FridgeGuard 🛡

The idea is generally to preserve food spoilage better for industries using event-driven alerting based approach.

This is an event-based system that triggers alert and stream ingestion in Google Cloud BigQuery when a sensor (such as ESP32) detects a spoil behaviour.

The trigger happens when a document (in a collection 'data') of Firebase Firestore instance gets updated. It then checks if the value of spoiled field is either TRUE. If it is, then it exports the data into a BigQuery table 'sensor' inside 'data' dataset with the same identical schema.

The system diagram below represents the complete flow from triggering event to data stream ingestion in BigQuery:

For accessing BigQuery API and bypassing authentication, it uses a Service Based Account approach in order to authenticate into Google Cloud project and BigQuery API. For this, you need to:

• Go to your Google Cloud console and search for Service Account under IAM section.
• You need to create a new service account.
• After creating a new service account, you need to create a new Key for that service account.
• Once you created the Key then you need to download the your_project_name.json file (which will be automatically downloaded in your browser).
• Rename the credentials file with key.json
• Move key.json file under root folder of project
• BigQuery will automatically authenticate to your Google Cloud project.
• Once done, go to BigQuery and run a search query to query all the records.

Note that: For crucial security purpose, key.json file has been added to .gitignore as it contains your Google Cloud project credentials for access and authentication via client libraries.

Implenting Kafka support for Storing Alert Log for aggregation and real-time streaming

The system is also capable to publish alert logs to Kafka topic when document gets updated in Firestore instance data. In makes a POST request call to Spring Kafka Client application with payload. The Kafka Client then publishes a new alert log in the Kafka topic alerts which can then be further consumed to perform write streams to external data sources.

The diagram below represents the entire flow: