bTracked

Highly Accurate Field Deployable Real-Time Indoor Spatial Tracking for Human Behavior Observations

Abstract

Methods for accurate indoor spatial tracking remains a challenge. Low cost and power efficient Bluetooth Low Energy (BLE) beacon technology's ability to run maintenance-free for many years on a single coin cell battery provides an attractive methodology to realize accurate and low cost indoor spatial tracking. However an easy to deploy and accurate methodology still remains a problem of ongoing research interest.

We propose a field deployable tracking system based on BLE beacon signals together with a particle filter based approach for online and real-time tracking of persons with a body-worn Bluetooth receiver to support fine grain human behavior observations.

First, we develop the concept of generic sensor models for generalized indoor environments and build pluggable sensor models for re-use in unseen environments during deployment. Second, we exploit pose information and void constraints in our problem formulation to derive additional information about the person tracked. Third, we build the infrastructure to easily setup and operate our tracking system to support end-users to remotely track ambulating persons in real-time over a web-based interface. Fourth, we assess five different tracking methodologies together with two approaches for formulating pose information and show that our method of probabilistic multilateration including the modeling of pose leads to the best performance; a mean path estimation error of 23.5 cm in a new complex indoor environment.

Quick start

Beacon setup

Build and configure the base_station software, (see: base_station for more details).
Deploy base-stations.
Configure and deploy beacons.

Server setup

Build the btracked-server, initialize the configuration database and start the server (see: btracked-server for more details).
Open the WebApp (runs on http://localhost:8080 by default).
Create a new map using the map editor tool.
Create an appropriate filter config (an sample config is available in: tracking_manager/filter_config.json)
Start a new instance via the instance page in the WebApp.

Components

base_station -- Responsible for sniffing BLE packets sent by the transmitter back to the server. Currently only the nRF51822 SoC is supported.
btracked-server -- Responsible for hosting the web-ui, storing map data and configuration, and managing active instances.

See the respective subdirectories of each component for more details.

Auxiliary code

tracking -- Used by the btracked-server component. Implements the tracking algorithm and signal models.
web-ui -- Source code for the instance viewer and map editor web app hosted by the btracked-server.

Reference

This repository is provided as part of the following paper:

M. Chesser, L. Chea, H. V. Nguyen, and D. C. Ranasinghe. 2018. "bTracked: Highly Accurate Field Deployable Real-Time Indoor Spatial Tracking for Human Behavior Observations". In Proceedings of 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services.

Cite using:

@INPROCEEDINGS{bTracked2018,
    author={M. Chesser and L. Chea and H. V. Nguyen and D. C. Ranasinghe},
    booktitle={Proceedings of 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services},
    title={bTracked: Highly Accurate Field Deployable Real-Time Indoor Spatial Tracking for Human Behavior Observations},
    year={2018}
}

License

This project is licensed under the MIT License.

See LICENSE for details.

AdelaideAuto-IDLab/bTracked