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
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
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
Kannst du die Abbildung neu erstellen und Cisco als Quelle nennen?
Drucksensor BMP085 von Bosch Sensortec setzt Maßstäbe bei Packungsdichte, Ruhestrom und Auflösung
Der neue digitale MEMS Drucksensor BMP085 von Bosch Sensortec (5 x 5 x 1,2 Millimeter) unterstützt unter anderem den Trend, Navigationsfunktionen in Mobiltelefone zu integrieren. Mit seiner sehr feinen Höhenauflösung von bis zu 25 Zentimetern ermöglicht er eine sinnvolle Unterstützung bei einem fehlenden GPS Signal. Über die ROHS-Konformität hinaus ist der Sensor auch frei von Halogenen.
UNIMAT Heating Boiler UT-M
The UT-M boiler series, as flame-tube smoke-tube boilers, built in accordance with the Pressure Vessels Directive, is used to produce high-pressure hot water cheaply in the mid-temperature range up to 190°C.
http://www.bosch.com/en/com/innovation/insidebosch/powertrains_of_tomorrow/challenges_posed_by_the_electric_powertrain/challenges_posed_by_the_electric_powertrain.html
Challenges posed by the electric powertrain
Powerful batteries, the latest power electronics: the electric drive presents engineers with many new challenges.
Within the Internet of Things, many if not all objects of our daily life will become „smart“. What does this mean?
According to Prof. Elgar Fleisch from University of St. Gallen, „Smart Things“ are defined by the combination of „Things“ with IT Hardware and Software. This allows for two kinds of functions: first the original „primary“, „thing-based“ functions. Those are usually local functions, with known business models. A car drives you from A to B, a phone lets you make phone calls, a watch gives you the time, your glasses allow you to see.
New is the second area: by adding IT based services via the IoT, many new additional „secondary“ functions become possible. They are in many cases not limited to the local physical device, and come often in combination with new business models.
Examples: a car in an emergency may call the red cross service. Its sensor data may be used to warn other cars behind you about foggy or icy road stretchs. Floating position data from cars and phones may be used to get information about traffic congestions. Your watch will allow for remote monitoring of your health and give you an early warning before a stroke. And so on.
Those are just a few example of new functions, that become possible with the Internet of Things – new chances to make lifes better, and certainly also significant new business opportunities for companies to create new customer offerings based on the combination of smart things and web-based services.
MongoDB provides agility, scalability, and performance without sacrificing the functionality of relational databases, like full index support and rich queriesIndexes: secondary, compound, text search, geospatial, and more