Machine-to-Machine Data Solution for Manufacturing

Maven Wave recently developed a connected machine proof of concept for a manufacturing client. The goal was to create a platform that would allow users to receive real-time positioning and machine metrics. Maven Wave leveraged the Google Cloud Platform and Android mobile technology to develop a framework that demonstrates key elements of the long-term solution. This includes:

  • Mobile device integration
  • Data integration with external data providers
  • Development speed
  • Solution scalability

Below is an overview of the custom M2M framework that we developed to achieve our client’s vision.


Connected Machine Architecture

  1. A native Android application was built to integrate with the machine’s electronic signal via a Bluetooth gateway to collect real-time data.  Select metrics were gathered every second and pushed to an API backend hosted on App Engine.
  2. The Android platform accelerated security and data integration between the device and the backend. A custom dashboard built using Google Map Engine provided both real-time and historical views of the machine’s position, as well as operating metrics.
  3. Google App Engine along with Cloud Endpoints allowed for rapid development of backend web services for data collection. The Google Cloud Endpoints framework automatically generated Android and Javascript clients and included key infrastructure functions such as authentication, authorization, and denial-of-service protection.
  4. Google Datastore is an auto-scaling NoSQL document storage solution perfect for handling the high transaction rates produced during data collection.
  5. Data collected within Datastore was loaded into Google BigQuery on a scheduled basis for performing interactive analysis across historical data collected from all machines.
  6. The Forecast IO API was leveraged to determine if there were any precipitation or severe weather alerts in the area of users. Alerts were then sent to devices using Google’s Cloud Messaging infrastructure.
  7. The Google Cloud Messaging (GCM) service handles all aspects of queueing of messages and delivery to the target Android application running on the target device.


By leveraging Google Cloud Platform, we eliminated any internal infrastructure requirements for our client. This allowed us to focus valuable R&D time and money on building the actual framework. The full solution was delivered in less than 10 weeks.

Given the solution is intended for a large consumer audience, scale was an important factor.  All of the Google Cloud Platform components leveraged for this solution are inherently built for scale at their core. After all, the same platform and technologies leveraged in this solution power the world’s largest consumer services.

This innovative use of the Google Cloud Platform and machine-to-machine data is just the tip of the iceberg. As companies build their big data strategy for the future, they must consider M2M data as an important piece of the equation. The possibilities for taking advantage of M2M data are significant for virtually every industry.

For more information on our M2M data solution, please contact us