Aiden
Realtime Human-Automotive Communication through Big Data Analytics
2020 - San Ramon, CA
Embedded Software Products
11-50 employees
Overview
Folio3 partnered up with Aiden, a California based startup founded by leading innovators from Volvo Cars, to develop a Cloud-based, Big Data analytics platform that lets vehicles share real-time data securely, making driving safer and more efficient.
The Challenge
Handling large amounts of data in realtime, Folio3 recognized the customer’s need for vehicles to participate in our connected world through
Using real-time data from automotive IoT devices to address various automotive challenges.
Managing and analyzing traffic and data in large-scale volumes
Ensure transparent data collection to ensure customer consent and compliance.
The Solution - Big Data Approach for Seamless Scalability:
Folio3 critically assessed the problem and predicted significant data volume growth as product usage increases.
Based on this, Folio3 proposed an AWS based, auto-scalable solution for easier, automated scaling based on the active user volume at any time, while also minimizing the need for manual intervention.
In addition to the above, Folio3’s adoption of a cloud-first, data-driven solution successfully mitigated these wider challenges:
AWS
An Amazon Web Services (AWS) cloud based web application that collects data from the cars with the consent of the owners.
AWS Lambda
Amazon Lambda was used to execute code for real-time data sharing, bi-directional vehicle communication, and anomaly detection in the cloud-based web application.
AWS IoT
Amazon IoT Core connects IoT devices securely to the cloud, enabling bidirectional communication and data exchange with managed services.
AWS S3
Amazon S3 for large-volume data storage and archival.
AWS ElastiCache
AWS: Kinesis
Amazon Kinesis was employed for real-time data streaming and analytics, enabling timely insights from the data.
AWS RDS
Amazon RDS for reliable and scalable relational database management of structured data generated by the vehicles.
AWS DyanmoDB
Amazon DynamoDB was used for high-performance, scalable NoSQL data storage to handle vast amounts of vehicle data.
AWS SNS
Amazon SNS facilitated seamless messaging and notifications between different system components, ensuring timely updates and alerts.
AWS SQS
AWS CloudWatch
AWS SSM
Amazon SSM enabled operational data insights and analytics-driven management of infrastructure resources.
AWS CloudFront
Amazon CloudFront delivered content quickly, reducing rendering times and improving the user experience with low latency and fast transfer speeds.
AWS Cloudformation
Furthermore, Amazon Cloudformation was utilized to automate the infrastructure management and deployment processes.
AWS CloudTrail
Amazon CloudTrail ensured governance, compliance, and auditing by logging and monitoring all API activity within the AWS environment.
NAT
NAT Gateway was utilized to allow private subnets in the VPC access the internet securely for using external services.
Technologies Used
Development Stack:
Java
ReactJS
ES6 Javascript
Infrastructure Stack:
Amazon S3
AWS Lambda
AWS CodePipeline
VPC
NAT gateway
Cloudfront
Cloudformation
Amazon RDS
Elasticache
DynamoDB
Cognito
Route53
SNS
SSM
SQS
Codebuild
Cloudwatch
Kinesis
IOT Core
