Updating the cadence to an ~hourly image would require ~2000 satellites, and updating it to every minute would require another 1.5 orders of magnitude... approximately 50,000 satellites.
The downlink capabilities to pull that data off the satellites would be colossally huge. A tremendous number of groundstations with a huge array of antennae constantly coordinating and pulling data down.
I'm sure Planet is heading in that direction, but it's actually hard to imagine the commercial value of such a mind-blowingly massive infrastructure investment.
In contrast to some of the other commenters, I do _not_ think that the NRO or any other collection of government organizations has a planetary image datastream anywhere close to this. The number of satellites and quantity of data required is really mind blowingly immense. I think that the downlink stations would be impossible to conceal, so if we had such a capability, we'd know about it.
It's also not necessary for their work - they typically task a satellite with watching an area of interest if they need to. They don't need 24/7 planet-wide monitoring.
In the limit where you're talking about a satellite "instantaneously local" to every location on the planet, that becomes just one ground antenna per satellite to handle whichever one is nearest. Yeah, 50k stations are expensive, but not nearly as much as the satellites they are talking to.
Or replace "cellular tower" with long-range wifi
https://en.wikipedia.org/wiki/Long-range_Wi-Fi#Notable_links
My point stands that there exists a possible path to get TB to PB of data down to earth through existing handsets. A collection of handsets could form a phased array receiver, everything is basically SDR anyways.
Because the satellites are small and relatively low power, the ground stations used to communicate with a high speed link probably use a 3-5 meter dish. So each groundstation site needs either a large array of rapid-slew tracking antennas or a big ol' phased array with some seriously hardcore software on board. A bank of ~20-30 3-5 meter antennae capable of slew and pitch to track a LEO target is a pretty serious investment. Each tracking antenna probably costs more than 100k... they'll have to have chilled antennae for low noise, and some heavy duty mechanisms to move them around. so 3200 sites * 30 dishes per site * 100k per dish is about 10 billion dollars - not including the cost of land or humans.
A phased array capable of directing a tight beam to 30 individual targets simultaneously all with different movement parameters is a many 10's of million dollar piece of equipment, and will only inflate the above number.
If one builds 50,000 satellites similar to what Planet has already built, the cost comes down into the single digit thousands of dollars per unit. Call it 10k. At that point, launch costs dominate the economics. Each sat has a mass of (say) 5 KG. The falcon heavy can launch 50,000 kg, but for cubesats some significant fraction of the mass will be in the deployment mechanism, so call it 7500 satellites per launch. That's 7 launches, at ~100 million each, so call it a round billion dollars to build and launch the satellites.
My googling shows 148.94 trillion square meters, with 18.6 trillion
We'll being generous to say "good enough to spot a car" is 2 pixels with 1 meter pixel size.
To be moderately confident it's a car, I'd guesstimate we'd need quite a bit higher resolution.
With no compression and RGB 24 bit encoding, that's 3 bytes/pixel, or 446 TB of data per "frame" of our realtime recording. Of course that could be compressed down a TON, but regardless it's a staggeringly large quantity of data to work with.
> some machine learning it should be possible to skip most of oceans forests and deserts (unless some unusual object appears in that area).
As far as I can think through, you'd need to process the data in the oceans, forests, and deserts if you want to find unusual objects. We can't do a shortcut and say only 1/8 of the world is inhabited/developed in some way and that's all we're going to monitor. Perhaps you take 1/4 or 1/8 of the data from the vast amounts of uninteresting data and look for larger anomalies.
No matter how you look at it, there'd be a ridiculous amount of data and processing required to do object detection on that scale.
I've recently been doing some world simulation for games, and found that you quickly start pushing RAM limits if you want to represent an Earth-sized planet at square kilometer precision. Turns out the Earth is pretty big. Mars is more reasonable, with about a quarter of the surface area.
With compression I don't think the storage per se would be a problem for the IC.
And if you're looking for that particular missing airplane, you could just look at the timestamped photo and see it there.
I don’t know if that was really true even back then, but today it’s completely doable and done all the time (think Google Chat or Facebook Chat).
My point is, times change, it’s entirely possible that in 20 years storing that much data will be completely possible.
In 20 years, we might have relatively faster links, but the improvement rate of those is much, much slower than storage density.
[1] https://www.wired.com/story/how-to-build-a-space-communicati...
[2] https://www.theverge.com/2013/2/1/3940898/darpa-gigapixel-dr...
There is research going on right now to build native camera systems that emit data (at the hardware level) that is not dense but rather sparse; information is transmitted as "blocks of pixels that changed between frame two and three" rather than "here is the state of all pixels at frame two, and here is the state of all pixels at frame three". In essence, doing a small amount of delta compression within the hardware itself.
This seems like a really natural fit for an application such as this one; and could potentially cut the amount of data needed to be paid attention to down by orders of magnitude.
Many of these ideas are similar to what is used to compress video down in the first place; it would be interesting to see a combination of video compression technology and "region of interest" ML pruning, where the ML models are applied only to interesting regions, as identified by the compression codec. The codec already has done the analysis to figure out which portions of the video have changed, which portions of the video are simply shifted versions of information from the last frame, etc.... You could significantly speed up ML analysis by making use of that kind of information.
This is already what hardware video codecs do well. If you’re talking about Chronocam-style differential sensors, they have their specialized use cases, but this is not one of them. Bandwidth from your sensor to your codec is already obscenely high, and you’re on a moving platform anyway.
As far as what video to actually store or do further processing on, ML ROI absolutely makes sense. This is basically what the Google Edge TPU is for: https://cloud.google.com/edge-tpu/
A huge advantage of them is that you have practically instant latency on the output, as opposed to restricted frame rates with motion blur from traditional cameras. Have a look at [1] for a few demos. The spinning bucket path reconstruction and drone visual odometry are my favourites.
[0] http://rpg.ifi.uzh.ch/research_dvs.html [1] https://www.youtube.com/watch?v=F3OFzsaPtvI
If US gov doesn't do it, China will.
[1] https://blogs.crikey.com.au/planetalking/2014/03/25/mh370-la...
I'm not trolling and I don't know the answer to that last one. But I'm assuming the general consensus is that it wouldn't change anything - a plane would be down and everyone would still be dead. So instead of mandating an expensive overhaul of everything that can feed more data constantly I assume they're probably trying to make some already in place tech fill the gap and it has limits. I am entirely speculating on that though. But when in doubt, something usually comes down to a cost-benefit analysis.
Also the money spent is nothing in the grand scale of aviation.
When you know the exact crash site, you can send help more accurate and therefore faster to save people, as airplanes can sometimes make a emergency water landing...
And in general I don't quite get it. GPS exists, so does Sattelite communication. And sure, for one private person it is quite expensive, but for an Airliner??
But in those events the planes have transponders/beacons that will tell you where they are. Remember with MH370 the pilot disabled it and then, to the best our knowledge, pointed the plane at the water.
A solution that can continue sending updates from any point on earth costs a lot more than one that only works in range of cellphone networks.
>New aircraft must broadcast their locations every minute when they’re in trouble, but only from January 2021. A gradual tightening of requirements starts in November, when airlines must track planes every 15 minutes under regulations adopted by the United Nations’ International Civil Aviation Organization.
The in distress technology isn't locked down yet but one option is increasing the capabilities of the existing distress beacons standards http://insidegnss.com/the-cospas-sarsat-meosar-system/
In reality tracking commercial airliners in real time is less useful for improving safety than better black boxes that collect more data.
"Under the rules taking effect in 2021, a plane would switch to one-minute tracking automatically when systems detected it was in distress because of turbulence, mechanical difficulties or an unexplained change in course, such as during a hijacking or if the crew became unconscious.
Pilots couldn’t turn the system off after it activates automatically, ICAO said. The system would deactivate itself once the plane was flying safely again.
However, a pilot could turn off the system if it was manually activated.
The challenges tied to minute-by-minute tracking include adding computing power and internet bandwidth to process larger volumes of data. The tighter system also may require reserving more space on the flurry of satellites being launched to satisfy demands for constant internet connectivity."
https://en.wikipedia.org/wiki/National_Reconnaissance_Office
1) Clouds
2) You can't see all latitudes from geo, the higher the latitude gets, the more marginal the images will be.
So I really doubt such a capability exists. Look a the FOV for a geo satellite like GOES-15: http://www.wmo-sat.info/oscar/satellites/view/151
No there's no way this is happening right now. I'm confident that they can continuously observe specific arbitrary locations of interest, but not the entire planet all at the same time. That's crazy talk.
The scale of infrastructure needed for something like that would be staggering.
Important question is, for what purpose?
Assuming it's the aviation safety domain we're talking about, I think improving aircraft connectivity to ground stations and enhancing real-time monitoring [0] would be a superior solution than to invest in array of video-recording infrastructure to keep tabs on the planet--this without even factoring in the privacy concerns that may arise out of continual recording and access to the said data.
[0] https://www.wsj.com/articles/how-to-avoid-another-malaysia-f...
1) the tech already exists (wouldn’t even require new satellites)
2) the costs involved are actually not very high
3) would help negate the security and reliability weaknesses of ADS-B.
Background on the system for tracking: https://aireon.com/
They could never get funding to use Ukrainian Dnepr rockets even if they were cheaper than SpaceX. The Ukrainians rockets payload capacity is far smaller than a Falcon 9, quality is questionable, and clearly would never have been able to hit the cadence Iridium needed (only 9 launches this decade, barely more than one per year).
Then SpaceX came along. No-one thought the Falcon 9 would be a success, because it was so ambitious compared to the Falcon 1. Then no-one thought SpaceX could be competitive on pricing, and SpaceX blew everyone away on pricing way before they even started re-using their rockets (because Musk and his team were smart enough to design the Falcon 9 to be the first rocket that could be mass assembled. He's not Tesla or Edison, in reality he's Henry Ford). SpaceX's success proving the Falcon 9 was a big reason iridium got the massive funding they needed for the new satellites.
Elon Musk has hardly anything to do with Iridium NEXT. SpaceX launched the satellites, but that's it. If it wasn't SpaceX, it would've been any other launch provider (just like how China, Russia, and McDonnell Douglas provided 23 Iridium launches, compared to SpaceX's 8 Iridium NEXT launches).
You really should be saying "Thanks to Bary Bertiger, Raymond J. Leopold and Ken Peterson", who were the three engineers who actually came up with, designed, and developed the entire Iridium constellation, as well as Motorola, the company that financed Iridium, Lockheed/Orbital ATK/Thales, the companies that built the satellites, and of course Iridium Communications, the company that actually runs it.
Give credit where credit is due. And it's not due to Musk.
Then they suddenly got new funding and started launching satellites again in 2017. Right at the same time Falcon 9s dramatically cut commercial launch costs by well over half compared to other launch providers.
So Elon deserves some credit here, just as Bary, Raymond and Ken do.
Suddenly SpaceX cuts launch costs by 4x and Iridium is able to get funded and launch again. Trying to claim coincidence is misleading.