Streaming Heart Rate Data with IoT Core and QuestDB
An end-to-end demo of a simple IoT system to stream and visualize heart rate data.
Thanks to the growing popularity of fitness trackers and smartwatches, more people are tracking their biometrics data closely and integrating IoT into their everyday lives. In my search for a DIY heart rate tracker, I found an excellent walkthrough from Brandon Freitag and Gabe Weiss, using Google Cloud services to stream data from a Raspberry Pi with a heart rate sensor to BigQuery via IoT Core and Cloud Dataflow.
Although Cloud Dataflow supports streaming inserts to BigQuery, I wanted to take this opportunity to try out a new time-series database I came across called QuestDB. QuestDB is a fast open-source time-series database with Postgres compatibility. The live demo on the website queried the NYC taxi rides dataset with over 1.6 billion rows in milliseconds, so I was excited to give this database a try. To round out the end-to-end demo, I used Grafana to pull and visualize data from QuestDB.
Prerequisites
- NodeJS v14+
- Docker
- Google Cloud Account
- gcloud sdk
- Optional: Raspberry Pi kit
In this tutorial, we will use a Debian image to run simulated heart rate data through IoT Core. If you wish to send real sensor data from Raspberry Pi, purchase the optional kit listed above and follow the install instructions.
Google Cloud Setup
In order to use Cloud IoT Core and Cloud Pub/Sub, you need to first create a Google Cloud Platform account and a new project (mine is called questdb-iot-demo ). Then, enable IoT Core, Compute Engine, and Pub/Sub APIs under APIs & Services -> Enable APIs and Services -> Search for APIs & Services:
IoT Core Setup
IoT Core is Google’s fully-managed IoT service to help securely connect and manage IoT devices. In this demo, we will create a registry called heartrate and send MQTT data. Click on “Create Registry” and set the Registry ID…
