Multi-Hop Sensor Network
Labeled wireless sensor network data set collected from a multi-hop wireless sensor network deployment using TelosB motes.
Usage
var dataset = require( '@stdlib/datasets/suthaharan-multi-hop-sensor-network' );
dataset()
Returns a dataset consisting of labeled wireless sensor network data set collected from a multi-hop wireless sensor network deployment using TelosB motes.
var data = dataset();
/* returns
[
{
'reading': 1,
'mote_id': 1,
'indoor': 0,
'humidity': 43.82,
'temperature': 30.21,
'label': 0
},
...
]
*/
Notes
- Humidity and temperature measurements were collected at
5
second intervals over a six hour period on July 10, 2010. - Temperature is in degrees Celsius.
- Humidity is temperature corrected relative humidity, ranging from 0-100%.
- The label
0
denotes normal data, and the label1
denotes an introduced event. - If a mote was an indoor sensor, the corresponding indicator is
1
. If a mote was an outdoor sensor, the indoor indicator is0
.
Examples
var incrgrubbs = require( '@stdlib/stats/incr/grubbs' );
var data = require( '@stdlib/datasets/suthaharan-multi-hop-sensor-network' );
var acc;
var d;
var i;
var j;
var k;
// Get the sensor data:
d = data();
// For each mote, test for an outlier temperature measurement...
i = 0;
for ( j = 0; j < 4; j++ ) {
k = j + 1;
// Create a new accumulator for performing Grubbs' test:
acc = incrgrubbs();
// Update the accumulator with temperature data...
while ( i < d.length && d[ i ].mote_id === k ) {
acc( d[ i ].temperature );
i += 1;
}
// Print test results:
console.log( '' );
console.log( 'Mote: %d', k );
console.log( '' );
console.log( acc().print() );
}
CLI
Usage
Usage: suthaharan-multi-hop-sensor-network [options]
Options:
-h, --help Print this message.
-V, --version Print the package version.
--format fmt Output format: 'csv' or 'ndjson'.
Examples
$ suthaharan-multi-hop-sensor-network
References
- Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher Leckie, and Marimuthu Palaniswami. 2010. "Labelled data collection for anomaly detection in wireless sensor networks." In Proceedings of the Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2010). Brisbane, Australia: IEEE.
License
The data files (databases) are licensed under an Open Data Commons Attribution 1.0 License and their contents are licensed under a Creative Commons Attribution 4.0 International Public License. The original dataset is attributed to Shan Suthaharan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher Leckie, and Marimuthu Palaniswami and can be found here. The software is licensed under Apache License, Version 2.0.