Miskolc IIS Hybrid IPS
Donated on 7/3/2016
The dataset was created for the comparison and evaluation of hybrid indoor positioning methods. The dataset presented contains data from W-LAN and Bluetooth interfaces, and Magnetometer.
Dataset Characteristics
Text
Subject Area
Computer Science
Associated Tasks
Classification, Clustering, Causal-Discovery
Feature Type
Integer
# Instances
1540
# Features
-
Dataset Information
Additional Information
The measurements were created to ease the development, comparison and evaluation of fingerprinting based hybrid indoor positioning methods. The measurements were recorded by the same kind of Android devices in order to reduce the effect of the variety of the hardware. The recording was preformed at weekend to reduce the noise of the environment. The measurements were performed in a three-story building and cover about 50% of it.
Has Missing Values?
Yes
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
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0 to 10 of 67
Additional Variable Information
#Measurement Info 1) Measurement Id - Java UUID 2) Timestamp - YYYY-MM-dd hh:mm:ss #Position Info 3-5) Coordinates of the absolute position (x,y,z) 6-7) Symbolic position - UUID and name of the position #Measruement Values 8-10) Magnetometer values x,y,z, real 11-42) WiFi RSSI values, negative integeres [-255,0] 43-65) Bluetooth devices {0,1} - 1 if the given devices was sensed in during the measurement.
Reviews
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset miskolc_iis_hybrid_ips = fetch_ucirepo(id=375) # data (as pandas dataframes) X = miskolc_iis_hybrid_ips.data.features y = miskolc_iis_hybrid_ips.data.targets # metadata print(miskolc_iis_hybrid_ips.metadata) # variable information print(miskolc_iis_hybrid_ips.variables)
Tth,Zsolt and Tams,Judit. (2016). Miskolc IIS Hybrid IPS. UCI Machine Learning Repository. https://doi.org/10.24432/C5CS4R.
@misc{misc_miskolc_iis_hybrid_ips_375,
author = {Tth,Zsolt and Tams,Judit},
title = {{Miskolc IIS Hybrid IPS}},
year = {2016},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5CS4R}
}Creators
Zsolt Tth
Judit Tams
DOI
Notes
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.