Without it you can't make a phone call, buy a stock, pull cash from an ATM, or use electricity.
Regulators are investigating whether the devices unfairly violate a borrower's' privacy.
Company fixed the error, but it may be years before the issue is resolved.
A California woman is suing her former employer for firing her after she uninstalled an app on her company issued phone which tracked her location every moment. The woman claims she was being monitored even while she was not working and likened the experience to being a prisoner wearing an ankle bracelet.
Happy Camel is intended to combine your digital camera with your GPS device. If you feed it a list of digital photos and a tracklog, it figures out where these images were taken. It can embed this position in the EXIF-data of your photos and create a .KMZ file for Google Earth or Google Maps displaying your photos at the right positions along the tracklog. See my search for the "Rust wat"-cache (view in Google Maps) or this hike on Mt. San Jacinto (view in Google Maps) as examples. Happy Camel is distributed under the GNU General Public License.
Military, civilian systems crashed.
What do you get when you mix technology with candy bars? In a cool yet creepy marketing campaign, Nestle plans to stalk consumers with a "we will find you" promotion that involves GPS trackers embedded in chocolate bars.
architectural conjecture :: urban speculation :: landscape futures
The OpenStreetMap (OSM) project is a prime example in the field of Volunteered Geographic Information (VGI). Worldwide, several hundred thousand people are currently contributing information to the "free" geodatabase. However, the data contributions show a geographically heterogeneous pattern around the globe. Germany counts as one of the most active countries in OSM; thus, the German street network has undergone an extensive development in recent years. The question that remains is this: How does the street network perform in a relative comparison with a commercial dataset? By means of a variety of studies, we show that the difference between the OSM street network for car navigation in Germany and a comparable proprietary dataset was only 9% in June 2011. The results of our analysis regarding the entire street network showed that OSM even exceeds the information provided by the proprietary dataset by 27%. Further analyses show on what scale errors can be reckoned with in the topology of the street network, and the completeness of turn restrictions and street name information. In addition to the analyses conducted over the past few years, projections have additionally been made about the point in time by which the OSM dataset for Germany can be considered "complete" in relative comparison to a commercial dataset.