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Google Cloud IoT & AI Reference Architecture

Data-first industrial analytics with Pub/Sub and BigQuery, plus Vertex AI, Gemini and Agent Builder for multimodal and agentic workloads.

Google Cloud Platform · 5 architecture layers

End-to-end data flow

01

Sensors & Cameras

MQTT / HTTP

02

Coral Edge TPU

On-device ML

03

Cloud Pub/Sub

Global bus

04

Dataflow / BigQuery

Stream + store

05

Vertex / Gemini

ML + multimodal

06

Looker / Cloud Run

BI + APIs

Architecture layers

L1

Device & Edge Layer

Google Coral (Edge TPU)

ASIC for edge ML inference — USB, PCIe and SOM form factors at low wattage

TensorFlow Lite / LiteRT

Optimised on-device inference with hardware delegates for MCUs and edge SoCs

Anthos / GKE Enterprise

Run containerised edge and plant-floor workloads with consistent Google Cloud ops

L2

Connectivity & Ingestion Layer

Google Cloud Pub/Sub

Global durable messaging for IoT telemetry at millions of messages per second

Apigee

Enterprise API management for exposing IoT data with OAuth, quotas and analytics

Cloud Datastream

Serverless CDC replication from operational stores into BigQuery

L3

Processing & Storage Layer

Cloud Dataflow

Managed Apache Beam for unified stream and batch IoT processing

BigQuery

Serverless warehouse — analyse months of sensor history in seconds with SQL

BigQuery Omni

Analyse IoT data across AWS S3 and Azure ADLS without wholesale migration

Cloud Bigtable

Wide-column NoSQL for massive time-series ingestion and lookups

Cloud Spanner

Globally distributed relational store for device registries needing strong consistency

L4

AI / ML Layer

Vertex AI

Unified MLOps — AutoML, custom training, feature store, registry and endpoints

Gemini on Vertex AI

Multimodal Gemini models for text, image, video and audio industrial reasoning

Vertex AI Agent Builder

Build grounded agents with search, tools and orchestration for plant operations

Vertex AI Vision

Warehouse occupancy, PPE and defect inspection with prebuilt or custom models

Vertex AI Forecast

Demand and anomaly forecasting for industrial time series

Document AI

Parse invoices, quality reports and forms into structured industrial data

L5

Application & Visualization Layer

Looker / Looker Studio

BI with LookML semantic layer connected directly to BigQuery

Cloud Run

Serverless containers for IoT microservices and APIs that scale to zero

Google Maps Platform

Fleet tracking, geofencing and routing for location-aware IoT

Firebase

Low-latency sync for live dashboards and field mobile apps

Industrial AI use cases

BigQuery IoT Analytics

Pub/Sub → Dataflow → BigQuery → Looker

Visual Inspection AI

Vertex AI Vision + Coral Edge TPU

Gemini Industrial Copilot

Gemini + Vertex RAG + Agent Builder

Time-Series Forecasting

Vertex AI Forecast + Bigtable

Robotics & Manipulation

Gemini Robotics patterns + Isaac integration

Multi-Cloud Analytics

BigQuery Omni + Dataplex

Key differentiators

Analytics-native stack

Pub/Sub, Dataflow and BigQuery form a coherent path from device events to petabyte analytics.

Vertex AI + Gemini

One platform for classical ML, multimodal GenAI and agent construction with enterprise controls.

Edge TPU acceleration

Coral hardware for efficient on-device vision and classification where cloud round-trips are costly.

Multi-cloud reach

BigQuery Omni and Anthos reduce lock-in when OT data already lives across hyperscalers.