Just got out of an interesting session with Garmin at the Telematics Update show.
Garmin said that fine detail analysis of a car's behavior including speed of acceleration; speed of braking; and avoiding hills could dramatically increase the range of an electric vehicle (EV)... or reduce the carbon footprint of a gas vehicle. This is over and above traditional information like speed and distance. It was, quite frankly, an implementation of geospatial analysis I hadn't thought of.... That is until the business/green aspects were provided to me...
Since EVs currently only have so many charging locations, you don't want to get stuck down the wrong road or halfway up the wrong hill.... ;)
The question will be how well an organization can integrate the various telematic information to create that analysis:
- Dynamic EV information like battery charge
- Fluid external information like traffic density
- Static external information like rise and fall of streets; as well as charging station location
to provide an EV’s driver with the "operational BI" on how/where to drive.
Other than shortest distance or shortest time how many elements due you think the average driver can process or agree to process from a navigation system?
Or does it depend on training associated with running out of "juice" on the wrong side of a hill from the charging station? ;)
Post your comments below or email (John.Myers@BlueBuffaloGroup.com) / twitter (@BlueBuffaloGrp) me directly.
Posted June 8, 2011 6:57 PM
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