The queensu/crowd_temperature dataset (v. 2015-11-20)  >  the temperature traceset

last modified

2015-11-20

nickname

temperature

short description

Simulated outdoor temperature data collected by taxis in Rome, Italy.

reason for most recent change

the initial version

release date

2015-11-20

date/time of measurement start

2014-02-01

date/time of measurement end

2014-02-04

methodology

We generate a temperature value for every active taxicab by applying Gaussian distribution. To fill out the parameters of Gaussian function, we need to assign the mean mu; and standard deviation sigma; for every run. Therefore, we assign a ground truth temperature mu; for every period in every grid on every day. We use data from The Weather Network http://www.theweathernetwork.com/ to assign the right ground truth to the right period and grid. For every taxicab, we assign a fixed error range sigma; that remains the same in all of its contributions. To do so, we randomly classify participant taxicabs into three classes. First class, called "honest", consists of taxicabs that usually sense accurate temperature within a 10% error range from the ground truth. The population of honest class is 145 taxicabs (50% of all participant taxicabs). Second class, called "dishonest", consists of taxicabs that usually sense inaccurate temperature within a 30% error range from the ground truth. The population of the dishonest class is 72 taxicabs (25%). Third class, called "misleading", consists of the rest of the participant taxicabs that is 72 (25%) that usually sense either accurate or inaccurate temperature. The data generator function makes a random decision of generating accurate or inaccurate temperature for each taxicab among the misleading class. The latter class plays a major role in the results of applying the data on a system, such as participants reputation system, since the accuracy of their contributions is not even. As a result, each taxicab has a sensed temperature contribution based on its fixed error range and the ground truth of the day, period and grid of its location.

 the queensu/crowd_temperature/temperature/ trace

 how to cite this traceset

Mohannad A. Alswailim, Hossam S. Hassanein, Mohammad Zulkernine, CRAWDAD dataset queensu/crowd_temperature (v. 2015‑11‑20): derived from roma/taxi (v. 2014‑07‑17), traceset: temperature, downloaded from https://crawdad.org/queensu/crowd_temperature/20151120/temperature, https://doi.org/10.15783/C7CG65, Nov 2015.

@misc{queensu-crowd_temperature-20151120,
    author = {Mohannad A. Alswailim and Hossam S. Hassanein and Mohammad Zulkernine},
    title = {{CRAWDAD} dataset queensu/crowd\_temperature (v. 2015-11-20): derived from roma/taxi (v. 2014-07-17)},
    howpublished = {Downloaded from \url{https://crawdad.org/queensu/crowd_temperature/20151120/temperature}},
    note = {traceset: temperature},
    doi = {10.15783/C7CG65},
    month = nov,
    year = 2015
}

TY  - DATA
TI  - CRAWDAD dataset queensu/crowd_temperature (v. 2015-11-20): derived from roma/taxi (v. 2014-07-17)
T2  - traceset: temperature
UR  - https://crawdad.org/queensu/crowd_temperature/20151120/temperature
PY  - 2015/11/20/
AU  - Mohannad A. Alswailim
AU  - Hossam S. Hassanein
AU  - Mohammad Zulkernine
DO  - 10.15783/C7CG65
ER  -