mishmap

I’ve put together a prototype which allows you to use your mobile phone to listen to GPS encoded podcasts based on your current location. Please read System Requirements before you download the application

How it works:

1. Subscribe to podcast channels (currently hardcoded in the software) whose RSS documents have been extended with a GPS tag. For example, subscribe to the “San Francisco places” podcast channel.
2. Download the podcasts (which are just audio files) from the channels to which you have subscribed.
3. When you are roaming around, click “generate playlist” which will select the podcast most relevant to your location. The software selects the podcast whose GPS coordinate is closest to your current location and creates a playlist. For the current protoype, you must enter your current location manually, but a future version will take this value automatically from a connected GPS device (some of the newer phones already have integrated GPS).
4. Open up an MP3 player (such as pTunes) on your mobile device and select the generated playlist. A future version will automatically launch the MP3 player with the appropriate podcast.

Real world examples:

• Subscribe to a podcast channel which provides information about important architecture in New York. After downloading the podcasts, walk around Manhattan and listen to podcasts about buildings in close proximity.

• Subscribe to a podcast channel about an art exhibit in a museum. After downloading the podcasts, walk around the exhibit and listen to podcasts about the artwork in front of you. Note that an indoor application requires a different technology than regular GPS (see future directions below).

System requirements:

• PDA/cellphone loaded with java (J2ME with CLDC/MIDP 2.0 profile and JSR 75 for FileConnection).

• The software has been tested on a Palm Treo 600 with IBM’s J9 jvm, which you need if you have a treo. You can download it here.
• External memory card

Challenges:

1. There is no readily available GPS solution (without car mount/car lighter power) for the Palm Treo 600, since their are challenges interfacing with its serial port. Thus, for this prototype, the user must manually enter their GPS location. The Treo 650 has Bluetooth capability which would allow me to get around the serial port issue.
2. The J2ME MIDP 2.0 profile is limiting. The jvm cannot launch an external application, so the user must manually launch an MP3 player in order to listen to the selected podcast

Future Directions:

• Integrate a GPS device (solving challenge #1)

• Use a different J2ME profile (ie CDC), which would permit an external MP3 application to be automatically launched with the appropriate podcast (solving challenge #2)

• Extend the GPS tag to permit a “relative” coordinate, so that podcasts can be marked with an indoor location. This would be valuable for a museum type of application where the user can listen to information about various pieces in the exhibit.

• Extend the GPS tag with a “discoverability radius”. Thus, a podcast would not be discoverable if the user is too far away, even if the podcast is closer than any other in the vicinity. This would be useful in a museum type of application where a podcast about a particular artwork should not be selected if the user is at the other end of the room.

Wouldn’t an organic food company’s marketing department be thrilled by a model in which each link in a product’s life cycle is documented and available to the public? Perhaps this can be accomplished with a combination of RFID and location aware technology. Just reference the product barcode to hear the story of how your morning cup of coffee found its way to your kitchen table:

[Montevede, Costa Rica, May 29, 2004] Hola! My name is  Andres Guadamuz and I am a worker on a local coffee plantation, responsible for maintaining machinery used in gathering coffee beans. Read more about our operation at http://www.cafe-monteverde.com/default.htm.

[Transamerica trucking company, Northern route, June 3, 2004] I left San Jose, Costa Rica on Monday, and I am on schedule to arrive in Los Angeles on Saturday. Gasoline prices have recently risen by 12 cents a gallon, and we are trying to insulate you, our customer, from the increased prices by reducing the weight of the packaging of our cargo.

[Monteverde coffee packaging plant, Los Angeles, June 9, 2004] This bag of espresso coffee bean is best if used by September 3th, 2005.

[Whole Foods, San Francisco, July 19th, 2005] Hi! I’m Jennifer, your cashier, and I’d like to thank you for buying organic foods. By supporting the Monteverde Coffee Company in Costa Rica, you help provide jobs and support sustainable agriculture, while enjoying an exceptional product! Rest assured that this RFID chip will now deactivate itself in order to protect your privacy. If you’ve enjoy this product, Rainbow Foods will give you 5% off your next purchase.

Maybe "supply chain narratives" like these will make us more informed and compassionate consumers, as we recognize that we live in a global village. This model isn’t limited to produce – it can be applied to other industries like textiles or services (what really happens when you drop off your dry cleaning? )

It’s Christmas Eve, PST, and the jingle jingle of the final cash register is now only an echo. It seems like an appropriate time to put aside all those business plans which incorporate mobile locative technology. For a moment, let us forget how your cell phone will inevitably soon direct you to the nearest McDonalds, your dearest nearby friend in a one mile vicinity, or the next eligible single you haven’t met yet (but as luck and your PDA screen would have it happens to share your common interests and is sitting at the other end of the bar).

There is certainly a market for the above over-hyped ideas, but what about the more subtle concepts over which venture capitalists are not going ga-ga? I’m referring to the uses of location-aware technology which can make a positive difference in improving our society. Here is one example and I challenge you to think of others. Happy holidays!

The mobile social worker

Envision a new breed of social worker who actively seeks out people in need. This preventative approach would have people visiting different communities prone to issues like racial tension, poverty, or poor health.

Armed with a PDA loaded with a specialized application for the task at hand, the social worker would fill out an electronic form (a questionnaire) on-site. When done with the interview, she would publish it to a server, along with the current GPS coordinate.

GIS software (ArcView, openGIS, etc) would crunch the datapoints and come up with models for addressing a variety of escalating issues.

• Are there many people suffering from a particular ailment? What could be the cause? For example, we might be alerted to illegal toxic waste dumping if we layered maps of cancer rates with maps of manufacturing plants.
• Are many children in this community malnourished? Perhaps nutritious lunch time meals can be sent to their schools.
• Do interviews indicate escalating racial tension? Perhaps we should deploy relevant social workers to promote tolerance with the community before a tragedy.

As these examples demonstrate, an effective strategy might be:

1. Define/pose a question.
2. Deploy a mobile task force to answer it, using some hardware which can publish information along with a spatial coordinate.
3. Use GIS software to crunch the data
4. Respond

You may now resume your post-holiday shopping.

Having just read Franz Dill’s posting (Future Now) about YellowArrow, it occurs to me that discoverability is a crucial and subtle locative concept.

Due to its technical limitations, the current breed of SMS mobile social toys needs you to be explicit in order to understand your current spatial context. Sites like dodgeball rely on the user to provide this info (ie. @myDiveBar), before querying a database to find one’s GPS coordinates and close-by friends.

Once GPS becomes pervasive on all cell phones, the previously manual “I am here” becomes a passive sequence of pings to whatever services you subscribe to. But how do you specify what you’re seeking? And how do you describe who knows about you?

Let’s define one’s “discoverability footprint” as a spatial and temporal description of what you can find and who can find you. The latter should satisfy those who have misgivings about the privacy implications for locative technologies.

I imagine an interface in which you could filter:

• topic – ie. jazz club with food
• groups – a la Yahoo Groups to limit your audience. ie. “ny nightlife list”
• direction – ie. only in the direction I am heading (with SMS, one would need to manually enter “North”; with GPS technology, it’s a no brainer). You could make your location or annotations known to people walking away from you (or where you have been)
• pattern – ie. 2 blocks to my right or left….or within 1 square mile northwest, except any areas discouraged by the neighborhood crime web service
• time – ie. after 8pm on a weekday. I envision this as a knob-style widget, where you can turn it like a radio tuner to find the right frequency. A physical knob feels intuitively like the right way to go.

The optimal discoverability interface will be a mix of useful hardware and software. Maybe a bunch of generic phycical knobs, levers and buttons which can be programmed and customized for the locative task at hand.

Jason Tester writes about his experience in creating spatial content in San Francisco. He decomposes these spatial annotations into 2 categories – “I was here” and “You are here”.

The former is likely an emotional, possibly exhibitionistic statement (”I was standing under this window sill when someone exclaimed, ‘garde loo’”). The latter classification smells (sorry!) of intent and is potentially more useful. Jason provides these examples:

• warnings (”bad neighborhood!”)
• lost & found (perhaps with an incentive a la geo-cache)
• temporary notes (”bar was lame; the party has moved!”)

http://blogger.iftf.org/Future/000599.html