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Just added indoor navigation to WeWork, without them knowing. Got this up and running in 2 days, using wifi + motion data for precise location. Every other indoor solution takes months and usually require beacons. Hyper is going to fix the indoor navigation space. 💪

90,317 Aufrufe • vor 1 Jahr •via X (Twitter)

11 Kommentare

Profilbild von Andrew Hart ᯅ
Andrew Hart ᯅvor 1 Jahr

WeWork and others can sign up for free:

Profilbild von AndaSeat
AndaSeatvor 1 Jahr

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Profilbild von Tom Connole
Tom Connolevor 1 Jahr

Can you do the Toronto PATH please 🙏

Profilbild von Vine Layer 0
Vine Layer 0vor 1 Jahr

Once the whole world is mapped in this way, we've got a new economy.

Profilbild von mr.tipton
mr.tiptonvor 1 Jahr

This is so well done

Profilbild von 🟧Clean Coder🟧
🟧Clean Coder🟧vor 1 Jahr

Anything you can tell us about how you match up wifi to a physical location in the building? I assume you have to at least map the access points yeah? Really cool regardless.

Profilbild von Volodymyr
Volodymyrvor 1 Jahr

Airports needs this! Last week I was trying to navigate in @ParisAeroport and it was hard to get between 2G and 2E. Louvre another great application.

Profilbild von DAYWALKER
DAYWALKERvor 1 Jahr

Amazing. You are my favorite company / tech right now. So many applications, demo wows, natural growth path, and everyone wins. Retailer, customer, you. Good luck!

Profilbild von Bart Trzynadlowski
Bart Trzynadlowskivor 1 Jahr

Very slick!

Profilbild von MikeeBuilds ⛩️〰️🧱
MikeeBuilds ⛩️〰️🧱vor 1 Jahr

Definitely need to link up this @OhioState hospital with this.

Profilbild von Adam From Alaska
Adam From Alaskavor 1 Jahr

That is very clean. Excellent work

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Once we started to work with large global retailers, we needed a better way to scale this process. Ideally, the staff at the store could do this themselves — rather than us flying our team across the world — and then we could lower the cost and timelines. So we built a self-serve version of our survey app, with a tutorial mode designed for beginners. Over time, we collected millions of data points, and so we were able to develop an algorithm which would auto-correct mistakes. In other words, if the surveyor accidentally placed their ground-truth location in the wrong place on the map, we could use our algorithms to detect it, and correct it. So now we have WiFi, and with and our efforts on producing a high quality survey, we have the best WiFi positioning available. With WiFi on its own, it’s achieving 3 meter accuracy. This is a great foundation to build on. WiFi + Motion data To refine this down to 1-meter accuracy, we realised that we could combine WiFi with the same technology behind self-driving cars and robotics: a motion system called SLAM (Simultaneous Localization and Mapping). SLAM uses the accelerometer, gyroscope and camera system to understand precise device motion. Imagine a car driving through a tunnel, using the motion since its last GPS ping to keep location accurate until it comes out the other side. On a phone, this technology is very reliable, and measures device motion with high precision. But SLAM is measuring motion within its own coordinate space, it’s not aligned with the real world. SLAM tracks the user’s relative motion, like “moved forward 2 meters, then turned left”, but does “forward” mean “north”, or some other direction? It’s not calibrated, so it could mean any location, any direction. We can’t rely on the compass to help us out with this, because phone compasses are notoriously incorrect — everyone knows the frustration of being sent the wrong way down a street. So our job was to align this motion data with the triangulation data we were receiving from WiFi. We designed an algorithm that could simulate every possibility, filter the unlikely scenarios, and hone in your location, using WiFi as an anchor. So WiFi gives us the initial blue dot, SLAM gives us motion, and as the user starts walking and we receive more data, our algorithms can refine location accuracy down to a consistent 1-meter accuracy. We’ve tested these algorithms in many locations, on hundreds of hours of ground-truth data:

Andrew Hart

91,047 Aufrufe • vor 1 Jahr