Scalable Real-Time Tracking for Autonomous Vehicles with AWS and Grafana
Event-driven architecture to orchestrate driverless trip data with Kinesis and Step Functions
Introduction
In the era of rapidly advancing technology, the once-unthinkable reality of autonomous vehicles has become a fascinating part of our daily lives. It’s awe-inspiring to witness how these vehicles have not only conquered the safety challenges that once loomed large over us but have also become a source of widespread fascination and discussion across social media platforms. As a seasoned data engineer deeply passionate about harnessing the power of data, I’ve been captivated by the myriad possibilities these driverless journeys present. Inspired by the transformative impact of autonomous travel, I embark on this intriguing case study to delve into the intricate data-driven intricacies that underpin this groundbreaking technological leap.
Problem
How can I help the disruptive autonomous vehicle industry orchestrate their vehicle charging intervals by monitoring miles of autonomy to keep their electric vehicle fleet running in the streets above 90% 24/7?
