Untaped Data from the Sky: Skybox Imaging

Skybox Imaging wants to provide real-time satellite images form earth and data analytics to build a Google-scale business.

Big Data companies scour the Internet and transaction records and other online sources to glean insight into consumer behavior and economic production around the world, an almost entirely untapped source of data—information that companies and governments sometimes try to keep secret—is hanging in the air right above us.

There are 1,000 satellites orbiting the planet at any given time, But only 12 send back hi-res images.

Bildschirmfoto 2013-04-05 um 10.28.12

Of the 1,000 or more satellites orbiting the planet at any given time, there are perhaps 100 that send back visual data. Only 12 of those send back high-resolution pictures (defined as an image in which each pixel represents a square meter or less of ground), and only nine of the 12 sell into the commercial space-based imaging market, currently estimated at $2.3 billion a year.

Even with six small satellites orbiting Earth, Skybox could provide practically real-time images of the same spot twice a day at a fraction of the current cost.

Plenty of people would want real-time access to that data—investors, environmentalists, activists, journalists—and no one currently has it, with the exception of certain nodes of the US government.

Skybox wants to go further than just providing real-time images. The company’s real payoff won’t be in the images Skybox sells. Instead, it will derive from the massive trove of unsold images that flow through its system every day—images that, when analyzed by computer vision or by low-paid humans, can be transmogrified into extremely useful, desirable, and valuable data. What kinds of data?

  • The number of cars in the parking lot of every Walmart in America.
  • The number of fuel tankers on the roads of the three fastest-growing economic zones in China.
  • The size of the slag heaps outside the largest gold mines in southern Africa.
  • The rate at which the wattage along key stretches of the Ganges River is growing brighter.

Continue reading:

http://www.wired.com/wiredscience/2013/06/startup-skybox/

Skybox Imaging:

Skybox

SkySat-1 in final testing at Skybox’s HQ

Skybox Imaging is an information and analytics company that provides easy access to reliable and frequent high-resolution imagery and first-ever HD video of the earth by combining the power of web technologies and a constellation of microsatellites. By operating the world’s first coordinated high-resolution imaging constellation, Skybox aims to empower commercial and government customers to make more informed, data-driven decisions that will improve the profitability of companies and the welfare of societies around the world.

Through a planned constellation of 24+ satellites that will capture high-resolution imagery and the first ever HD-video of any spot on earth, multiple times per day, Skybox will be able to take the pulse of the planet on a near real-time basis to provide an indispensable tool in addressing global challenges in areas including security, humanitarian efforts, and environmental monitoring.

 

Stanford Technology Venture Program

featuring Co-Founders of Skybox Imaging:

Dan Berkenstock (EVP and Chief Product Officer | Founder)

Julian Mann (Vice President, Product Development | Founder)

John Fenwick (Vice President, Flight Programs | Founder)

Ching-Yu Hu (Director of Marketing and Customer Relations | Founder)

http://www.skyboximaging.com/

Mercedes-Benz needs Big Data solutions to be ahead in connected car technologies

Mercedes-Benz, Bosch and HDI have partnered up with European accelerator network Startupbootcamp to access ideas in the fields of connectivity, mobility and big data.

As part of this partnership, called SBC2go, the partners will provide financial resources, mentors and marketing support to startups selected to participate in the programme.

Dr. Frank Spennemann from Daimler lab and Mercedes-Benz says partnering with Startupbootcamp Berlin will “accelerate our access to innovation and will plug us into an impressive community of alumni, mentors and investors. At the same time we support start-ups in developing business ideas and increase their market value. Due to our global presence we can open doors to new markets.”

So, what is Mercedes-Benz, Bosh and HDI looking for?

E.g. Daimler has a number of initiatives already such as the Car2Go car-sharing service which has over 7,000 vehicles in 18 cities on the road in Europe and North America

They need basic, advanced and realtime data anlytics. How basic traffic data analytics can look like, can already be seen at uber.com

uber - networks, showing probabilities

Here are San Francisco’s location networks, showing the probability that a ride starts in one neighborhood and ends in another.

Having this kind of analytics in realtime, car sharing service car2go could offer e.g. dynamic pricing. This would mean an competitve advantge to DriveNow (BMW), flinkster (Deutsche Bahn) and ZebraMobil.

It is great to see that Mercedes-Benz, Bosch and HDI are supporting the Berlin start-up ecosystem. The output of this partnership will be definitely interesting.

Links:

http://www.startupbootcamp.org/blog/the-big-league-startupbootcamp-berlin-partners-up-with-mercedes-benz-hdi-and-bosch-for-sbc2go.html

http://techcrunch.com/2013/04/16/mercedes-benz-bosch-and-hdi-create-new-accelerator-with-startupbootcamp-berlin/

http://blog.uber.com/2012/01/09/uberdata-san-franciscomics/

 

Tim O’Reilly on Humans, Machines and Data at Stanford

Tim O’Reilly uses examples from Google’s autonomous Vehicle project to highlight the developing changes and interactions in the relationship between humans, machines and data (human-machine symbiosis).

How can it be that during the DARPA Grand Challenge an autonomous car drove 7 miles in 7 hours and 6 years later Google autonomous Vehicle drove 100 000 miles?

Peter Norvig, Chief Scientist, of Google has an explanation: “We don’t have better algorithms. We just have more data.”
The data was the Google street-view vehicle. The data came from humans who drove with the Google street-view cars the roads, equipped with detailed sensors which measured, photographed and collected all the data. The data was stored in the cloud and made available to the Google autonomous Vehicle. This is an example for rethinking human-machine symbiosis.

All this data makes the Google autonomous Vehicle project just possible. It is a fairly hard AI problem to pic a traffic light out of a video stream. It is a trivial AI problem to figure out if it is red or green if you already know it is there.

Read more: e-corner Stanford University’s Entrepreneurship Corner
Stanford Technology Ventures Program (March 6, 2013)

 

Creative Data Agency from Germany