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Indoor positioning – Are we nearly there yet?

It is hard to imagine anyone not knowing what a GPS (Global Positioning System) is these days. GPS is great when you are outdoors, but the minute you walk into a large building, mall, or hospital, your GPS receiver becomes useless.

I don’t know about you, but getting lost in a large mall is not an unusual scenario. Indoor navigation (for humans and robots) is an obvious use case, but there are others, such as:

  • Highly accurate positioning of less than one meter accuracy - for example enabling a retailer to know exactly in front of which item a customer is standing or exactly where a specific, tagged asset is in a large warehouse.
  • Positioning in 3D - knowing whether you are standing or in distress and lying on the floor.
  • Tracking - in shopping centres it may be of interest to understand what paths people take as they explore the place; in times of emergency it could be important to know where people are and where they are heading.

There are already quite a few indoor positioning solutions that assume that you have your smart phone with you at all times and that Wi-Fi and/or Bluetooth are turned on. But this is not always true. Some solutions require a lot of complex Wi-Fi and networking infrastructure to be in place.

Ideally, one would like minimal infrastructure and nothing on your person, but with the capability of scaling to locating and tracking of many entities simultaneously in a privacy preserving way (i.e., avoid using cameras). As usual, tradeoffs need to be made and to understand them let’s go over some basics.

How does indoor positioning work?

The simplest method is transmitting and reflecting a pulse (RF, light, ultrasound). This reflected pulse is picked up by a receiver and the time between transmission and reception is measured. Since the pulse speed is known (speed of light for RF and light, speed of sound in air for ultrasonic) the distance can be calculated. Seems simple but if the transmission is in all directions (omnidirectional antenna) then your reflected pulse can come from anywhere on a circle as all points on a circle are the same distance from its centre where the radar is located.

So we need to determine direction. This can be achieved by making the antenna directional – a narrow beam is pointed at the direction of interest or the beam is “swept” across a section of interest. Here is another complication: almost everything reflects the radar pulse and most of it is not interesting.

How do you track entities of interest? A lot of what you are looking at is stationary and this “background” can be accounted for. Moving objects “change” the pulse (check out the Doppler effect ) and identifying this change allows one to immediately identify the moving things. So it is not so simple after all!

This is where the Internet of Things steps in. If the object you are locating and tracking happens to have a device with some unique identifier attached to it, like a tag or smart phone, things become significantly easier. Now you can have many fixed transmitters sending out pulses, getting received by the device that can then send out a “reply” rather than the reflected pulse that can also contain its unique identifier. The transmitters can be simple and omnidirectional, but then you need a few of them (remember each one defines a circle; in the plane, i.e., in 2D, at least 3 transmitters are needed to determine a unique position) – the determination of a location from measuring distances to a few fixed points is known as Trilateration (check out Multilateration while you’re at it).

This still requires some calculations that need to be performed somewhere – basically solving for the intersection point of multiple circles. Additionally, in many cases, the object is moving and we would like to track it accurately and in real time.

What else do we need?

We know from outdoor location-based applications and services we want our location to be pinpointed a map. Doing something similar for indoor positioning is more difficult than outdoor positioning where high quality maps are readily available. Many new buildings may have used sophisticated 3D architectural tools when being designed and therefore good accurate 3D models could be made available.

This is less likely to be true of older buildings. Any such drawings, just like maps, need to be kept up to date and digitally available. In this respect, the entire building has a place in the Internet of Things ecosystem, sharing its floor plan and dimensions to the connected devices and people who move within it.

The technology and standards are emerging, but the ultimate indoor positioning solution that is inexpensive, has high accuracy, has good privacy protection, etc., is still not quite there.

Where we are in space and time is tightly coupled with what we are doing and also provides some of our context.

Outdoor location is part of the story (when did we leave home, where did we go, etc.) but many of us spend a lot of their time indoors – at home, in the office, in shopping malls, in restaurants, etc. – providing much more information on our activities, behaviour, preferences, and more.

Whether we want to share this data and let others use it, is a different story.

Gadi Lenz, chief scientist at AGT International

Image source: Shutterstock/Jojje