Partially obscured by the evening commute, though, was a 3rd peak. That was new. “What we know from traditional surveys is, people remember their biggest trips. But what people forget is ‘I’m picking up the laundry,’ ‘I’m stopping to grab coffee.’ We see more of these data captured by cell phones.” Those trips, the futzing around of daily life, tend to happen in off-peak hours—from midday into the evening, 8 or 9 o’clock. “That’s traditionally when agencies cut down their services.” The buses are slacking off when they could be serving a whole other population.
Tag: locative
Investigatory Datasheds
the notion of a “crime scene” has thus been digitally expanded, taking on a kind of data shadow, as someone simply driving down a street or sitting in a park one day with their phone out is now within the official dataprint of an investigation
25 regular places
people are constantly exploring new places. They move to a new home, find a new favorite restaurant, find a new bar, or start going to another gym, etc. However, the number of regularly visited places is constantly 25 in a given period. If a new place is added to the list, 1 of the places disappears. The pattern is the same when the researchers divide the locations into categories based on how often and how long time they spend at the location.
ManyCities
“ManyCities” is a new website that “explores the spatio-temporal patterns of mobile phone activity in cities across the world,” including London, New York, Los Angeles and Hong Kong. Taking complex data and organizing it in a intuitive way, the application allows users to quickly visualize patterns of human movement within the urban context down to the neighborhood scale. You can imagine how useful a tool like this can be for urban planners or even daily commuters, especially once real time analytics come into play. Take a look at ManyCities yourself, here.
AR localization
coincidentally, i spent several weeks in 2000 modeling this same train station for a political referendum
we used the then cutting-edge VRML to allow you to explore the new train station in 3D in your browser. we worked off of architectural blueprints to create our 3D rendering.
Here is a small video of what we have been working on in my team at ETH over the last weeks. We are working on creating models for localization in large buildings such as malls. These models are the result of fusing data provided by multiple users over time. This should inspire developers to see which kind of indoor localization support to expect from the Tango API in the course of the next months.
Location Exfiltration from Power Consumption
Our approach enables known route identification, real-time tracking, and identification of a new route by only analyzing the phone’s power consumption
Brain location providers
Your brain has at least 4 different senses of location – and perhaps as many as 10
just like smartphones, your brain has multiple location providers and uses a fused approach to get a location 🙂
New York Songlines
To this end I offer these as the New York Songlines. An oral culture uses song as the most efficient way to remember and transmit large amounts of information; the Web is our technological society’s closest equivalent. NASDAQ Times Square by aa440, on FlickrEach Songline will follow a single pathway, whether it goes by one name or several; the streets go from river to river, while the avenues stop at 59th Street, which is my upper limit for the time being. I’ve long since gone beyond the parts of Manhattan with which I have any real personal knowledge, making tips from readers increasingly important.
creating reference points by telling stories.
Seeking Serendipity
If you want to explore beyond the places your friends think are the most enjoyable, or those the general public thinks are enjoyable, you need to seek out curators who are sufficiently far from you in cultural terms and who’ve annotated their cities in their own ways.
BeerCloud
this looks like a fun app.
Gregor J. Rothfuss 