When designing, testing, and deploying real-time bio-signal processing algorithms/workflows, we usually run them on multiple data sources to check if they work as expected. StreamingHub makes this process less painful. It provides:

• APIs to access data from different devices and datasets
• Tools to convert existing datasets into open, streaminghub-compatible formats
• An extensible architecture to support new devices as needed

Main Components

• DFDS (dfds/) - JSON schemas to describe data streams, data sets, and analytics.
• pyDFDS (streaminghub_pydfds/) - A Python package providing APIs to read DFDS-annotated metadata and data.
• Curator (streaminghub_curator/) - A WebApp to annotate files with DFDS metadata and rearrange them into a standard form.
• DataMux (streaminghub_datamux/) - A Python package providing APIs to proxy/replay/simulate live data, replay recordings, and simulate real-time environments,
• Plugins (streaminghub_plugins/) - Plugins for providing new device proxies, codecs, and RPC modes to DataMux.

Extras

• Examples (examples/) - Some examples and tutorials to get you started with streaminghub.
• Repository (evaluation/) - Code and results of some performance tests, user studies, and case studies that we conducted.

When building real-time algorithms and workflows to process bio-signals, how would you feed data into them?

Case 1 - Reading Live Sensor Data: How would you connect to the device? Once connected, how would you transform the returned data into a usable format?

Case 2 - Reading Recorded Sensor Data: How would you know which columns / fields to read? If you have many data files with different column/field names, how would you read them all?

We recommend using micromamba to seamlessly install both python and non-python dependencies.

# clone the repository
git clone git@github.com:nirdslab/streaminghub.git

# cd into project directory
cd streaminghub/

# install micromamba (recommended)
"${SHELL}" <(curl -L https://micro.mamba.pm/install.sh)

# create an environment with required dependencies
micromamba env create -n streaminghub --file environment.yml

# activate environment
micromamba activate streaminghub

If using streaminghub for an existing project, you can directly install the required components via pip.

# clone the repository
git clone git@github.com:nirdslab/streaminghub.git

# install curator (from source)
pip install -e streaminghub/curator

# install datamux (from source)
pip install -e streaminghub/datamux

# install curator (from PyPI)
pip install streaminghub_curator

# install datamux (from PyPI)
pip install streaminghub_datamux

```bash
# starting streaminghub curator
python -m streaminghub_curator --host=<HOSTNAME> --port=<PORT>

# starting datamux server (for streaming live data)
python -m streaminghub_datamux

If you intend to utilize StreamingHub, kindly ensure proper attribution.

@inproceedings{jayawardana2022streaminghub,
author       = {Jayawardana, Yasith and Ashok, Vikas G. and Jayarathna, Sampath},
title        = {StreamingHub: Interactive Stream Analysis Workflows},
year         = {2022},
publisher    = {Association for Computing Machinery},
address      = {New York, NY, USA},
doi          = {10.1145/3529372.3530936},
booktitle    = {Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries},
articleno    = {15},
numpages     = {1--10},
location     = {Virtual},
series       = {JCDL '22}
}