Ever wondered why your smartwatch or smartphone only tells you the distance you walked only in terms of steps in indoor environments? You guessed it right, lack of reliable GPS in indoor environments. But, there are so many signals around us such as WiFi that could help make these devices obtain accurate distance measurements in indoor environments. But, wait. Why is accurate distance measurement in indoor environments important? Is it even necessary?
You might be familiar with the fact that research in indoor localization (i.e finding a reliable equivalent of GPS for indoor environments) has been a topic of interest over the past two decades. Still, we are still haven't reached a point where we have a ubiquitous equivalent to GPS yet. However, the demand for accurate localization has been growing with the advent of Internet of Things : You now have robots cleaning your house, Drones taking over deliveries and so on. Now, imagine a situation when a device got to know its location at some point reliably using GPS. Now, consider that the device was able to accurately measure how much it moved relative to that point. Voila! You can still track its location without the need for constant GPS connectivity. So, you could plan a route for your robot to clean or for your drone to navigate your warehouse! (Hello Amazon ;)!)
How is this possible? Wouldn't the estimated distance incur more errors over time? If you have these questions, I would invite you to read my paper : "Enhancing Indoor Inertial Odometry with WiFi" (See
In this video, you will find a proof-of-concept demonstration of a research prototype WIO that I have developed for accurate distance estimation using WiFi Signals. Shot by an audience member at the The 27th IEEE International Conference on Network Protocols (ICNP) in Chicago, Illinois, you can see example application of WIO on a robot car (like a roomba) to enable it accurately track the distance it has moved using the WiFi signal from a nearby Access Point and an Inertial Measurement Unit. You can see that the device moves 3ft and our scheme was able to accurately predict this distance, despite so many people walking around and creating disturbances in the WiFi signal.
This work won the best demo award at ICNP 2019! Thank you for watching.
ICNP 2019 :
Full Paper at Ubicomp 2019:
My Webpage : raghav-hv.com
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