Google Cloud Integration
Advanced energy analytics with BigQuery, Cloud Functions, and the full Google Cloud ecosystem.
Energy Analytics at Google Scale
Google Cloud provides world-class data analytics and machine learning infrastructure. BigQuery can analyse petabytes of energy data in seconds, Cloud Functions enable serverless event-driven processing, and Looker delivers enterprise-grade business intelligence. For organisations that need to run complex queries across large energy datasets, Google Cloud is an excellent choice.
EpiSensor integrates with Google Cloud via Pub/Sub, Google's fully managed messaging service. The gateway publishes energy data to Pub/Sub topics, which then fan out to any combination of storage, analytics, and alerting services without any single point of failure.
How It Works with EpiSensor
The ZGW-10 Gateway publishes energy data to Google Cloud Pub/Sub using MQTT with JWT-based authentication. Each gateway authenticates with a service account key, and messages are published to configurable Pub/Sub topics in structured JSON format. Pub/Sub handles message buffering and delivery guarantees, ensuring no data is lost even during downstream service maintenance.
From Pub/Sub, data flows to your chosen analytics stack. A common pattern streams data into BigQuery via a Dataflow pipeline for SQL-based analytics and long-term storage, triggers Cloud Functions for real-time alerting and data enrichment, and connects to Looker or Data Studio for dashboards. For advanced use cases, Vertex AI provides managed machine learning to build predictive models on your energy data.
Key Features
Pub/Sub Messaging
Publish energy data to Google Cloud Pub/Sub for reliable, scalable message delivery. Multiple subscribers can consume the same data stream independently.
BigQuery Analytics
Load energy data into BigQuery for fast SQL analytics over massive datasets. Analyse years of consumption data across thousands of meters in seconds.
Cloud Functions
Trigger serverless functions on every incoming energy reading. Implement real-time alerts, data validation, unit conversions, or custom business logic without managing servers.
Looker Dashboards
Build governed, interactive energy dashboards in Looker with consistent metric definitions. Embed dashboards in internal portals or customer-facing applications.
Vertex AI
Train and deploy machine learning models on your energy data with Vertex AI. Predict consumption patterns, detect anomalies, and forecast demand using managed ML pipelines.
Use Cases
Portfolio-Scale Analytics
Aggregate energy data from hundreds of sites into BigQuery. Run cross-portfolio benchmarking queries, identify outliers, and rank buildings by energy performance in seconds.
Consumption Forecasting
Use Vertex AI to build consumption forecasting models trained on historical energy data combined with weather, occupancy, and tariff data. Improve energy procurement and reduce costs.
Data-as-a-Service
Energy service providers can use BigQuery's data sharing features to provide tenants and customers with self-service access to their energy data through governed, role-based datasets.
Getting Started
In the Google Cloud Console, create a Pub/Sub topic for energy data and a service account with Pub/Sub publisher permissions. Download the service account key file. On the ZGW-10 gateway, configure the MQTT output with your Google Cloud project ID, Pub/Sub topic, and service account credentials. The gateway authenticates using JWT tokens derived from the service account key and begins publishing immediately.
To get data into BigQuery, create a BigQuery subscription on your Pub/Sub topic -- this streams messages directly into a BigQuery table with no additional code. For real-time processing, attach a Cloud Function to the Pub/Sub topic. Within an afternoon you can have a complete pipeline from sensor to dashboard.
Ready to Connect to Google Cloud?
Talk to our team about deploying EpiSensor with your Google Cloud infrastructure.