Geofencing - Part 1
The Series
“Series about what?” you may ask. Well, geofencing of course. I’m going to blather on about what they are, why there cool and why should you care, how to build (a simple) one, and when that’s all said and done I’m going to show you a long-winded video-tutorial of how to use my sample geofence-server.
I’ve split this blog series into three parts. For you few excited folks out there, worry much! I’ve not yet written the other parts in the series, but I imagine they’ll make there way on out here sooner or later. I am splitting up the posts so that my readers (you) can feel accomplished as they work there way through the sections. (Well, I’m splitting it up mostly so I can feel accomplished in finishing something, but I like the latter description so we’ll stick with that.) I’ve split it up as follows:
- What is [a] geofence/geofencing? [this post]
- How to build your own geofence-server with Ruby and Mongo [link]
- A sample geofence-server, built just for you [link]
Now, on to the blathering!
What is [a] Geofence/Geofencing?
General Description
A geofence is a conceptual fence around some geographically defined area. For example, the company I am currently working for deals in car-centric telemetry. Specifically, we process a lot of geo-spatial data. We use this to allow users to create a conceptual fence around their car (a geofence). When the car reports outside of the fence, we can send them a notification.
This is useful for making sure your car isn’t stolen, tracking your children, setting reminders for yourself, etc. If the idea of a conceptual fence is still a little fuzzy, I’ll draw you a pretty picture:
Some simple properties that a geofence might include:
- If the user inside or outside of the fence
- If the user traveled into (from outside of) the fence (and vice versa)
- How long the user been inside or outside of the fence
Conceptually, a geofence is by no means a profound idea. So, why do we care?
So Why Geofences?
Let’s face it, geofences are sexy. Apps that use user’s geo-spatial data is the next step in user-engagement. With geofences, we can interact with our users when they’re on the move; enjoying life and not spending countless hours in front of a computer. Apple realizes this to the point that they are including geo-spatial reminders in iOS (probably using geofences of some sort).
And the possibilities are endless! Sure, everyone’s going for the obvious answers right now, such as: alerts, reminders, etc.; but there are so many opportunities that haven’t been explored. What if Facebook used geofences in their next mobile app to determine how many people attended an event? They could use the GPS position of everyone running the FB app on their phone to determine who actually showed up. And guess what, they could easily do that with geofences! (Yeah maybe it’s creepy, but it’s cool!)
I’m sure there are many more use-cases for geofences but I’ll leave that for you to dream about. (What? You’re dreams aren’t location-aware? Hmm… Interesting)
Building Geo-Spatial Apps
There are several approaches to implementing geofences. You can use built-in features from several database engines. You can roll your own from scratch (because obviously your approach will be way awesome!). Or, you could take portions from various technologies to hack together a geofence engine/server.
When thinking about implementing your own server, you’ll want to think about several important pieces.
- How are you going to store the data?
- Does the size of the fence matter?
- What algorithm will you use to determine if someone is inside or outside of the fence?
- Does your storage model impact your algorithm and if so, is that good or bad?
- Is speed important from the beginning? How does that impact your algorithm?
- Etc.
It’s a lot of work. If you’re working on a prototype, side-project, or just playing around; you’ll probably want to utilize some existing technology or find a good introduction/blog (like this one!).
If you’re curious about geo-spatial data-processing in general, check out some of these articles as well:
- Spatial Indexing with Quadtrees and Hilbert Curves
- Hilbert Curves
- Geofencing with Rails and MySQL
- Computational Geometry (chapter 9) in Algorithms in a Nutshell
- Ray Casting for PIP problems
Available Services
And finally, to wrap things up, here is a list of sites that provide geofence services:
I’m sure there are more that I am forgetting, but you get the point. There are quite a few services out there and geofencing is going to be too important to ignore.
Part 2
Well, that’s all I have for you right now. If you think you’re ready, head on over to Part 2 for a whirlwind introduction on building your own (simple) geofence server with Ruby and Mongo.