Big Data Processing and Trip Driver Score Analytics for Connected Cars

Project Overview

IoT and big data are two sides of a coin. Indium Software was entrusted with building the big data infrastructure for the client’s connected-car IoT devices. This infrastructure was designed to support real-time events such as impact alerts, tow alerts, and driving violation alerts. Additionally, Indium Software developed advanced analytics and machine learning models to assist car owners in optimizing their trips based on various factors, monitoring the driving behavior of their child or driver, and checking their vehicle’s health.

About Client

The client is a group company of a Tier-1 automotive parts supplier operating in three continents. It was incorporated to deliver enhanced value through connected car and telematics solutions. With manufacturing facilities in Asia and Europe, the client has international offices in North America, Europe, China, and Japan.

Business Requirements

The requirement was two-fold as stated below:

  • Set up a Big Data infrastructure that supports real-time events such as impact alerts, tow alerts, driving violation alerts, etc.
  • Develop advanced analytics and machine learning algorithms to help car owners optimize their trips based on previous trips across multiple drivers, monitor the driving behavior of their kid/driver, and check their vehicle’s health.