City Scooter Fleet Management

We designed an end-to-end customer experience platform for robust data collection and fleet management that tracks millions of vehicles across hundreds of fleets.

  • 122Tons
    of CO2 prevented from being emitted by vehicles
  • 1KScooters
    included in data simulation analyzing behaviors
  • 300KMi
    replaced by scooter mileage during the testing period

The Challenge

Cities are changing at a rapid pace and quickly adopting smart eco-friendly spaces and transportation. Our client wanted develop a new city scooter that greatly improved ride quality and safety as well as a management platform that would support consumer features alongside robust fleet management and the capability for 3rd parties to white-label the scooters and the platform.

Controlling Vehicles

Core API’s that allowed 3rd parties to communicate and
control vehicles in their owned or leased fleets.

Reliability

A platform that remained secure and reliable at scale in
order to support mobility partners.

Data

Detailed vehicle system and vehicle data critical for usage
and performance analytics.

Industry

  • Transportaion



Data Strategy

  • In-depth Discovery Engagements

Systems Implementation

  • Data Preperation
  • Data Warehousing
  • Custom Dashboards

Operationalize

  • Operationalizing Data
  • Using Data to Experiment
  • Predictive Analytics
The Garage at productOps

The Solution

Our client and their Mobility partners know the state of their vehicles at all times. We turned to AWS to provide the backbone of our platform and used AWS services such as API Gateway to securely manage requests, ECS to process messages, and a Parquet database on S3 to store all message transactions in a large data lake. Using AWS, our certified engineers we able to quickly develop, test, and deploy our platform ahead of schedule.

Big Data

Core API’s that allowed 3rd parties to communicate and
control vehicles in their owned or leased fleets.

Scalability & Testing

In order to ensure that the platform could handle vehicle
messaging at scale, we created a virtual city where thousands
of vehicles would move around the city and simulate
the full range of scooter behaviors including errors. We
ran tests using the virtual city and found several vulnerabilities
in the architecture. By discovering these early on
we were able to modify the platform and created a system
that was more reliable, scalable, and ultimately a lot less
expensive to run.

Outcomes

  • Increased Access
  • Increased Transparency
  • Performant Data Lakes
  • Accurate Testing
  • Scaleable, Reliable Platform Development
The result was improved ride quality and safety as well as a management platform that supports more consumer features.

Technology

This project was powered by the following partners:

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