Goals - Fleet-Analytics-Dashboard/Application GitHub Wiki

Table of Contents

1. Project Requirements

The requirements of the project by our professor and the company adesso SE

  • develop a dashboard that helps companies to optimize their automotive fleets
  • preferably the focus should be creating business value, not just using "fancy technology"
  • therefore, the solution should be developed with the user or user-centric
  • one important aspect should be data visualizations
  • deeper insights should be given with telematic data from the automotive fleets via:
    1. batch analysis for fleet management (e.g. DM clustering algorithm, k-means)
    2. streaming analysis for monitoring fleet management and drivers (indirectly) (e.g. Dash)
  • optional: give recommendations (machine learning, ...)

2. Overall Project Goals

  • Develop a dashboard that helps companies to optimize their automotive fleets
  • Create business value
  • User-centric approach
  • Data visualizations
  • Provide deeper insights into telematic data of automotive fleets (NREL Fleet DNA Data)
    • Collected by NREL (National Renewable Energy Laboratory USA)
    • Research for the use of Truck platooning use cases

3. Group Member Goals

What each group member wants to learn during this project, starting with an MVP

3.1. Sorted by technologies

  • Reserach, Concept, Mockup Design (user needs, competitors, target groups): Johannes, Lucie, Larisa, Tim, Jakob
  • Backend (VM, database, batch data processing, server): Johannes, Tim
  • Dashboard (data visualizations, SQL requests,): Lucie, Larisa, Jakob, Johannes
  • Data analytics (data preparation, descriptive analysis, data viszualizations with Dash, machine learning): Tim, Lucie, Larisa, Jakob
  • Project management (GitHub tickets, sprints, tasks, documentation): Johannes

3.2. Sorted by members

Lucie

  • Statistical analysis
  • Data visualizations with Dash
  • User research
  • Not interested: data pipelines, databases

Tim

  • Data preparation
  • Data pipeline
  • Databases
  • Data analysis
  • Architecture
  • Google Cloud VM
  • Not interested: research (only data basis maybe), frontend

Larisa

  • Data preparation
  • Statistical analysis
  • Data visualizations with Dash
  • User research
  • Data simulation
  • Not interested: data pipelines, databases

Johannes

  • Data pipelines
  • Data visualizations
  • User research
  • Architecture (VM, server, database)
  • Project management and documentation
  • Not interested: -

Jakob

  • Decision Science
  • Data visualizations with Dash
  • User research
  • Google Cloud VM
  • Not interested: data pipelines, database