MongoDB IoT CITY Tour EINDHOVEN: Bosch & Tech Mahindra: Industrial Internet, Industry 4.0, Smart Factory & Big Data

Industrial Internet, Industry 4.0, Smart
Factory & Big Data
TechMahindra, MongoDB and Bosch Software Innovations
© 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.

2
Circle of Concern today
This is where the story ends

Circle of Concern tomorrow
3
This is where the story starts

Industrie 4.0: The next Industrial Revolution
Industrie 1.0 Industrie 2.0 Industrie 3.0 Industrie 4.0
First
mechanical
loom
(1784)
4
End of
18th century
Complexity, Productivity
Start of
20th century
Start
of 1970s
Since
2010
First
production line,
Cincinnati
slaughterhouses
(1870)
First
programmable
logic controller (PLC),
Modicon 084
(1969)
Zeit
Cyber-physical
Systems (CPS)
Source: Forschungsunion, acatech, Abschlussbericht Arbeitskreis Industrie 4.0

Smart Factory
è New business models through the convergence of IT & production
5
Customer
Integrated
Engineering
Resilient
Factory
Networked
Production
Predictive
Maintenance
Technology
Marketplace
Adaptive
Logistics
Up-Cycling
Source: Forschungsunion Wirtschaft & Wissenschaft

Example: Indoor Asset Tracking
6
TechMahindra Track & Trace

7

Asset Details Page
8

Indoor-Localization using WiFi
9

Outlook: High Accuracy Indoor Localization
10
HAIP: High Accuracy Indoor Positioning

Outlook: Vertical Integration + HAIP
è Vertical Integration
l From Field Level
to ERP
l Automatic creation
of quality lots
l Full transparency
11
Example Architecture

Architecture Blueprint
Customer Manufacturer Operator
HTML5/Javascript (Bootstrap/AngularJS)
Identity Management
BPM
- Cisco Position
- Mail notification
Bosch Software Innovations Suite
Cisco
MSE
M2M
- Nutrunner drivers
- Smartcards
BRM
- Event evaluation
Third Party
Systems
Payment
Data
Bases
Mongo
Mongo
Bosch SI PaaS
TechM/AWS
ERP
NEXO Nutrunner Smart Id Card
12

Foundation: Bosch Software Innovations Suite
Business &
End User
User Interface
13
Common Environment
App Store
Design Tools
M2M UI Models
M2M Inform. Models
BPM Process Models
Design Time
Repository
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
• Modeling
• Optimization
• Administration
• Deployment
• Execution, Monitoring
• Modeling
• Simulation
• Implementation
• Execution
• Monitoring, Reporting
• Device Integration
• SW-Provisioning
• Central Registry
• Event Management

Details of Bosch Software Innovations Suite
M2M BPM BRM
Agent
-
Hub
Agent-
Hub
14
Device Management
(M2M)
Business Rules
Management
(BRM)
Business Process
Management
(BPM)
è Device Management
è Device Abstraction
è Event Management
è Software Provisioning
è Identity Management
è Define actions according
to certain events
è Recommendations for
actions
è Portal for user interaction
è Process modelling
è Process execution
è Integration layer with ESB
(e.g. SAP, …)
Agent
-
Hub
Central
Registr
y
BPM BRM

Connecting Physical Devices: Flexible Options
WiFi Bluetooth
Agent
Hub
Agent
Hub
Edge Controller
GSM LTE UMTS
DSL WAN Internet
GSM LTE UMTS
DSL WAN Internet
Edge Node
Communication
Management
• Connection
control
• Routing
• Events
• Certificates
• Authentication
• Encryption
M2M Back End
Local Network Global Network
1
2
ZigBee
NFC
Backend
Hub
GSM LTE UMTS
DSL WAN Internet
BACnet OPC
Edge Controller
Edge Node
Infrastructure
Management
–  : Depending on hardware performance, timing, reliability, communication
cost, different distributed system architectures are supported
Information
Models
Software
Provisioning
3
1 3
15

Managing IoT Data - Information Models as a Key Enabler
Services, Events, Properties
Information Model Implementation
16
è Each physical “thing” (device/
subsystem) is formally described
using WSDL/XML models as
basis for software abstraction
è The model defines the properties
and capabilities of the (physical)
system
è Enables typical applications like
l Configuration management
l Performance/status monitoring
l Fault management
Device Drivers
Contract
Contract
WSDL, XSD
Java
Java
Defines the services,
events, properties and
also communication
patterns
single device or
subsystem

Growth in connections generates an unparalleled scale of data
Tens Hundreds Thousands Millions Billions Connections
Internet of Things
Machine-to-Machine
Monitored
Building
automation
Manufacturing
Security
Utilities
Smart Systems
(Intelligence in Subnets of Things )
Telemetry
and
Telematics
Smart Homes
Connected Cars
Intelligent Buildings
Intelligent Transport
Systems
Smart Meters and Grids
Smart Retailing
Smart Enterprise
Management
Remotely controlled and
managed
Sensors
Devices
Systems
Things
Processes
People
Industries
Products
Services
Internet of Things
Source: Machina Research 2014

Evolution from M2M to IoT and 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)
Source: Machina Research 2014

IoT Data Management Requirements
Rich Applications Business Agility
Single View
Multiple Data Sources Continuous Innovation
Process Convergence
Operational
Insight
Real-Time
Enterprise-Ready
Secure & Reliable

• IoT apps generate multi-structured
data
• Modeled more efficiently
as JSON documents
• Exposed to powerful
analytics
• Developers more
productive
– Less time wrestling ORMs
– More time creating apps
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” }
}"
}
}"

From Concept to Code
Key Capabilities of Bosch SI Suite & MongoDB
Bosch SI IoT Suite
M2M | BPM | BRM | Big Data
A
Scale
B
Flexibility
C
Analytics
D
Unified View
Solutions
Capabilities
21

Vehicle Diagnostics
§ Commercial Vehicles are driven across the country for testing purposes. So there is a need for real
time information of vehicle parameters to understanding it’s performance against benchmarks
§ To monitor the health of the EV and provide insight to field support staff to determine the root cause
of the problem
Reports - Statistics of Vehicles
Customer Complaints, Alerts, Vehicle
Details – Around 32 reports for OEM
Vehicle Tracking Screen & CAN
Summary Screen
Solution Highlights
Business
Need
§ Capture proprietary information regarding the vehicle available from the CAN bus and provide the same to R & D teams
for further analysis
§ Provides Battery, Range, Charging Station Status to Owner & Remote Vehicle operations E.g Door lock / HVAC
§ Manage vehicle Reserve Charge
§ Provide vital EV health details (135 vehicle level alerts handled) enabling trouble shooting , Vehicle Event replays
§ Reports - Trip Analysis, Trip Details, Trip Summary, CAN Data Summary & CAN DM1 Message Summary
§ Analytics - Interpretation of various CAN messages (Proprietary, Diagnostic & Standard)
Business Benefits

Farm to Fork: Tracking and Condition Monitoring of Refrigerated Cargo
§ Transport of minimal shelf life products with varied temperature requirement
§ Managing cold chain is very complex
§ Adherence to SLAs around product freshness and delivery
§ Infrastructure constraints with longer lead times forcing tighter monitoring
Solution Highlights
Business
Need
§ Implement and support the consignment tracking system
§ Installation and maintenance of data aggregator units
§ Host application in cloud
Key Features:
§ Temperature tracking and monitoring
§ Vehicle location and milestone tracking, Analytics and dashboard
§ Fleet and driver management , Alerts and event management
Business Benefits
Adhere to quality norms and improving
customer satisfaction
Improved visibility and tracking thus
reduce spoilage

Remote Patient Monitoring
Cardiac patients in need of continuous medical supervision, observation and care by qualified
medical professionals require their heart rates and Challenge rhythms to be monitored
Benefits
Cost Savings for the patient, provider and
payer
Reduced medical emergencies and
hospital re-admissions
Solution Highlights
The patient’s ECG data is remotely accessed through cellular network by cloud hosted Remote Patient
Monitoring solution and is analysed round-the-clock by a team of qualified and experienced clinicians,
cardiac technicians and medical personnel. Monitoring , feedback and emergency alerts are sent within the
specified time protocols to the designated parties

E2E Presence along the IoT Value Chain

Thank You
26

Continuous Integration
New
Column
ID PSI Temp Loc
3 months later…
• Dynamic database schema
• No need to define upfront
• Enables agile methodologies
– Evolves as the application changes
– Eliminates teams co-ordinating ALTER
TABLE operations

Business Process Convergence
New
Table
New
Table
New
Column
• Aggregate data from multiple
source systems
• Define single schema,
update whenever the source
systems change…or JOIN
hundreds of tables!
• Document model & dynamic
schema makes single view a
reality
– Real time sensor data blended
with enterprise data

Powerful Analytics on Live Data

Scalable, Reliable, Secure
Automatic Sharing & Replica Sets
Defense in Depth

MongoDB IoT CITY Tour EINDHOVEN: Bosch & Tech Mahindra: Industrial Internet, Industry 4.0, Smart Factory & Big Data

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MongoDB IoT CITY Tour EINDHOVEN: Bosch & Tech Mahindra: Industrial Internet, Industry 4.0, Smart Factory & Big Data