Android Platform
Last updated
Last updated
Android client app: Single Kotlin app shipped to the user.
Data gathering: UI, user data collection and handling, and HTTPS client in Kotlin.
ML: Call FedML's Java API from Kotlin for local training (Kotlin has first-class Java interoperability).
Server: Single modular Python server with a single database.
Python is the language of choice to best support ML exploration.
ML module:
Call FedML's Python API from the server for aggregation.
Web module: gather and store data.
Django for HTTPS server and database interface (ORM).
PostgreSQL for the database.
HTTPS does not support broadcasting; we cannot assume the clients would always be on. So, I assume the clients will occasionally poll the server for new information. We only need to implement a REST API or something equivalent for communication.
