The Client

BRL is an outdoor sporting goods company focused on the fishing industry. With existing freshwater lure manufacturing capabilities BRL is expanding its service lines to include technology enabled fishing capabilities that include data collection devices, experience, learning/logging and social integrations. BRL Outdoors envisions itself as a platform company with multiple service and product offerings that comprise the platform to service the full scope of the fishing ecosystem.

Service Offerings

Services

Product Strategy & Roadmap
Architecture Design

Tech Stack Used

Bitbucket

PostgreSQL Server

Redis Server

Python - Django

JIRA

QMetry

React

React native

AWS RDS

Elastic search

Redis

AWS Elasticache

Sendgrid

AWS SNS

Firebase

AWS S3

AWS cloudfront

Jenkins

Nginx

Stripe

Google Maps

Business Use Case

The client is looking to develop a hands free virtual assistant through smart speaker technologies and voice processing. This smart speaker / wearable device will enable a smarter fishing experience. End users should be able to use the hands-free voice user interface to record and query for data. The accompanying application is expected to function in online and offline scenarios.

Solution

We identified the following as the key building blocks:

  • Create mobile application that will interact with the IOT device
  • Use NLP to translate voice to text data within the mobile
  • Use GPS and 3rd party integration to track location and geological conditions
  • Update the cloud server with the data collected through the mobile device

Challenges

  • NLP requires training data and is also required to function offline. We identified Sensory sdk to provide NLP and voice recognition.
  • Identifying reliable 3rd party services to procure geological information such as the moon’s position , wind direction, speed, pressure.

Results

     

    • Microservices and APIs developed using Python
    • Kubernetes was used to manage docker containers
    • Distributed Cache using Redis was implemented as part of performance tuning.
    • DevOps integration was implemented using Jenkins.
    • JIRA was used for project management and Qmetry for test management
    • Elasticsearch used to set up indexed data storage for APIs
    • Push notification management through firebase and Amazon SNS

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