How does google maps work

Google also takes traffic reports from transportation departments, road sensors, and private data providers to keep its information up to date. Amanda Leicht Moore, the Group Product Manager for Google Maps, told Tech Insider that the historical data allows it to inform Google Maps users if traffic on their route is better or worse than it typically is, and how much they will be slowed down by accidents of slowdowns.

But the accuracy of location data is unmatched only because of its users, since the billion Google Maps users on the road act as sensors for the app, which make the service as precise as possible.

For the latest videos on gadgets and tech, subscribe to our YouTube channel. Best Deals of the Day ». Tech News in Hindi. More Technology News in Hindi. Latest Videos. It seems like a ridiculous notion that we would need a complete representation of the world when we already have the world itself.

But to take scholar Nathan Jurgenson's conception of augmented reality seriously, we would have to believe that every physical space is, in his words, "interpenetrated" with information. All physical spaces already are also informational spaces. We humans all hold a Borgesian map in our heads of the places we know and we use it to navigate and compute physical space. Google's strategy is to bring all our mental maps together and process them into accessible, useful forms.

Their MapMaker product makes that ambition clear. Project managed by Gupta during his time in India, it's the "bottom up" version of Ground Truth. It's a publicly accessible way to edit Google Maps by adding landmarks and data about your piece of the world.

It's a way of sucking data out of human brains and onto the Internet. And it's a lot like Google's open competitor, Open Street Map , which has proven that it, too, can harness the crowd's intelligence. As we slip and slide into a world where our augmented reality is increasingly visible to us off and online, Google's geographic data may become its most valuable asset.

Not solely because of this data alone, but because location data makes everything else Google does and knows more valuable. Or as my friend and sci-fi novelist Robin Sloan put it to me, "I maintain that this is Google's core asset.

In 50 years, Google will be the self-driving car company powered by this deep map of the world and, oh, P. Skip to content Site Navigation The Atlantic. Popular Latest. The Atlantic Crossword. Sign In Subscribe. And that's just from comparing the map to the satellite imagery.

But there are also a variety of other tools at Google's disposal. One is bringing in data from other sources, say the US Geological Survey. But Google's Ground Truthers can also bring another exclusive asset to bear on the maps problem: the Street View cars' tracks and imagery. In keeping with Google's more-data-is-better-data mantra, the maps team, largely driven by Street View, is publishing more imagery data every two weeks than Google possessed total in Let's step back a tiny bit to recall with wonderment the idea that a single company decided to drive cars with custom cameras over every road they could access.

Google is up to five million miles driven now. Each drive generates two kinds of really useful data for mapping. One is the actual tracks the cars have taken; these are proof-positive that certain routes can be taken.

The other are all the photos. And what's significant about the photographs in Street View is that Google can run algorithms that extract the traffic signs and can even paste them onto the deep map within their Atlas tool.

So, for a particularly complicated intersection like this one in downtown San Francisco, that could look like this:. Google Street View wasn't built to create maps like this, but the geo team quickly realized that computer vision could get them incredible data for ground truthing their maps. Not to detour too much, but what you see above is just the beginning of how Google is going to use Street View imagery.

Think of them as the early web crawlers remember those? That's what Street View is doing. One of its first uses is finding street signs and addresses so that Google's maps can better understand the logic of human transportation systems. But as computer vision and OCR improve, any word that is visible from a road will become a part of Google's index of the physical world.

And that's how you get your maps to look this this: Some details are worth pointing out. In the top at the center, trails have been mapped out and coded as places for walking. All the parking lots have been mapped out. All the little roads, say, to the left of the small dirt patch on the right, have also been coded.

User contributions provide additional details to businesses like reviews, photos, and opening and closing times. Google data shows that users submit more than 20 million contributions each day. User-generated error reports are also integral for finding out errors that cannot be identified without human assistance. Custom setups like underwater cameras are used for special circumstances.

For their first underwater expedition, Google captured the Great Barrier Reef. Data from street view vehicles are also used to verify and correct the existing data from other sources. Street signs captured here, and processed through technologies like OCR, can even be used to correct business listings with accurate addresses.

Recommended blog - What are Top 10 Breakthrough Technologies? It has been estimated that there are more than Street View cars currently on the streets around the world. Google focuses mostly on the US, then Europe, and then other popular tourist destinations for its mapping tours.

That means that developing countries have sparse street view coverage, most of that provided by users. A Map with blue areas showing where Street View is available. Source: Google. If you use Google Maps and keep on the location services on your phone, whether you know it or not, you're contributing your data to Google Maps.

Back in the day, Google used data from traffic cams and such to estimate traffic conditions, but now a much more effective system is in place. Google receives the location and speed of movement of every smartphone that uses Google Maps, and data is collected from a number of such phones on the road. This real-time data, combined with historical data about the usual traffic at a place, can be used to predict the traffic density of a place with fairly good accuracy.

This is how you get your real-time traffic updates. This user data is also used to determine the times of day when businesses are most crowded. Satellites, Street View vehicles, and user contributions bring in a massive amount of data, which can be automatically processed and incorporated into Google Maps, to an extent. Processing images with AI are important to maintaining such a large collection of data.

Machine Learning models are used to automate the map-making process- refining building outlines in satellite images, reading street signs from Street View data, and so on. The algorithms required to keep the machinery running are top-secret, but they organize the data, look for errors, and combine data from different sources to form a comprehensive picture. Recommended blog - What is an Algorithm? Types, Applications, and Characteristics. But there is only so much that can be automated.

Human employees at Google review error reports submitted by users, verify content and make the necessary adjustments. Google Maps seems committed to a vision of mapping out the entirety of the earth. If you look at the numbers, they're mind-boggling.

And Google Street View vehicles have captured 10 million miles of imagery. To put it into perspective, 10 million miles is more than the distance covered if you were to circle the Earth times. Google Maps is making great strides. A map covering percent of the world, and also lets you see every detail of it in all its three-dimensional glory, is set to soon be a reality. Be a part of our Instagram community.