DigitalGlobe Powers Crowdsourced Hunt For Missing Malaysian Flight 370
Every now and then we need a reminder that technology is more than games and gadgets, and this is one of those times: To help in the bizarre and tragic case of the Malaysia Flight 370 jet that has mysteriously vanished without a trace, a company called DigitalGlobe is using satellite images and crowdsourcing to help in the search.
DigitalGlobe says it owns the world’s most advanced commercial imaging satellites, and it also has a crowdsourcing platform called Tomnod that allows users to comb through satellite images to aid “Response and recovery efforts for numerous natural and man-made disasters”.
DigitalGlobe Tomnod
DigitalGlobe used its satellites to capture some 3,200 square km of the area where the flight could have gone down--since then the area has updated to 24,000 square km--and it asked the community to help look through all of it to identify and flag anything of note.
It took just a couple of days for 2 million or so volunteers to tag 645,000 items. The way the systems works is that it shows the same images to many different people, and if enough people tag the same little square on the grid, an expert will review that area to see if the item of interest is worth investigating.
That makes the process rather efficient; essentially, the tedious legwork is done by what amounts to throngs of worker bees, thus freeing up the time and resources of the experts to do more sophisticated work.
DigitalGlobe says it owns the world’s most advanced commercial imaging satellites, and it also has a crowdsourcing platform called Tomnod that allows users to comb through satellite images to aid “Response and recovery efforts for numerous natural and man-made disasters”.
DigitalGlobe Tomnod
DigitalGlobe used its satellites to capture some 3,200 square km of the area where the flight could have gone down--since then the area has updated to 24,000 square km--and it asked the community to help look through all of it to identify and flag anything of note.
It took just a couple of days for 2 million or so volunteers to tag 645,000 items. The way the systems works is that it shows the same images to many different people, and if enough people tag the same little square on the grid, an expert will review that area to see if the item of interest is worth investigating.
That makes the process rather efficient; essentially, the tedious legwork is done by what amounts to throngs of worker bees, thus freeing up the time and resources of the experts to do more sophisticated work.
