Satellite Surveillance Takes the Pulse of America’s Health
Can surveillance pix taken by using satellites 22,000 miles above grant deep insights into the humans who stay in our planet’s city areas?
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| Satellite Surveillance Takes |
And the lookup crew at the back of the find out about relied on a stunning technological know-how to attain its conclusions: Artificial intelligence. Satellite Surveillance Takes the Pulse of America’s Health.
Rather than manually poring over 150,000 high-resolution satellite tv for pc pix to categorize environmental features, the crew fed the statistics into a neural community and used AI to extract the insights.
Elaine Nessie,2 one of the study’s authors and a researcher at a college in Boston, spoke to us about how her crew carried out the study, and what AI ought to suggest for the future of public health.
What used to be your speculation going into the study?
Quite a few research have regarded at exclusive factors of our surroundings and how that correlates with bodily activity, weight problems prevalence, and different fitness outcomes.
Previous research have seemed at matters like avenue structures, highways, greenery, areas between houses, and so on.
We had been looking forward to we would see some associations between the constructed surroundings and weight problems prevalence.
We simply weren’t certain how excessive these associations would be.
What position did synthetic brain play in the research?
In this study, we should have long past out and bodily counted the entirety in all the one of a kind communities that we have been involved in studying.
That would take a while… however if we may want to have AI do that work for us, it would ease the quantity of guide work we had to do.
Yes and no. The AI appears at every photo and assigns chances to what it sees.
The AI represents the entirety in every picture – whether or not it’s bushes or a residence or some thing else – as a number.
It then combines all these numbers to use as a illustration of that unique image, and then it combines pix throughout a unique regional to create a numerical photograph of the environment.
We regarded at cities that had high-obesity occurrence and cities that had low-obesity occurrence and located that nearby traits like parks and crosswalks have massive correlation with decrease weight problems levels.
We located some shocking correlations, too, such as that areas close to police stations are correlated with greater weight problems levels.
But overall, our correlations line up with weight problems estimates posted by using the CDC. Have you performed any different research alongside these lines?
Yes. Most of my activity is searching at new science and how we can use that in public fitness research. Another learn about that we did truly stimulated this one in a way. A couple of years in the past we appeared at high-resolution satellite tv for pc photographs of health facility parking a lot in three Latin American countries.
The thought used to be that we may be capable to correlate the parking lot records with the incidence of influenza-like ailments in these countries, theorizing that greater parked motors would imply greater degrees of illness.
Since they don’t frequently have get right of entry to to statistical data, we located we may want to correlate that photograph facts with the incidence of illness. But for that, we had to manually depend all the cars.
How are you working with AI now?
We have a few ongoing studies. We have a comparable learn about to our weight problems lookup connecting environmental facets with crime. Going forward, how quintessential will AI be in this form of research?
The primary intention of this find out about was once to see how we should use AI to analyze public fitness issues: Specifically, can we use these strategies to enhance how we accumulate information and how we method data?
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Previous research have seemed at matters like avenue structures, highways, greenery, areas between houses, and so on.
We had been looking forward to we would see some associations between the constructed surroundings and weight problems prevalence.
We simply weren’t certain how excessive these associations would be.
What position did synthetic brain play in the research?
That would take a while… however if we may want to have AI do that work for us, it would ease the quantity of guide work we had to do.
It took about 24 hours for the neural community to go via all the images. The quantity of time it would take for any one to go via these pics manually ought to be up to a month.So is the AI simply labeling all these elements for you, doing the grunt work?
Yes and no. The AI appears at every photo and assigns chances to what it sees.
The AI represents the entirety in every picture – whether or not it’s bushes or a residence or some thing else – as a number.
It then combines all these numbers to use as a illustration of that unique image, and then it combines pix throughout a unique regional to create a numerical photograph of the environment.
We regarded at cities that had high-obesity occurrence and cities that had low-obesity occurrence and located that nearby traits like parks and crosswalks have massive correlation with decrease weight problems levels.
We located some shocking correlations, too, such as that areas close to police stations are correlated with greater weight problems levels.
But overall, our correlations line up with weight problems estimates posted by using the CDC. Have you performed any different research alongside these lines?
Yes. Most of my activity is searching at new science and how we can use that in public fitness research. Another learn about that we did truly stimulated this one in a way. A couple of years in the past we appeared at high-resolution satellite tv for pc photographs of health facility parking a lot in three Latin American countries.
The thought used to be that we may be capable to correlate the parking lot records with the incidence of influenza-like ailments in these countries, theorizing that greater parked motors would imply greater degrees of illness.
Since they don’t frequently have get right of entry to to statistical data, we located we may want to correlate that photograph facts with the incidence of illness. But for that, we had to manually depend all the cars.
How are you working with AI now?
We have a few ongoing studies. We have a comparable learn about to our weight problems lookup connecting environmental facets with crime. Going forward, how quintessential will AI be in this form of research?
The primary intention of this find out about was once to see how we should use AI to analyze public fitness issues: Specifically, can we use these strategies to enhance how we accumulate information and how we method data?
These kinds of research can virtually advantage public health, and these strategies can be one way of auditing distinct elements of our environment.Read More on the Data Powering Surveillance Systems:
Deep Learning in Surveillance
How Smart Video Surveillance is Changing Edge Architectures
Durability and Surveillance in Edge Units
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