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This summer, San Francisco is launching a pilot program with wireless sensors that will also produce a data feed that can be used to find parking:
As others point out, this is a typical case of an idea that looks good on paper but in practice is quite useless, since there's no reservation feature. The most annoying thing would be to go to a spot shown as empty and finding it already full. That would result in more gas consumption than today's ad hoc method of finding a space.
Now if Google could collect real-time data via automated parking ticket systems, or even by getting access to security camera feeds and doing some image processing, then they'd be in business. I don't know how these systems are typically run, but it might be a smart move for Google to pursue partnerships with popular big-city parking locations for exclusive access to this data, to the extent that it can be collected from current systems.
In dense parts of San Francisco where this would be most useful, by the time I'm getting into my car, usually someone is already waiting for the space. This summer, San Francisco is launching a pilot program with wireless sensors that will also produce a data feed that can be used to find parking: http://sfpark.org/how-it-works/data-feed/
It's good to see someone at least tackling the problem.
As others point out, this is a typical case of an idea that looks good on paper but in practice is quite useless, since there's no reservation feature. The most annoying thing would be to go to a spot shown as empty and finding it already full. That would result in more gas consumption than today's ad hoc method of finding a space.
First, this is just a trial, they'll get a lot of information about how useful it is and tweak it accordingly.
Second, consider the data generated. A little bit of number crunching will generate a lot of highly useful information that can be used independently. Such as a map of all parking areas in the city along with other metadata such as how often there are spaces available, etc. Think about how this can be used. It can be used to provide better driving directions so that you are directed to nearby parking structures instead of the destination itself, when there isn't parking at the destination. It can also be used to figure out where it's best to park based on factors like general location, time of day, day of week, etc.
I just downloaded it and surprise surprise there are no spots listed at all in San Francisco. Ok, perhaps that's because the app is new, or maybe there are just no free spots. However, in a busy and competitive city like SF I really wonder how useful this is going to be. From my own anecdotal evidence living in SF, if I drive by an empty spot downtown during the day, it's usually gone anyway by the time I've circled…
Agreed, the current implementation is unlikely to work where it matters - in dense areas. Now if they'd find a way to couple this to realtime satellite data...