BLE RSSI 加速度计 室内测量免费

资源介绍

Context This repository offers smart-home wearable accelerometer and Radio Signal Strength Indicator (RSSI) data acquired : 1) with low-cost hardware; 2) with high-resolution location annotations; 3) from four UK homes. The data are intended to evaluate RSSI-based indoor localisation methods with activity measurements provided from a user-worn wearable device. Location labels are recorded automatically using a small camera which registers fiducial floor tags as the participant carries out their normal routines in a natural way. Approximately 14?hours of annotated wearable measurements are provided. A user wears a wearable device on their wrist, which records accelerometer data at 25Hz. This data is transmitted, at 5Hz, towards a number of Bluetooth Low Energy access points (8-11) within the home. The access points mark the packets with a Received Signal Strength Indicator (RSSI) measurement and note the accelerometer measurements. The user's actual location is derived from a camera which registers fiducial floor tags, placed at a metre apart, where the user pose and relative position is decoded using image processing code (also provided). A complete guide to dataset is available at: https://www.nature.com/articles/sdata2018168/ Figshare link to the repository: https://figshare.com/articles/Residential_Wearable_RSSI_and_Accelerometer_Measurements_with_Detailed_Annotations/6051794 This data was collected as part of the SPHERE IRC project (https://www.irc-sphere.ac.uk/) at Bristol University. Getting started 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 Content Read https://www.nature.com/articles/sdata2018168 for all the juicy details. A guide to loading the data using python is provided at: /residential_wearable_data_repo_with_location_labels_sub/codes/load_dataset_py/readme.txt Acknowledgements Data Authors: Dallan Byrne & Michal Kozlowski 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. Inspiration Looking to inspire other researchers and enthusiasts to use our data to evaluate their indoor localisation models.