

Drag-and-drop query (topology) builder

Data visualizer

Edge Analytics Platform – Kanga IDE & Visualizer

Data visualizer Data visualizer

14 12

Future Direction – Kanga Milestone

Kanga IDE (Topology Design/

Query Builder/

Job Monitoring)

Kanga

Visualizer (Report &

Dashboard)

Kanga Main

Common

Library (Collection/

Store/Processing)

Machine

Learning Library (Classification/Clustering/

Outlier detection)

Kanga (Java) / Kanga Lite(node.js)

Kanga

Marketplace

Kanga Suite (Common)

Kanga v1.0 (2016) Kanga v2.0 (2017)

One device supporting

Kanga IDE (Topology Design/

Query Builder/

Job Monitoring

/Deployment)

Kanga

Visualizer (Report &

Dashboard)

Kanga Main

Common

Library (Collection/

Store/Processing)

Machine

Learning Library (Classification/Clustering/

Outlier detection)

Kanga Cloud(Java) / Kanga Desktop(Java) / Kanga Lite(node.js)

Kanga

Marketplace

Kanga Suite (Common)

Multi device & cloud supporting

Reasoning

Library

(Sematic CEP)

High Speed

I/O Library

(Sensor F/W)

Iotivity

(OCF) Library

Open Source : Kanga Lite v1.0 Open Source : Kanga Lite v2.0 (’17.4Q)

14 13

Future Direction – Kanga v2.0

Sensor HW (Vibration/Temperature,)

High speed IO (Sensor) Framework

Kanga lite framework

Application

Sensor data simulator

Kanga lite framework

Application

Layer 1

Layer 2

Layer 3

Layer 4

Real Layer Test Layer

14 14

. Bringing all the elements together

* strong Industry collaboration to accelerate IoT deployments

Summary – Extract Business Value and Take Action

Intelligent Devices

Intelligent System of Systems

Edge Analytics + + = Customer Value

Copyright © 2017 Samsung SDS Co., Ltd. All rights reserved