# OODIDA: On-board/Off-board Distributed Real-Time Data Analytics for Connected Vehicles

## TL;DR

OODIDA is a scalable platform enabling real-time distributed data analytics for connected vehicles, efficiently managing task distribution and execution across on-board and off-board systems using message-passing in Erlang/OTP.

## Contribution

It introduces a novel platform that handles task distribution and concurrent execution in connected vehicle networks with a scalable message-passing infrastructure.

## Key findings

- Supports large numbers of concurrent tasks
- Flexible programming language support for computations
- Efficient task distribution in vehicle networks

## Abstract

A fleet of connected vehicles easily produces many gigabytes of data per hour, making centralized (off-board) data processing impractical. In addition, there is the issue of distributing tasks to on-board units in vehicles and processing them efficiently. Our solution to this problem is OODIDA (On-board/Off-board Distributed Data Analytics), which is a platform that tackles both task distribution to connected vehicles as well as concurrent execution of tasks on arbitrary subsets of edge clients. Its message-passing infrastructure has been implemented in Erlang/OTP, while the end points use a language-independent JSON interface. Computations can be carried out in arbitrary programming languages. The message-passing infrastructure of OODIDA is highly scalable, facilitating the execution of large numbers of concurrent tasks.