Sidewalk Labs’ Replica Has Spun Out

Some really interesting news in the digital twin planning space from last week:

The newly formed company, which is headed by Nick Bowden, also announced Thursday it has raised $11 million in a Series A funding round from investors Innovation Endeavors,  Firebrand Ventures and Revolution’s Rise of the Rest Seed Fund. The capital will be used to accelerate Replica’s growth through new hires beyond its existing 13-person staff, expansion to new cities and investment in its technology.

What makes this interesting is what Replica is:

The Replica modeling tool uses de-identified mobile location data to give public agencies a comprehensive portrait of how, when and why people travel. Movement models are matched to a synthetic population, which has been created using samples of census demographic data to create a broad new data set that is statistically representative of the actual population.

How, when and why people move around a city.

As a planner, investor or developer; you can imagine how this is really interesting. As the TechCrunch article points out, there are privacy implications to this but if this model works and can help plan cities better, we’ll all be better off. Cities are growing at exponential rates and new ones are being built every day. Helping planners make better initial decisions about where and how things should go OR help them make changes as the city develops will only improve life for all.

The iPhone U1 UWB Chip, Digital Twins and Data Collection

Oddly enough the biggest news this week from the iPhone 11 introduction by Apple barely got any play. In fact, on the iPhone 11 Pro website, you have to scroll past Dog Portrait mode to get any information about it. Apple describes the U1 chip thusly:

The new Apple‑designed U1 chip uses Ultra Wideband technology for spatial awareness — allowing iPhone 11 Pro to understand its precise location relative to other nearby U1‑equipped Apple devices.4 It’s like adding another sense to iPhone, and it’s going to lead to amazing new capabilities. With U1 and iOS 13, you can point your iPhone toward someone else’s, and AirDrop will prioritize that device so you can share files faster.4 And that’s just the beginning.

https://www.apple.com/iphone-11-pro/

Makes sense right? A better way to AirDrop. But there is so much more there, “precise location relative to other nearby equipped Apple Devices“. But what is UWB and why does it matter? The UWB Alliance says:

UWB is a unique radio technology that can use extremely low energy levels for short-range, high-bandwidth communications over a large portion of the radio spectrum. Devices powered by a coin cell can operate for a period of years without recharge or replacement. UWB technology enables a broad range of applications, from real-time locating and tracking, to sensing and radar, to secure wireless access, and short message communication. The flexibility, precision and low-power characteristics of UWB give it a unique set of capabilities unlike any other wireless technology.

So that’s really interesting, low energy use, high bandwidth and is very secure. I thought Jason Snell did a great job looking into the U1 on Six Colors:

From raw data alone, UWB devices can detect locations within 10 centimeters (4 inches), but depending on implementation that accuracy can be lowered to as much as 5 millimeters, according to Mickael Viot, VP of marketing at UWB chipmaker Decawave.

That’s pretty amazing. Basically it takes what makes Bluetooth LE great for discover, secures it and then makes it faster and more accurate. So we can see the consumer use cases for UWB, sharing files and finding those tiles we’ve heard so much about. But where this gets very interesting for our space is for data collection and working inside digital twins. You can already see the augmented reality use case here. A sensor has gone bad in a building, I can find it now with millimeter accuracy. But it’s not just what direction it’s how far. UWB uses “time of flight” to pinpoint location (measuring the time of signal to gauge distance), enabling it to know how far away it is. Just knowing a sensor is ahead of you is one thing, but knowing it is 20 feet away, that’s really a game changer.

You can see this through a little known app Apple makes called Indoor Survey. Small side note, back in late 2015 I blogged about Apple’s Indoor Positioning App which ties into all this. Where you really see this use is when you go to the signup page see how data is brought into this app using a standard called Indoor Mapping Data Format. Indoor Mapping Data Format (IMDF) provides a generalized, yet comprehensive data model for any indoor location, creating a basis for orientation, navigation and discovery. IMDF is output as an archive of GeoJSON files.  Going to the IMDF Sandbox really shows you what this format is about.

Apple’s IMDF Sandbox

Basically you see a map editor that allows you to really get into how interiors are mapped and used. So Apple iPhone 11 UWB devices can help place themselves more accurately on maps and route users around building interiors. Smart buildings get smarter by the devices talking to each other. Oh and IMDF, Apple says, “For GIS and BIM specialists, there is support for IMDF in many of your favorite tools.“. I will need to spend a bit more time with IMDF but its basically GeoJSON objects so we already know how to use it.

The thing about GPS data collection is it works great outdoors, but inside it is much harder to get accuracy, especially when you need it. With Indoor Survey, devices can collect data much more accurately indoors because they know exactly where they are. If you’ve ever used Apple Maps in an airport and seen how it routes you from gate to gate, you get an idea how this works. But with UWB, you go from foot accuracy to sub centimeter. That’s a big difference.

Now we’re a long way away from UWB being ubiquitous like Bluetooth LE is. Right now as far as I can tell, only Apple has UWB chips in their devices and we don’t know how compatible this all is yet. But you can see how the roadmap is laid out here. UWB, GeoJSON and an iPhone 11. Devices help each other get better location and in turn make working with Digital Twins and data collection so much easier.

Bad Esri Products are Good

I was having drinks the other day with an ex-Esri employee and we were talking about what Esri products I liked to work with. The short list is right below:

  1. ArcView 3.x
  2. MapObjects
  3. ArcIMS

Arc/INFO might be on that list but let’s cap it at three. None of them were products that Esri wanted to keep around. All of them were thrust in the marketplace and then poorly supported. I get the idea that Esri wanted everything on ArcGIS platform (Server being a joke for so many years is proof of this) but being a developer on those platforms was really hard. The transition from Avenue to VB/VBA was particularly brutal. There were books written to help with this transition, but none by Esri.

My trajectory was shaped by these products above being abandoned by Esri. I went another direction because of being burnt by proprietary products that when abandoned cause huge problems. I think you have two choices, either double down or hit the eject button. I’m so glad I ejected…

Download Your Fusion Tables Data

I first wrote about Fusion Tables back in 2010.

Google Fusion Tables – Are you kidding me? These stuff is “teh awesome”. Fusion tables are going to be more “killer” than Google Maps was. Yup, pay attention.

cageyjames

“teh awesome”? Seriously, who says that? Well I guess I did and that’s OK. Was it more “killer” than Google Maps, obviously no. It’s not that Fusion Tables was wrong, it is just there are so many alternatives to it that it really doesn’t matter anymore like it did when it first arrived.

Well if you’re like me, you probably have a lot of data in Fusion Tables and Google just sent out an email explaining how to get it out.

If you created many tables over the years, we’ve made it easy to download all your data in one step with a new dedicated Fusion Tables option in Google Takeout. You can save the rows, metadata and geometries of any base tables that you own, and export this data in the following formats: JSON, CSV and KML.

It’s a really nice tool, just tried it myself on some baseball data that I had in there. Google explains the tool as such:

The data for each table is saved to its own “archive”. The data will be saved in a Google Sheet; for datasets beyond the size limits of Sheets, you’ll get a CSV. This archive is stored in a top level folder called “ft-archive” in your Drive.

A Google Maps visualization is automatically created with the archived data. This map preserves many of the original Fusion Tables styling configurations. Any changes you make to the Sheet or CSV will appear in the map visualization.

A listing of all archived tables is stored in a Sheet. This handy Sheet is called “ft-archive-index” and lives within the “ft-archive” folder. The index Sheet summarizes each run of the archive tool and preserves the visualization URLs with encoded styles. Each time you run the archive tool, you will get additional archives based on the current data in your tables along with corresponding new rows in the archive directory.

You have until December 3, 2019 to get your data out. Google Takeout makes it easy which is really nice.

Moving the Home Office

Moving the home office is always interesting, you find so much that you’ve done over the past years and just stuck in a drawer or a shelf. Companies you worked for, RaspberryPis that never were used. Keys to a safety deposit box you don’t recall its location. But that is what makes moving therapeutic, cleaning out the old, unused parts of your life and focusing on the ones that make you happy. Do I need a puppet of Andrew Turner1 in my desk, nope. But I do need the things that make me happy. So now that I’ve boxed up everything but the work MacBookP Pro, I feel strangely at rest2.

  1. I still love Andrew, just haven’t had the need for his head on a stick. 

  2. At least until I have to unpack and realize that if I had only kept that RaspberryPi, my life would be so much better.