Looding...

Wheels

Connected Vehicle Platform

Automotive
case study

Business Impacts

50% Reduction in monthly infrastructure costs

70% Reduction in time to production using DevOps best practices

Improved scalability with single-click deployment

Customer Key Facts

  • Location : United States
  • Industry : Automotive

Problem Context

Wheels, a global leader in fleet management and mobility, managing over 3 million vehicles across 59 countries had an in-house platform that collected telematics data for each vehicle but did not support real-time tracking to prevent unauthorized/improper usage of the fleet’s assets. The telematics solution lacked reporting capabilities for analyzing trends and patterns at driver and vehicle levels. The underutilization of assets and operational inadequacies resulted in a loss of investment. Wheels needed a scalable solution using telematics as a strategic decision-making tool.

Challenges

  • Streaming data was a pull model and not a push model
  • No consistency in data capturing and data schema
  • Disparate data sources

Technologies Used

AWS Lambda

AWS Lambda

Amazon S3

Amazon S3

Amazon SQS

Amazon SQS

Amazon Athena

Amazon Athena

Amazon Glue

Amazon Glue

Amazon DynamoDB

Amazon DynamoDB

AWS CloudFormation

AWS CloudFormation

Amazon Kinesis Data Firehose

Amazon Kinesis Data Firehose

Amazon Kinesis Data Analytics

Amazon Kinesis Data Analytics

Digital Fleet Management Capability

Solution

Quantiphi developed a highly scalable, fully managed platform using AWS native services to address Wheels' existing challenges. This solution can monitor all assets 24x7 by capturing data points for both vehicle and driver and sending real-time alerts. Wheels is able to focus on metrics that are easily consumable. Additionally, data is used to make strategic purchase decisions, such as purchasing/selling new or old assets, type of asset, etc.

Result

  • Captured and monitored logs for the fleets to generate real-time alerts and insights. It helped to
    • Reduce instances of mechanical failure
  • The platform loaded daily summary data of vehicles and events which included
    • Tire pressure
    • Average miles per hour
    • Average miles per gallon
    • Total trip distance
  • Enhanced resource utilization enabled
    • Better asset utilization
    • Maintenance scheduling and planning
    • Route and path optimization
  • The platform's telematic data was used in various business units within Wheels to better plan events such as fuel savings, incident minimization, elevating the customer experience

Thank you for reaching out to us!

Our experts will be in touch with you shortly.

In the meantime, explore our insightful blogs and case studies.

Something went wrong!

Please try it again.

Share