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ble-accelerometer-indoor-localisation-measurements.zip (34.96 MB)
Residential Wearable RSSI and Accelerometer Measurements with Detailed Annotations
Version 5 2019-01-31, 08:40
Version 4 2018-08-23, 08:12
Version 3 2018-08-23, 08:10
Version 2 2018-08-23, 08:05
Version 1 2018-06-12, 14:52
dataset
posted on 2019-01-31, 08:40 authored by Dallan ByrneDallan Byrne, Michal KozlowskiMichal KozlowskiContext
This repository offers smart-home wearable accelerometer and Radio Signal Strength (RSS) data acquired : 1) with low-cost hardware 2) with high-resolution location annotations 3) from four lived-in premises.
Instructions
1. Download and unzip the dataset.
2. Navigate to:
ble-accelerometer-indoor-localisation-measurements/codes/load_dataset_py
3. Install prerequisites:
pip -r install requirements.txt
4.Run the sample module to load and view the measurements :
python3 src/load_data.py
Further Information
Please cite: Byrne, D., Kozlowski, M., Santos-Rodriguez, R., Piechocki, R. & Craddock, I. Residential wearable RSSI and accelerometer measurements with detailed location annotations. Sci. Data 5, 180168 (2018). https://www.nature.com/articles/sdata2018168
Thanks to: Raul Santos-Rodriguez, Robert Piechocki, Ian Craddock, SPHERE IRC team, Beatriz Monsalve-Carcalen and Raimon Fransoy.
Funding
This work was performed under the Sensor Platform for HEalthcare in a Residential Environment (SPHERE) Interdisciplinary Research Collaboration (IRC) funded by the UK Engineering and Physical Sciences Research Council (EPSRC), Grant EP/K031910/1
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Keywords
RSSIBluetooth-determined locationAccelerometersbehaviour patternsSmart Home Systemindoor localizationwearablehealth monitoring systemannotation procedureElectrical and Electronic Engineering not elsewhere classifiedHealth InformaticsHealth Information Systems (incl. Surveillance)Applied Computer ScienceKnowledge Representation and Machine Learning
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