How You May Be Helping Google Map Indoor Spaces

A couple of years ago, Google acquired the startup Behavio. One of the selling points behind Behavio was how it used behavior data from Phones to better understand human behavior. It’s likely that Google acquired the company Zipdash back in 2004 to learn about real-time traffic data.

Compass Study,  Calsidyrose, Some rights reserved
Compass Study,
Calsidyrose, Some rights reserved

A Google patent application published in the last week describes how Google might be using Mobile data from phones to map indoor spaces, combining the technologies behind Behavio, with traffic monitoring from Zipdash to better understand spaces that many people navigate through while carrying a mobile device that connects to the internet with wireless signals and carries sensor data that can indicate the location and movements of those devices.

The patent tells us that current approaches to determine indoor locations of mobile devices are based on interior scans of wireless access points. Theses scans could be used to build a database that can model an indoor space by determining locations of the access points and their corresponding signal strengths at those locations. To create a database like this, an indoor wireless location provider would have to conduct site surveys at selected locations.

An undertaking like this could require surveying tens of thousands of buildings and floors to determine the location of the wireless access points. And this database could might become stale and inaccurate overtime due to location changes in the access points after the surveys are complete.

This patent is aimed at providing a scalable method that could be used to conduct site surveys to construct wireless access point models of an indoor location. This would be done by crowd-sourcing the wireless and INS (Inertial navigation systems) signals from multiple devices moving through the indoor location. The end goal of this would be to provide a more accurate and up to date model database of access points.

The approach behind the patent is the following method.

(1) Identifying a map of an indoor space,

(2) Receiving inertial navigation signals (sensor signals from accelerometers, etc.) from a set of mobile devices moving through that indoor space and

(3) Calculating user trajectories based on the inertial navigation signals. This method provides direction and speed of movement of the mobile devices being tracked. Tracking these trajectories helps to identify walkable areas of the indoor space being targeted, and where turns take place among these paths. The inertial navigation signals (INS) may include: accelerometer data, gyroscope data, and compass data.

This is how large indoor spaces such as shopping malls transit stations, airports, and similar indoor places may be mapped by looking at sensor data and wireless access signals from those devices.

The patent is:

Crowd-Sourcing Indoor Locations
Invented by: Faen Zhang, Edward Y. Chang, Yongqiang Huang, Shuchang Zhou
Assigned to Google
US Patent Application 20150204676
Published July 23, 2015
Filed: August 15, 2012


Aspects of the present disclosure provide techniques for constructing a scalable model of an indoor space using crowd-sourced inertial navigation system (INS) signals from mobile devices. By tracking INS signals from a number of participating users, the user’s trajectories can be estimated as they move their mobile devices indoors. The estimated trajectories can be scored against similar routes taken by other users. Routes with the highest scores are then laid out over a map of the indoor space to identify areas most often traveled to and from landmarks and distances between the landmarks.

Locations within Indoor spaces may also be identified in other ways as well. The patent points out:

(1) Other signals to identify locations for an indoor space may also be used that could include radio frequency (RF) signals, light, sound image recognition signals, and other types of signals and/or environmental factors or any combination of these.

(2) The server building a database may look at map information, which could include floor plans representing an indoor space within a building.

(3) “Beacon” messages may also be used to send out information to identify wireless network access points. The beacon messages may also include additional network access information which also assists devices in accessing the network.

(4) The patent tells us that Personal Indentifiable Information need not be collected, and may actually be removed in order to protect the privacy of the wireless network’s users.

(5) A GPS receiver may be included in the mobile devices , that could be used to determine the geographic location of the client device, and could identify the device’s latitude, longitude and altitude position.

(6) Mapping of an indoor space may help identify interior constraints, such as walls, which people cannot walk through, as well as frequent landmarks within that indoor space, such as offices, conference rooms, bathrooms.


Having people provide data about their locations can be essential for their use of such services. Information collected from the devices of people using those services help to provide such services. I can’t remember the last time I tried to navigate somewhere with the use of a paper map. I can remember visiting places, and using Google Maps to find walking directions to busy Urban spaces. This does seem to be a capability that helps make our lives easier.

Article Name
How You May Help Google Map Indoor Spaces
A recent Google Patent Application describes how Google might used sensors in Mobile devices to track and Map indoor spaces.

12 thoughts on “How You May Be Helping Google Map Indoor Spaces”

  1. Most interesting. This also means, by using an Android phone someone might be giving away the overall layout of their private homes – to Google and whoever has a legal right to access the data.

  2. This is fascinating. I wonder with what margin of error they can calculate probable locations of walls and doors, or even of more elaborate data – maybe if it sees you looking up recipes a lot in one room, it determines that it’s your kitchen.

    I wonder if it’s possible (not that it would ever be practical) to get an idea of what materials comprise parts of your home and your furniture, just based on the strength of the signals that can get through them when you’re using a device there.

  3. This is amazing. How Google is using technology to map the buildings but as Andreas very rightly mentioned that any body can get access to the layout of our homes by accessing this data. The scenario presented in some futuristic movies, where technology companies and even government access every private details of a citizen seems to be coming true and it must be stopped.

  4. Hi Ethan,

    The patent does talk about walls as constraints, noting no actual movement in those spaces. Interesting question about them understanding the kinds of materials your home may be comprised of, but nothing I recall from the patent that discusses that. They aren’t showing an interest in that, and I suspect they might not see value in the answer, though I can imagine that there might be some.

  5. Hi Cathy

    There is an element of science fiction to this process, that reminds me of movies like Minority Report. The patent isn’t hinting at malicious uses or any uses involving personally identifiable information, and having mapping software for very large indoor spaces such as shopping malls is something that could be very helpful. I think we need to see how Google uses the indoor mapping described here before we criticise them too much.

  6. I read this article completely about the comparison of most recent and earlier technologies, it’s awesome article. Thanks

  7. Superb article. We are working with a number of companies helping them maximize beacon marketing but the sector is still in it’s infancy. These ideas would take it to the next level. Nice work Bill.

  8. Hi Tom,

    I was a little surprised to see beacons mentioned in this patent, but it’s definitely an area of growth for the Web, and for Google. It will be interesting seeing where it goes.

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