intel/placelab2004121712200412172006-11-09intel/placelabLocation-aware dataset collected using Place Lab software.

These traces contain 802.11, GSM and GPS trace data collected using Place Lab software, for 3 different neighborhoods in the Seattle metro area. Total trace duration is approximately 2 hours, with around 55,000 total readings.

the initial version2004-12-172004-09-262004-09-293841http://www.placelab.org/datasets/http://www.crawdad.org/wiki/pmwiki.php?n=Main.Dataset.intel-placelablocationwardrivingGPSsignal strengthcellular networkLocation-aware Computing802.11 infrastructureGSM (Global System for Mobile Communications)GPS (Global Positioning System)The accuracy of Place Lab depend on the number and mix of beacons in the environment, making it difficult to make absolute statements about the system's performance. To quantify the accuracy of Place Lab and how they vary by area, we measured both 802.11 beacon density and corresponding Place Lab accuracy in an urban, a residential and a suburban area.For each area (see the traceset included), we drove around the areas with a laptop with an Orinoco 802.11 interface, a GPS unit (Wired Garmin Rhino GPS unit), and a Nokia 6600 cell phone.We collected 802.11 and GSM beacons periodically using Place Lab software. We also took GPS readings for measuring "ground truth" location to be used for accuracy estimation. Total trace duration is approximately 2 hours, with around 55,000 total readings.19200412172006-10-17intel/placelab/placelabPlace Lab traceset for location accuracy analysis.

Place Lab traceset for location accuracy analysis.

the initial version2004-12-172004-09-262004-09-29Location-aware ComputingFor each locale (see the traces included - downtown, ravenna, and kirkland), we drove around the areas for sixty minutes with a laptop, a GPS unit, and a Nokia 6600 cell phone. 802.11 scans were performed at 4Hz using an Orinoco 802.11 interface in the laptop. GPS readings were taken at approximately 1Hz using an external serial GPS unit. Finally, the GSM measurements were taken at 1Hz by the Nokia 6600 and relayed to the laptop via Bluetooth4. At all times we tried to navigate within areas in which GPS lock would not be lost as GPS forms the round truth location to be used to estimate beacon positions and Place Lab's accuracy.Unfortunately, our Nokia cell phones only allow us to know the ID of the current cell tower with which the phone is associated, making it impossible to learn the full set of towers in range. While this allows us to know if coverage is available, it does not let us learn about density or Place Lab's accuracy if all towers in range were known. Thus all GSM-based Place Lab results are calculated using the single available cell ID./download/intel/placelab/pervasive05_traces.tar.gzintel/placelab52200412172006-10-17intel/placelab/placelab/downtownPlace Lab log collected from Downtown, Seattle.

Place Lab log collected from Downtown, Seattle.

the initial versionfalse2004-12-172004-09-262004-09-26Collected from Downtown Seattle - a mix of commercial and residential urban high-rises.File names are as follows: downtown{no}.{month}.{day}.{year}.txt - no: serial number - month, day, year: measurement start date in MM.DD.YY format All files are in the Place Lab log format. (For documentation on the log format and tools that can parse them, visit http://www.placelab.org )intel/placelab/placelab53200412172006-10-17intel/placelab/placelab/ravennaPlace Lab log collected from Seattle's Ravenna neighborhood.

Place Lab log collected from Seattle's Ravenna neighborhood.

the initial versionfalse2004-12-172004-09-292004-09-29Collected from Seattle's Ravenna neighborhood - a medium-density residential neighborhoodFile names are as follows: ravenna{no}.{month}.{day}.{year}.txt - no: serial number - month, day, year: measurement start date in MM.DD.YY format All files are in the Place Lab log format. (For documentation on the log format and tools that can parse them, visit http://www.placelab.org )intel/placelab/placelab54200412172006-10-17intel/placelab/placelab/kirklandPlace Lab log collected from Kirkland, Washington.

Place Lab log collected from Kirkland, Washington.

the initial versionfalse2004-12-172004-09-262004-09-26Collected from Kirkland, Washington - a sparse suburb of single-family homesFile names are as follows: kirkland{no}.{month}.{day}.{year}.txt - no: serial number - month, day, year: measurement start date in MM.DD.YY format All files are in the Place Lab log format. (For documentation on the log format and tools that can parse them, visit http://www.placelab.org )intel/placelab/placelab38intel/placelabAnthony LaMarcaanthony.lamarca@intel.comIntel Research SeattleResearcher41intel/placelabJeffrey Hightowerjeffrey.r.hightower@intel.comIntel Research SeattleResearchercheng-metropolitanYu-Chung ChengYatin ChawatheAnthony LaMarcaJohn KrummProceedings of the Third International Conference on Mobile Systems, Applications, and Services2005--06--http://www.placelab.org/publications/pubs/pervasive-placelab-2005-final.pdfLocation systems have long been identified as an important component of emerging mobile applications. Most research on location systems has focused on precise location in indoor environments. However, many location applications (for example, location-aware web search) become interesting only when the underlying location system is available ubiquitously and is not limited to a single office environment. Unfortunately, the installation and calibration overhead involved for most of the existing research systems is too prohibitive to imagine deploying them across, say, an entire city. In this work, we evaluate the feasibility of building a wide-area 802.11 Wi-Fi-based positioning system. We compare a suite of wireless-radio-based positioning algorithms to understand how they can be adapted for such ubiquitous deployment with minimal calibration. In particular, we study the impact of this limited calibration on the accuracy of the positioning algorithms. Our experiments show that we can estimate a user's position with a median positioning error of 13-40 meters (depending upon the characteristics of the environment). Although this accuracy is lower than existing positioning systems, it requires substantially lower calibration overhead than existing indoor positioning systems and provides easy deployment and coverage across large metropolitan areas. Moreover, unlike GPS, it does not require line of sight to the sky and consequently works in areas where GPS does not (indoors and in dense urban environments).mobile, crawdadmeasurementwirelessintel_placelabcrawdadintel/placelab20050601lamarca-placelabAnthony LaMarcaYatin ChawatheSunny ConsolvoJeffrey HightowerIan SmithJames ScottTimothy SohnJames HowardJeff HughesFred PotterJason TabertPauline PowledgeGaetano BorrielloBill SchilitProceedings of the Third International Conference on Pervasive Computing2005--05--http://www.placelab.org/publications/pubs/pervasive-placelab-2005-final.pdfLocation awareness is an important capability for mobile computing. Yet inexpensive, pervasive positioning - a requirement for wide-scale adoption of location-aware computing - has been elusive. We demonstrate a radio beacon-based approach to location, called Place Lab, that can overcome the lack of ubiquity and high-cost found in existing location sensing approaches. Using Place Lab, commodity laptops, PDAs and cell phones estimate their position by listening for the cell IDs of fixed radio beacons, such as wireless access points, and referencing the beacons' positions in a cached database. We present experimental results showing that 802.11 and GSM beacons are sufficiently pervasive in the greater Seattle area to achieve 20-30 meter median accuracy with nearly 100% coverage measured by availability in people's daily lives.mobile, crawdadmeasurementwirelessintel_placelabcrawdadintel/placelab20050501