New Technologies to the Rescue of Epileptics
Creating a device that can predict epileptic seizures to help patients regain autonomy in their everyday lives?
That's the amazing project we worked on with the association Aura.
Epilepsy is one of the biggest causes of unexpected death and remains a huge scourge because no definitive cure has yet been found. The seizures are so unpredictable they have disastrous consequences on the epileptics lives and autonomy.
We created a mobile app able to detect and warn them when a seizure is coming, using technologies such as Airflow, Docker, Grafana or Ansible.
We will cover the full data architecture of the project, and will present the tremendous work that has been done by all the people who worked on this meaningful project for how long?
This project is now in open-source, available for anyone to help and contribute.
Outline/Structure of the Case Study
1- Intro on Epilepsy & the Aura Projet
AURA is an open, collaborative, non profit project that aims to develop a connected device detecting early seizure signs in order to alert the patients
2- Complete architecture to store and monitor physiological data
What motivate our choice of technologies / tools ? What went wrong and how did we manage to adapt ?
3- Next steps (Infra on AWS architecture with Terraform & Machine Learning)
What are our next steps ? How do we need to scale ? How do we plan to iterate on the Machine Learning model training ?
DevOps tools: Docker, Ansible, Terraform
Data Engineer tools: Airflow, InfluxDB NoSQL database, Grafana
Participants will learn:
- about state of the art technologies through a use case
- DevOps good practices with a modular Infrastructure as Code
- Craftsmanship in Data Engineering
Data and DevOps engineers
Prerequisites for Attendees
Knowledge of Docker & Ansible is nice to have but every tool used will be described.