nitinguptadu / gas-sensors-for-home-activity-monitoring-data-set Goto Github PK

Abstract: 100 recordings of a sensor array under different conditions in a home setting: background, wine and banana presentations. The array includes 8 MOX gas sensors, and humidity and temperature sensors. Source: Creators: Flavia Huerta,Gaurav Gawade Ramon Huerta, University of California San Diego, USA Donors: Flavia Huerta Ramon Huerta, University of California San Diego, USA (rhuerta ‘@’ ucsd.edu) Thiago Mosqueiro, University of California San Diego, USA (thmosqueiro ‘@’ ucsd.edu) Jordi Fonollosa, Institute for Bioengineering of Catalunya, Spain (jfonollosa ‘@’ ibecbarcelona.eu) Nikolai Rulkov, University of California San Diego, USA ( nrulkov ‘@’ ucsd.edu ) Irene Rodriguez-Lujan, Universidad Autonoma de Madrid, Spain ( Irene.rodriguez ‘@’ uam.es ) Data Set Information: This dataset has recordings of a gas sensor array composed of 8 MOX gas sensors, and a temperature and humidity sensor. This sensor array was exposed to background home activity while subject to two different stimuli: wine and banana. The responses to banana and wine stimuli were recorded by placing the stimulus close to the sensors. The duration of each stimulation varied from 7min to 2h, with an average duration of 42min. This dataset contains a set of time series from three different conditions: wine, banana and background activity. There are 36 inductions with wine, 33 with banana and 31 recordings of background activity. One possible application is to discriminate among background, wine and banana. This dataset is composed of two files: HTsensordataset.dat (zipped), where the actual time series are stored, and the HTSensormetadata.dat, where metadata for each induction is stored. Each induction is uniquely identified by an id in both files. Thus, metadata for a particular induction can be easily found by matching columns id from each file. We also made available python scripts to exemplify how to import, organize and plot our data. The scripts are available on GitHub: https://github.com/gauravgawade951999/gauravgit For each induction, we include one hour of background activity prior to and after the stimulus presentation. Time series were recorded at one sample per second, with minor variations at some data points due to issues in the wireless communication. For details on which sensors were used and how the time series is organized, see Attribute Information below.

License: MIT License