[Dataset] intel/placelab (v. 2004-12-17)

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the initial version

@MISC{intel-placelab-2004-12-17,
  author = {Anthony LaMarca and Jeffrey Hightower},
  title = {{CRAWDAD} data set intel/placelab (v. 2004-12-17)}, 
  howpublished = {Downloaded from http://crawdad.cs.dartmouth.edu/intel/placelab},
  month = dec,  
  year = 2004
}
					

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 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.

[Traceset] intel/placelab/placelab (v. 2004-12-17)

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the initial version

@MISC{intel-placelab-placelab-2004-12-17,
  author = {Anthony LaMarca and Jeffrey Hightower},
  title = {{CRAWDAD} trace set intel/placelab/placelab (v. 2004-12-17)}, 
  howpublished = {Downloaded from http://crawdad.cs.dartmouth.edu/intel/placelab/placelab},
  month = dec,  
  year = 2004
}
					

Place Lab traceset for location accuracy analysis

For 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.

[Trace] intel/placelab/placelab/downtown (v. 2004-12-17)

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the initial version

@MISC{intel-placelab-placelab-downtown-2004-12-17,
  author = {Anthony LaMarca and Jeffrey Hightower},
  title = {{CRAWDAD} trace intel/placelab/placelab/downtown (v. 2004-12-17)}, 
  howpublished = {Downloaded from http://crawdad.cs.dartmouth.edu/intel/placelab/placelab/downtown},
  month = dec,  
  year = 2004
}
					

Place Lab log collected from Downtown, Seattle

Collected 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 )

[Trace] intel/placelab/placelab/ravenna (v. 2004-12-17)

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the initial version

@MISC{intel-placelab-placelab-ravenna-2004-12-17,
  author = {Anthony LaMarca and Jeffrey Hightower},
  title = {{CRAWDAD} trace intel/placelab/placelab/ravenna (v. 2004-12-17)}, 
  howpublished = {Downloaded from http://crawdad.cs.dartmouth.edu/intel/placelab/placelab/ravenna},
  month = dec,  
  year = 2004
}
					

Place Lab log collected from Seattle's Ravenna neighborhood

Collected from Seattle's Ravenna neighborhood 
- a medium-density residential neighborhood

File 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 )

[Trace] intel/placelab/placelab/kirkland (v. 2004-12-17)

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the initial version

@MISC{intel-placelab-placelab-kirkland-2004-12-17,
  author = {Anthony LaMarca and Jeffrey Hightower},
  title = {{CRAWDAD} trace intel/placelab/placelab/kirkland (v. 2004-12-17)}, 
  howpublished = {Downloaded from http://crawdad.cs.dartmouth.edu/intel/placelab/placelab/kirkland},
  month = dec,  
  year = 2004
}
					

Place Lab log collected from Kirkland, Washington

Collected from Kirkland, Washington 
- a sparse suburb of single-family homes

File 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 )

[Author] Anthony LaMarca

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[Author] Jeffrey Hightower

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[Paper] cheng-metropolitan

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Location 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).

[Paper] lamarca-placelab

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Location 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.