DEVELOPMENT - Home - IoT Solutions World Congress · development with an iot platform innovation ... aws the iot application platform harvests models ... mobile app bi/reporting

TERESA TUNG, PH.D.

DEVELOPMENT

WITH AN

IoT PLATFORM

INNOVATION

THROUGH AGILITY

Copyright © 2016 Accenture All rights reserved.

THE PLATFORM CORE

THE ROLE OF THE

IoT PLATFORM

IoT is an iterative process that starts with an initial use case that is then rapidly adapted. Faster deployment and iteration result in better applications, more accurate analytics, better outcomes.

PLATFORM ACCELERATES DEVELOPMENT

Agility to rapidly develop and evolve use case. Scale number of devices, volumes of data, analytical models.

PLATFORM GROWS NEW USE CASES

Agility to harvest, discover, and reuse IoT components. Scale horizontal components to scale across verticals.

10s

Models

3,500

msg/sec

1 Env

AWS

1000s

Models

6,000

msg/sec

3 Env

AWS

THE IoT APPLICATION

PLATFORM

HARVESTS

MODELS

DEVICES

CLOUD

DATA

APPLICATIONS

PLATFORM ACCELERATES

2

PL

AT

FO

RM

G

RO

WS

ENABLING AGILITY AND SCALE OF APPLICATIONS

Copyright © 2016 Accenture All rights reserved. 3

A HOW TO

DRIVE AGILITY WITH AN IoT PLATFORM

Infrastructure Management

Application Management

Data Architecture Management

• Infrastructure Deployment

• System Configuration

• System Monitoring

• Asset Model and Relationships

• Visualization

• Hypermedia API

• Domain model and schema

• Data Mapping and Discovery

• Real-time Analytical model

• Batch Analytics

Install, Deploy, Configure, Test,

Link and Monitor

INTEROPERABLE

REFERENCE

ARCHITECTURE

CAPTURE &

CONFIGURE

SPECIFIC INSTANCES

. . .


DEVELOPMENT:

THE FIRST APP

BUILD IT ALL: BASE COMPONENTS

AND CLIENT SPECIFIC INTERFACES

ASSET

HEALTH

LOW-

LOW

DETECT

CURVE

FITTING

TIME

SERIES

CLIENT

INSTANCE

CLIENT

INSTANCE

DEVICE

INSTANCE

AWS

EAST

DEVICE

INSTANCE

MODELS

DEVICES

CLOUD

DATA

APPLICATIONS

SMART WATER

12 weeksInitial real-time streamingBase set of components


DEVELOPMENT:

THE NEW APP

CONFIGURE AND REUSE;

FOCUS ON DOMAIN-SPECIFICS

ASSET

HEALTH

SURVIVAL

ANALYSIS

CURVE

FITTING

TIME

SERIES

CLIENT

INSURANCE

AGE,

MANUFACTURE,

LOAD

CLIENT

INSURANCE

AWS

EAST

RISK

ANALYSIS

AGE

DEVICE

INSTANCE

DEVICE

INSTANCE

MODELS

DEVICES

CLOUD

DATA

APPLICATIONS

SMART GRID

8 weeksLeverage existing baseContribute new components


DEVELOPMENT:

THE NEW CAPABILITY

REUSE MOST OF THE STACK; ADD NEW

CAPABILITY AND HARVEST

MODELS

DEVICES

CLOUD

DATA

APPLICATIONS

ASSET

HEALTH

DETECT

IMAGE

IMAGES

CLIENT

INSTANCE

CLIENT

INSTANCE

AWS

EAST

DEVICE

INSTANCE

Caffe

OIL & GAS

2 weeksMain focus on domain specificHeavy reuse of components

NEW

NEW

NEW


CONFIGURE TO DEVELOP

CAPTURE FOR REUSE

PUTTING THE “INTERNET” IN IoT

2. CAPTURE

FOR REUSE

3. CONFIGURE TO

RAPIDLY DEPLOY

1. DEVELOP FOR

INTEROPERABILITY

Platform relevance requires an ecosystem

effect. Ease extension and harvest of new

capabilities via a self-service model.

Automation simplifies deployment. Parallelism

allows brute force comparison of components

in champion-challenger fashion. Self-learning

recommendations assist discovery and identify

new relevant components.

Design assuming heterogeneity across the

stack – devices, analytics compute engines,

datastores, applications. Establish interoperable

and asynchronous patterns.

Domain Knowledge GraphSmart Water

System Metadata


LEGEND

8

DEVELOP FOR INTEROPERABILITY

CONFIGURABLE PIPELINE

Platform Build

Platform Configure

3rd party Integration

Client-specific Build

RAPID VISUALIZATION

DEVELOPMENT

FRAMEWORK augments BI tools to create analytics applications

DATA VIRTUALIZATION

presents a single logical access interface to all data stores

ANALYTICS LIFECYCLE

MANAGEMENT

manages configuring, launching, and monitoring analytics models

DEVICE MANAGEMENT

is vendor agnostic

CLOUD MANAGEMENT

is deployable across cloud

providers

PLATFORM MANAGER

INDUSTRY ENABLERS

ACCESS LAYERS

API MANAGER

EGRESS GATEWAY ADAPTERS

Platform Admin UI

Configuration / Monitoring

Developer Portal /Catalog

Web Apps Mobile Apps Business Intelligence Adhoc Analysis

Mediation

Service AssuranceCustomer

Subscription Relationship

Manager Software Manager

Business Rules Manager

Device Inventory

Device Manager

INGRESS GATEWAY ADAPTERS

INGRESS GATEWAY ADAPTERS

STREAMING LEG

BATCH LEG

DATA MANAGER

ANALYTICS

FEDERATED SECURITY

Device Comm. Manager

RTU

Intel Gateway

Device Agent

Batch Data IngestStaging

(SFTP, HDFS)

Storage Manager

Post-Process Event Router

Virtualized Data Access (Hive, PrestoDB)

Data Service Layer (API)

HA NoSQL Warehouse

RDBMS Data Lake

ETL Orchestration

Spark

KinesisAnalytics Layer

(SAS, R)

Stream Processing

Pre Processor

Batch Processing

Post Processing

IAM

Active Directory / Customer ID

External Gateway

Legacy Data Gateway

Notification HubDevice Manager

Device Comm. Manager

HTTPS

TCP/IP

External to Platform


H&PS

Muscular/skeletal diagrams, cell systems

RESOURCES

Asset and workforce tracking, dispatch management, resource allocation

FINANCIAL SERVICES

Candlestick, OHCL indicators, geographical risk, lender-to-lender, and loan tranches

PRODUCTS

factory schematics

TELCO

3D globe of call data, network diagrams, security threat maps

9

APPLICATION

INTEROPERABILITY

THE VIZ STACK THE VIZ COMPONENTS

WEB CLIENT

APPLICATION

HTML, CSS, JavascriptSPAs, React.js, Angular.js, Backbone.js, etc

SERVER

APPLICATION

Java, Javascript, C#, PythonREST API, SOAP, sockets

DATA STORAGE

MySQL, Redshift, Teradata, Hana, OracleRDBMS, NoSQL, Document Stores, etc

TH

E S

TA

CK

A

STANDARDS

For how to build reusable industry specific visualizations

B

APP TEMPLATES

That drive decision science based user experience

C

APIS

Data type specific APIs that map to data input format standards

Dimensions

Data Input Format

Styling

Lifecycle

Code Structure

Layouts

MVC Patterns

Interactions

Guided Decisions

Geospatial

Tabular

Network

Hierarchical

Time Series

Aardvark Sample

D

DOMAIN SPECIFIC

LIBRARY

Needed for a variety of problems in different industries.

Example are:

Pronounced “Aardvark”—the Rapid Visualization Development Framework makes it easier to manage custom applications to supplement BI tools


MODEL

INTEROPERABILITY

1. Data Science Playground

2. Deployment Wizard

Quality

Control

Center

UNIQUE FEATURES

3. MonitoringDiagnostics

4. Maintenance 5. Wiki

Server

REFERENCE ARCHITECTURE MODEL LIFECYCLE COMPONENTS

AUTOMATED ANALYTICS

USERS

Data Scientists Business Analysts

MODEL MANAGEMENT

Runtime VerifierDeployment &

SchedulerMonitoring

Service

Model StoreTrained Model

StoreMetadata Store

APIModel Interface

Templates

RUNTIME ENVIRONMENTS

Distributed Computing Scientific Computing

SCRIPT-BASED OBJECT-BASED

Analytics modeling

Statistical analysis

Machine learning algorithms

Clustering Association Classification Regression

• Uni-/multi-variate analysis

• Bayesian

• Principle component analysis (PCA)

• K-means

• Hierarchical

• Expectation-Maximization (EM)

• DBSCAN

• A priori

• FP-Growth

• Eclat

• Decision tree

• K-nearest neighbor

• Support Vector Machine (SVM)

• Neural Networks

• ARIMA

• Logistic

• Regression tree


DATA INTEROPERABILITY

MANAGE DATA CONSUMPTION ACROSS

DIFFERENT STORES AND DIFFERENT FORMATS

MobileApp

BI/ReportingSingle View of

Enterprise DataSupply Chain Management

Analytics

DATA VIRTUALIZATION

Data Federation Query Plan Enterprise SecurityETL

Streams

Network Sensor Readings

Usage Sensor Readings

Maintenance Logs

CustomerContacts

SiteInventory

ServiceOrders

Customer Service Records

Site Manager Contacts

REFERENCE ARCHITECTURE DATA COMPONENTS

INGESTION PIPELINES

Type Drive Workflow

Rule Driven ETLQuality and

ReconciliationSource-Based

Enrichment

Web ServicesRDBMS Warehouse Data Lake In-memory Flat Files NoSQL

RDBMS EDW Document Store Time Series DB

METADATA PROVIDES CONTEXT


2. CAPTURE FOR REUSE

AN ILLUSTRATIVE EXAMPLE

Has Instance

Has Subclass

“Core relationship”

LEGEND

Analytics Type

Sensor Data KindProperty Optimal Store

Infra: Datastore

has_sensor_data_kind

has_reading_type

ConfigurationOptimal Store: RDBMS

Time SeriesOptimal Store: Columnar

Forecasted

Raw

Sensor Data

Sensor Readings

Sensor

has_sensor

_readings

has_sensor

_data

has_datastore

has_analytics

_type

has_sensor_readings

Pressure Instance A DataPressure Instance Ahas_sensor

_data

has_analytics_type

has_sensor_data_kind

PressurePressure Sensor

has_sensor

_readingshas_reading_type


3. CONFIGURE

TO RAPIDLY DEPLOY

SCALE THE IoT PLATFORM

WITH NEW APPLICATIONS

SCALE NEW APPLICATIONS

WITH AN IoT PLATFORM

THE PLATFORM CORE

CAPABILITIES SMART WATER

12 weeksInitial real-time streamingBase set of components

SMART GRID

8 weeksLeverage existing baseContribute new components

OIL & GAS

2 weeksMain focus on domain specificHeavy reuse of components

Applications

Cloud

Data

Models

Devices

Reuse

Harvest

Harvest

Harvest

Reuse

Reuse


IoT IS A PLATFORM OF PLATFORMS

NOT ABOUT “YOUR PLATFORM,” BUT

ABOUT AN ECOSYSTEM OF PLATFORMS

Social

Health

Enterprise Cloud

Telco

Industrial


THE PROMISE OF IoT

DRIVING TO OUTCOMES

AND AN AUTONOMOUS

PULL ECONOMY

http://www3.weforum.org/docs/WEFUSA_IndustrialInternet_Report2015.pdf

FROM WORLD ECONOMIC FORUM REPORT*

2015: INDUSTRIAL INTERNET OF THINGS…

*WEF Report authored by Accenture

FROM

PRODUCTS TO SERVICES OUTCOMES AUTONOMY

• Improved asset utilization and tracking

• Operational cost reduction

• Equipment productivity enhancement

• Improved worker productivity, safety and working conditions

• Remote equipment operation

• New ‘as-a-service’ business -models (e.g. pay-per-use)

• Product / Service hybrids

• Software based services

• Data monetization

• Open APIs / Developer Networks

• Continuous demand-sensing

• Perceptive response

• Integrated human-machine / robot workforce

• Digital labor

• End to end automation

• Resource optimizationand waste reduction

• Pay-per-outcome models

• Shared risk

• New connected ecosystems

• Platform-enabled data marketplaces

• Products-as-a-platform

• Industry boundaries blur

OPERATIONAL

EFFICIENCY

NEW PRODUCTS,

SERVICES AND

BUSINESS MODELS

AUTONOMOUS

PULL ECONOMY

OUTCOME-BASED

ECONOMY

http://www3.weforum.org/docs/WEFUSA_IndustrialInternet_Report2015.pdf

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DEVELOPMENT - Home - IoT Solutions World Congress · development with an iot platform innovation ... aws the iot application platform harvests models ... mobile app bi/reporting