There were three main inspirations for this app: first, the rich availability of data sets published by the US Government (and the API’s availability to consume that data), second, the vast abilities of the OSIsoft PI System to store and return and visualize that data, and, third and last, the incredible geospatial visualizations offered by ESRI.
Altogether, those three inspirations guided by development of this app, which is currently unnamed, but which I refer to as an “Alternative Fueling Solution”. Its use would, I envisioned, allow four key groups of people to better accomplish their work:
1. An engineer in charge of a site’s electric vehicles can keep track of the location of a vehicle in her fleet along with key information on that vehicle
2. An operator of such a vehicle can quickly gauge his vehicle’s remaining fuel capacity and locate nearby and available fueling stations
3. A site manager can get a quick top-level view of the activity of alternative fuel vehicles on her site and both see where a vehicle is along with where it has been, to gauge behavior patterns
4. A data analyst can get not only instantaneous vehicle values but rich visualizations—trends, tables, gauges, and more—of historical data as well and furthermore download that data to his desktop PC for inspection
Additional requirements were that the application be web-based and compatible with almost all devices, and additionally, that it be simple to deploy.
All of these requirements were met in the completed app (see attached presentation slides); the app is a single file, only 30 kB in size (it's custom home screen icon is 10 kB in size, for comparison), and was deployed in less than ten minutes to an Azure cloud server, from which it was tested on a 2nd generation iPad, a Dell Latitude running Windows 8, and a Samsung Galaxy SIII.
The above link will take you to the mobile-compatible version of the project; it's currently disconnected from an automobile and from a PI Coresight Server, so much of the functionality is lacking, but this at least highlights the user interface, the device compatibility, the geolocating features, and the integration with the NREL fueling station dataset (assuming that there are any around your current position).
The complete code for the project will follow in a second post.