Blog post: http://blog.planetos.com/data-exchange-as-a-scenario-for-monetizing-automobile-sensor-data/ We are in the very early days of connected cars, going through what is called the “idea maze” in the entrepreneurial world. We’re talking of Apple and Google getting integrated with the car entertainment systems, we’re talking of user interfaces, and we’re talking about how many cars and which cars will be connected by 2020. In 2011, I led the global ABB team to win the world’s first nation-wide fast-charging infrastructure for electric cars in Estonia. Already then, I saw the opportunities that connected cars can bring to consumers and businesses. However, as with all new technology, the question is always — what is the initial point of entry, and what is going to be the structure of business as things proceed. Peter Thiel likes to ask “What is the next great company nobody is building?”. I think this is a very important question also in the connected cars space. From Planet OS perspective, where we work with sensor-heavy industries, we see that the emerging connected cars industry will have even a greater challenge of device fragmentation as weather forecasting, the mobile hardware manufacturers depending on Android, or oil & gas which is the most comprehensive user of sensory data. The good news is that the fast-paced consumer will go and buy the car that will work with their personal mobile device, and all automakers will have to adopt whatever will become the equivalent of “Works with Nest” strategy (think “works with Audi” vs “works with Apple”). There is no single right answer. My hope today is to help to spark thinking of the business use cases and execution of a different kind of automotive data which is not based on personal data rather than machine and sensor data. Why? Because sensor data is outgrowing social data volumes quickly, and by 2020 (see?), HP predicts 40% of all data ever created by human kind will be sensor data. At Planet OS, we have developed an industrial IoT platform for Real-World Sensor Networks in the Ocean, Land, Air and Space sensors. Planet OS has developed a powerful suite specifically focused on sensor data that combines data mining, integration, search & discovery and data exchange. Planet OS' capability to work with a wide variety of data types enables organizations to build advanced domain-specific applications without the fragmentation of data sources and data transformation. In a world Planet OS operates, there is a lot of geospatial data, along with a mature data marketplace, even if the exchange mechanism itself is not very sophisticated, nor user friendly. With the growth of connected cars there will be the growth of data. And this is, similarly to mobile, the driver to change how business is conducted. It will change how cars are sold and it will ch

1. Rainer Sternfeld, CE September 2014
Data Exchange as a Scenario for
Monetizing Automobile Sensor Data
January 29, 2015
ConnecteDriver 2015, Brussels
Rainer Sternfeld, CEO, Planet OS
@rsternfeld
@planet_os

2. 2 January 2015
ABB Baltic States 2006-2011
Business Development Manager, Baltics
(1,300 people, $300M revenue)
Business Development
• Fast-charging network for electric cars
(first nation-wide in the world)
• Regional + Local BU strategies
• New product rollout and ramp-up
• Production management software dev.
Corporate Development
• OneCampus production facilities
• SAP implemented in 3 countries
• 5S + COPQ implementation
• New operations, processes and policies
• Restructuring of operations
Statue of Liberty of Estonia (2007-2009)
ABB OneCampus (2009-2011)
eMobility Estonia (2011)
Data buoy for phytoplankton (2008-2011)
UGV+manipulator for DoD (2005-2006)
About the speaker | Rainer Sternfeld

3. 3 January 2015
Industrial IoT Platform for Real-World Sensor Networks
Consolidate dataflows, organize and make sense of your data
Access your data with 3rd party tools and systems
One interface to search and discover your local and remote data
Securely sell, exchange and acquire commercial or public datasets
Build advanced domain specific solutions without hassle

4. 4 November 2014
Data management
will not scale as we know it
Sensor data will outgrow
social data in 3 years
Sensor data is
too big to move
Swimming in sensors, drowning in data

5. 5 January 2015
Business anatomies of data exchange
1. SME data vendors sell to big buyers
2. Big buyers sell/exchange data between each other
3. One-off vs. streaming of data
4. Raw data vs. data products

6. 6 January 2015
Traditional Data Value Chain is Missing Data Exchange
SATELLITES
DRONES
CARS
BUOYS
OIL PLATFORMS
SHIPS
TRACTORS
LIGHTING
PHYSICAL
CHEMICAL
BIOLOGICAL
OPTICAL
NON-OPTICAL (RF)
TIME-SERIES
RASTER
ARRAYS
VECTORS
SEISMIC
VIDEO
ACOUSTIC
QA/QA
OUTLIER DETECTION
MODELING
DATA FUSION
DATA LOGISTICS
VISUALIZATION
ENHANCEMENT
DERIVATIVES
HARDWARE SENSORS RAW DATA
SOFTWARE
ANALYTICS
CUSTOMER
APPLICATIONS
ENERGY
WEATHER
AGRICULTURE
TRANSPORTATION
INSURANCE
TELECOMMS
LIGHTING
HEALTHCARE
DATA EXCHANGE LIVES HERE

7. 7 January 2015
Why Data Exchange?

8. 8 January 2015
Enterprise use cases: it’s not a one way street
1. Bi-directional real-time weather data (use cars as in-situ platforms)
2. Real-time on the road driving assistance (data aggregation models)
3. Insurance and driving statistics
4. Anomaly detection (drunk driving) and notifications
5. People per car / pedestrians / cyclists / motorbikes
ENVIRONMENTAL
& TRAFFIC SAFETY
GOVERNANCE,
INFRASTRUCTURE
& ENGINEERING
1. Reduce nation-wide annual road maintenance costs
2. Design better freeway systems and road quality
3. Improve GPS navigation/routing algorithms
4. Design and build better cars
5. Reduce lighting costs

9. 9 January 2015
Technology use cases: it’s all about streaming
1. Earn money without selling private data
2. Eliminate manual work from selling datasets
3. Improve data quality through immediate feedback
4. One Data Exchange for all incoming data (it’s a buyers market)
5. Lower barrier of entry to buying more data
6. Arbitrage
AUTOMATION

10. 10
Index the real world