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GNFUV Unmanned Surface Vehicles Sensor Data Set 2 Data Set
Download: Data Folder, Data Set Description

Abstract: The data-set contains eight (2x4) data-sets of mobile sensor readings data (humidity, temperature) corresponding to a swarm of four Unmanned Surface Vehicles (USVs) in a test-bed, Athens, Greece.

Data Set Characteristics:  

Multivariate, Sequential, Time-Series

Number of Instances:

10190

Area:

Computer

Attribute Characteristics:

Real

Number of Attributes:

6

Date Donated

2018-09-13

Associated Tasks:

Regression

Missing Values?

Yes

Number of Web Hits:

13009


Source:

Dr Christos Anagnostopoulos; School of Computing Science, University of Glasgow; email: christos.anagnostopoulos '@' glasgow.ac.uk; G12 8QQ Scotland, UK. (NETLAB Group: https://netlab.dcs.gla.ac.uk/)


Data Set Information:

The data-set comprises 2 x (4) sets of mobile sensor readings data (humidity, temperature) from four (4) Raspberry Pi's corresponding to a swarm of four (4) Unmanned Surface Vehicles (USVs). Each USV set contains records of the format: {'Device'; 'humidity-value'; 'temperature-value'; 'experiment-id';'sensing-time','Pi'}. The swarm of the USVs is moving according to a GPS pre-defined trajectory. The USVs are floating over the sea surface in a coastal area of Athens (Greece). More information: [Web Link]


Attribute Information:

Attributes:
'device' = USV ID (String)
'humidity' = sensed humidity value from the USV sensor (real value)
'temperature' = sensed temperature value from the USV sensor (real value)
'experiment' = 1 (constant real value)
'time' = the sensing and reporting time (real value)
'pi' = Raspberry Pi ID


Relevant Papers:

Please cite one of the following papers:
[1] Harth, N. and Anagnostopoulos, C. (2018) Edge-centric Efficient Regression Analytics. In: 2018 IEEE International Conference on Edge Computing (EDGE), San Francisco, CA, USA, 02-07 Jul 2018
[2] Harth, N., Anagnostopoulos, C., (2017) Quality-aware Aggregation & Predictive Analytics at the Edge. IEEE International Conference on Big Data (IEEE Big Data 2017), December 11-14, 2017, Boston, MA, USA



Citation Request:

Please cite one of the following papers:
[1] Harth, N. Anagnostopoulos, C. (2018) Edge-centric Efficient Regression Analytics. In: 2018 IEEE International Conference on Edge Computing (EDGE), San Francisco, CA, USA, 02-07 Jul 2018
[2] Harth, N., Anagnostopoulos, C., (2017) Quality-aware Aggregation & Predictive Analytics at the Edge. IEEE International Conference on Big Data (IEEE Big Data 2017), December 11-14, 2017, Boston, MA, USA.


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