Dynamic Data Analysis System Design for OMRON using AWS Managed Services

Client Overview

Omron Electronic Components LLC  

For over 80 years, OMRON has been a leading manufacturer and provider of advanced electronic components. Extensive product groups include relays, switches, connectors and sensors (e.g., MEMS, human image sensing, optical). Omron Electronic Components LLC is an American subsidiary of Omron Corporation, a $7 billion global leading supplier of electronics and control system components and services. OMRON’s broad product offering can be found in applications for the communications, transportation, medical, HVAC, appliance, industrial automation, consumer electronics, test and measurement, and gaming markets around the world.

Technology & Business Requirements

OMRON wanted a solution to collect and store their environment sensors’ data (Acceleration, Barometric pressure, Humidity, Light, Sound Noise, Temperature, UV, smell) in real time and they wanted to analyze correlation between other data which are separately collected (ex. weather, comfortable index). The purpose of use is for validation of data correlation internally in OMRON, not for commercial use.

This would require:

  • Collecting real-time sensor data over BLE with continuous display on dashboard. Sensor data should be stored and pre-processed on the cloud.
  • As post process, correlation analytics to operate with other data source (ex. weather, comfortable index) by which operator can pick up environment index which most correlate with added index. This post process to be enabled with a Machine Learning model.
  • The Machine Learning model to be utilized by operator to input the model in dashboard enabling the Operator to validate the function of model with real-time dashboard.

(OMRON environment sensor series)

VOLANSYS Contribution

VOLANSYS architected a cloud-based Machine Learning solution, including web application, for OMRON, using AWS Managed Services as it has all the required infrastructure available that accelerates solution design time. Volansys utilized Amazon Machine Learning to train and deploy Machine Learning model to accurately detect an event.

  • Designed secure, cost-effective and scalable cloud architecture using AWS managed services
    • Stored and retrieved sensor data for dashboard using Amazon Simple Storage Service. Hosted cloud to cloud application using Amazon EC2 instance to connect with router and process the data. Used Amazon Cognito, AWS Lambda and Amazon API gateway to serve secured restful API content. AWS SDK helped to make the application user friendly for developers.
  • Developed web application to customize settings and dashboard for collected environment data
    • Designed dynamic dashboard to customize Machine Learning endpoints for different graphs
  • Processed environment sensors’ data using Amazon EC2 for:
    • Pre-process data
    • Updating offsets
  • Developed script to calculate AWS pricing based on file size, processing time and storage
  • Cloud implementation and auto deployment using AWS Managed Services

AWS Technologies & Services used

Technologies | Engineering Expertise

Embedded Firmware Development | Quality Engineering | Wireless Connectivity

Solution Architecture
Benefits Delivered
  • Helped up-sell cloud connected environment sensor solution with weather detection and prediction applications using AWS Managed Services for data processing
  • Setup and running long Machine Learning training jobs with just few clicks in AWS SageMaker, saving execution time