MongoDB IoT City Tour STUTTGART: Industrial Internet, Industry 4.0, Smart Factory & Big Data. By, Bosch SI

© TechMahindra, MongoDB and Bosch Software Innovations GmbH 2014. All rights reserved, also regarding any disposal, exploitation, reproduction, editing, distribution, as well as in the event of applications for industrial property rights.

TechMahindra, MongoDB and Bosch Software Innovations

I o T E U R O P E A N C I T Y T O U R

S T U T T G A R T



Industrial Internet, Industry 4.0, Smart Factory & Big Data



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IoT Predictions (by 2020-22)

7,1tn IoT Solutions Revenue | IDC

Some Big Numbers:

1,9tn IoT Economic Value Add | Gartner

309bn IoT Supplier Revenue | Gartner

50bn Connected Devices | Cisco

14bn Connected Devices | Bosch SI

http://postscapes.com/internet-of-things-market-size



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IoT Predictions (by 2020-22)

7,1tn IoT Solutions Revenue | IDC

Some Big Numbers:

1,9tn IoT Economic Value Add | Gartner

309bn IoT Supplier Revenue | Gartner

50bn Connected Devices | Cisco

14bn Connected Devices | Bosch SI

Some Small Numbers:

http://postscapes.com/internet-of-things-market-size

Peter Middleton, Gartner:By 2020, component costs will have come down to the point that connectivity will become a standard feature, even for processors costing less than

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Inspired by: C Weiss, Holisticon



Bosch Group – IoT Candidates?

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Circle of Concern today

This is where the story ends



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This is where the story starts

Circle of Concern tomorrow



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How the ‘Internet of Things’ impacts global manufacturers

Industrie 4.0 @ Hannover Messe 2013Chancellor Dr. Angela Merkel receives the report „Industrie 4.0“ from Prof. Dr. Henning Kagermann (acatech) and Dr. Siegfried Dais (Bosch)



Smart Factory

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Customer Integrated

Engineering

Resilient Factory

Networked Production

Predictive Maintenance

TechnologyMarketplace

Up-Cycling

Adaptive Logistics

New business models through the convergence of IT & production

Source: Forschungsunion Wirtschaft & Wissenschaft



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The Internet of Things: Nobody can do it alone

Component & Device Manufacturer

Telcos IT Companies and System Integrators

Cloud Services

Integration

Application

PlatformConnec-

tivityModuleChipset Equipment

Software Innovations OfferingM2M Value ChainMachine-to-Machine = applications

without human intervention

„embedded world“ „IT world“



Example: Indoor Asset Tracking

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TechMahindra Track & Trace



Asset Details Page

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Indoor-Localization using WiFi

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Bosch Software Innovations Suite

Manufacturer OperatorCustomer

Identity Management

HTML5/Javascript (Bootstrap/AngularJS)

BPM

- Cisco Position- Mail notification

M2M

- Nutrunner drivers- Smartcards

BRM

-Event evaluation

Third Party Systems

Payment

Cisco MSE

DataBases

Mongo

Mongo

Bosch SI PaaS

TechM/AWS

ERP

NEXO Nutrunner Smart Id Card

Architecture Blueprint

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Outlook: High Accuracy Indoor Localization

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HAIP: High Accuracy Indoor Positioning



Outlook: Vertical Integration + HAIP

Vertical Integration From Field Level

to ERP Automatic creation

of quality lots Full transparency

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Example Architecture



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Common Environment

Business & End User User Interface

App Store

Design Time Repository

Design Tools

Identity Management

User Interface Management

Execution Systems

Business Rules Management

(BRM)

Business Process

Management(BPM)

Device Management

(M2M)

Tenants

Users

Roles

Relations

Authorizations

Distributed Devices

Editors

BRM Rule Models

BPM Process Models

M2M Inform. Models

M2M UI Models

• Modeling• Optimization• Administration• Deployment• Execution, Monitoring

• Modeling• Simulation• Implementation• Execution• Monitoring, Reporting

• Device Integration• SW-Provisioning• Central Registry• Event Management

Foundation: Bosch Software Innovations Suite



M2M Back End

Connecting Physical Devices: Flexible OptionsLocal

NetworkGlobal Network

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2

ZigBee

WiFi Bluetooth

NFC

Backend Hub

GSM UMTSLTEDSL InternetWAN

OPCBACnet

Edge Controller

Edge Node

Edge Controller

– : Depending on hardware performance, timing, reliability, communication cost, different distributed system architectures are supported



AgentHub

AgentHub

CommunicationManagement

• Connection control

• Routing• Events• Certificates• Authenticatio

n• Encryption

InfrastructureManagement

InformationModels

SoftwareProvisioning

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1 3

Edge Node

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Managing IoT Data - Information Models as a Key Enabler

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Each physical “thing” (device/subsystem) is formally described using WSDL/XML models as basis for software abstraction

The model defines the properties and capabilities of the (physical) system

Enables typical applications like

Configuration management

Performance/status monitoring

Fault management

Device Drivers

Services, Events, Properties

Information Model Implementation

Contract

Contract

WSDL, XSD

Java

Java

Defines the services, events, properties

and also communication

patterns

single device or subsystem




So this brings us to…



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Internet of Things

Machine-to-Machine

Monitored

Smart Systems (Intelligence in Subnets of

Things )

Telemetry and

Telematics

Smart HomesConnected Cars

Intelligent BuildingsIntelligent Transport

SystemsSmart Meters and Grids

Smart RetailingSmart Enterprise

Management

Remotely controlled and managed

Building automation

ManufacturingSecurityUtilities

Internet of Things

SensorsDevicesSystemsThings

ProcessesPeople

IndustriesProducts Services

Source: Machina Research 2014

IoT Data - Growth in connections generates big data



Data

Big data

Changing data models

Real-time Processing

Aggregation

Internet of Things

Large estates of devices

Evolving applications

All forms of data

Data streaming and processing

Pre-IoT (M2M)

Limited estate of devices

Single purpose applications

Structured / Semi-structured

Data transfers (sensors and

actuators)

Evolution from M2M to IoT and Big Data

Source: Machina Research 2014

A

D

C

B



• IoT apps generate multi-structured data

• Modeled more efficiently as JSON documents

• Exposed to powerful analytics

• Developers more productive

Modeling Complex Data

{ assetId: "NEXO 109", hour: ISODate("2014-07-03T22:00:00.000Z"), status: "Online", type: "Nutrunner", serialNo : "100-210-ABC", ip: "127.0.0.1", position: { 0: { 0: { x: "10", y:"40", zone: "itc-1", accuracy: "20” }, …, 59: { x: "15", y: "30", zone: "itc-1", accuracy: "25” } }, …, 59: { 0: { x: "22", y: "27", zone: "itc-1", accuracy: "22” }, …, 59: { x: "18", y: "23", zone: "itc-1", accuracy: "24” } } }}

A DCB



Use Case 2: Systematic Capturing of Field Data Project sFDE

Field Data Collection and Analysis

Components: Car brakes, power steering etc (via ECU)

Usage patterns: temperature, voltage, etc.

Predictive maintenance, product optimization

Synergies through standardized field data capturing

Continuous feedback from control units in the field

Reduce return ratesImprove quality

Why MongoDB: Constantly evolving system: data

capturing and data analytics point of view Large amount of streaming data Scalability, enterprise features References and Support

A

DC

B



Capabilities

Solutions

Key Capabilities of Bosch SI Suite & MongoDB

Bosch SI IoT SuiteM2M | BPM | BRM | Big Data

A DCBScale Flexibility Analytics Unified View

From Concept to Code

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Innovative Platforms and Solutions for the IoT

M2M

BRM

BPMBosch IoT Suite

EnergySmart Metering VPP (Virtual Power Plant)

ManufacturingService Portal

Mobility Fleet ManagementeMobility Solutions

Bosch Software Innovations: Systems and Software House for IoT Solutions

Smart HomeIntelligent Solutions

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Thank You

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