1. IoT and Big Data
Internet of Things and Big Data
Part I / III: Vision and Concrete Use Cases

2. IoT and Big Data
Joint Webinar Series:
Register to Reserve your Seat
Webinar 1: Vision & Use Cases
Webinar 2: Data Management Requirements for the IoT
Webinar 3: From Concept to Code

3. IoT and Big Data
Today’s Speakers
Dirk Slama, Director of Business Development
Bosch Software Innovations
20+ years of experience in large-scale distributed application
projects including M2M and IoT projects
Emil Berthelsen, Principal Analyst
Machina Research
Two decades of experience with management, strategic and research
consulting in business process management, telecoms and IT and more
recently focused on M2M, IoT and Big Data
Mat Keep, Product Management & Marketing
MongoDB
15 years working in high scale, data driven systems, working with
relational databases before moving into NoSQL and Big Data
platforms

4. IoT and Big Data
"Fixed" computing Mobility/BYOD Internet of things Internet of everything
Source: Cisco IBSG, 2013
(you go to the device) (the device goes with you) (age of devices) (people, process, data, things)
1995 2000 2013 2020
200M
10B
50B
Rapid growth of connected things

5. IoT and Big Data
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
$1
“

6. IoT and Big Data
Networked
heating systems
Networked
surveillance systems
Connected
vehicles
Smart sensor
platforms
Network
capability of
devices
Low power
consumption
Small form
factor
Energy
harvesting
capability
Wireless
technologies
Applications
Appropriate
cost
Enablers
IP is a key driver of innovation

7. IoT and Big Data
Bosch Group – Example Products

8. IoT and Big Data
THING IT
[HW | SW]
THING-BASED
FUNCTION
[Local | Business
models known]
IT-BASED
SERVICE
[Global | Business
models required]
IoT Formula for Success
Example SERVICE: Send ambulance
in case of accident (detected by sensors)
Example FUNCTION:
Drive from A to B
A B
Source: University of St. Gallen, Prof. Dr. Elgar Fleisch

9. IoT and Big Data
Key Drivers in the IoT Ecosystem
Enterprises
 Process efficiency
 End-to-end processes
 STP
 Real-time decisions
 Big Data
Partners
 Value chain optimization
 Real-time integration
 Flexible supply chains
 Mobile tracking &
monitoring
Users
 Mobile revolution
 Social & business networks
 Personalized services
 Location based services
Things
 Ubiquitous comms: GSM, WiFi,
BlueTooth, ZigBee, NFC, RFID
 HW: Cost , performance 
 Software: Embedded Linux,
embedded Java, …
 Smart devices, sensors,
actuators

10. IoT and Big Data
Vehicle
 Equipped with telematics unit
 Sensors to monitor moving parts,
hydraulics liquids, etc
Partners
 Service provider
 Repair specialist and vehicle
manufacturers
Vehicle Driver
 On-board diagnostics
 Information about other vehicles,
e.g. to unload harvest
Vehicle Operations
 Intelligent monitoring of machine
KPIs and fluid analysis
 Optimum servicing intervals
Example: Remote Condition Monitoring

11. IoT and Big Data
So this brings us to…

12. IoT and Big DataTensHundredsThousandsMillionsBillionsConnections
Internet of Things
Machine-to-Machine
Isolated
(autonomous, disconnected)
Monitored
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
Building
automation
Manufacturing
Security
Utilities
Internet of Things
Sensors
Devices
Systems
Things
Processes
People
Industries
Products
Services
Growth in connections generates
an unparalleled scale of data
Source: Machina Research 2014

13. IoT and Big Data
A new mindset and technology is
required for IoT
A changing approach to
databases in the Internet of
Things

14. IoT and Big Data
New requirements in enabling technologies
Devices
Connectivity
Platforms
Internet of
Things
Connected things,
products, services,
systems, etc.
Security
Networks
Apps &
Analytics
Databases
Source:
Machina Research 2014

15. 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)
Evolution from M2M to IoT and Big Data
Source: Machina Research 2014

16. IoT and Big Data
Data
Big data
Changing data
models
Real-time
processing
Aggregation
Databases will need to address new requirements
Scalability
Flexibility
Analytics
Unified View
Source: Machina Research 2014

17. IoT and Big Data
Scalability
Heterogeneity
Agility & Flexibility
in
Applications, Devices
and Connectivity
Scalability
Flexibility
Analytics
Unified View
in
Data
M2M & IoT Application
Platforms
Data Databases
SQL
(Oracle, IBM, etc.)
for structured data
Hybrid
(SAP Hana, VoltDB, etc.)
for speed and heterogeneity
NoSQL
(MongoDB, Cassandra, etc.)
for agility and heterogeneity
IoT-Platforms and Database-Systems
Source: Machina Research 2014

18. IoT and Big Data
IoT Foundation: Bosch Suite for IoT
A
D
C
B
Scale
Flexibility
Analytics
Unified View

19. IoT and Big Data
Example Applications

20. IoT and Big Data
Event Correlation

21. IoT and Big Data
Use Case 1: Retail & Logistics

22. IoT and Big Data
Use Case 2: Handheld Power Tools

23. IoT and Big Data
Use Case 3: Field Data Capturing
Project SCFD
 Structured Capturing of
Field Data
 Components: Car brakes,
power steering, etc.
 Usage patterns:
temperature, voltage, etc.
 Predictive maintenance,
product optimization
Why MongoDB:
Constantly evolving system,
from a data capturing and a
data analytics point of view
 Large amount of streaming
data
Asset
Management
Stream
Processing
Big Data
Management
Analytics
BRM BRM

24. IoT and Big Data
Capabilities
Solutions
Key Capabilities of MongoDB
Bosch SI IoT Suite
M2M | BPM | BRM | Big Data
A
D
C
B
Scale
Flexibility
Analytics
Unified View

25. IoT and Big Data
Register Now for Webinar 2
Key Data Management Capabilities
for IoT

26. IoT and Big Data
Any questions?