Welcome to Kelvin SDK - App Samples

This repository contains sample applications that demonstrate how to use the Kelvin SDK.

We recommend that you start first by reading the official Kelvin Documentation on https://docs.kelvin.ai.

Sample Applications

🚀 SmartApps

Application	Domain	Level	Description
Casting Defect Detection	Computer Vision	Advanced	Uses a TensorFlow-based model to identify and analyze manufacturing defects in casting processes.
Event Detection	Event Detection	Beginner	Monitors streaming data for threshold-crossing events and emits Control Changes or Recommendations.
Multi-Objective Optimization ML	Machine Learning	Advanced	Solves multi-objective optimization problems using ML techniques.

📥 Importers

Application	Level	Description
Camera Connector	Intermediate	Publishes camera-feed images to the Kelvin Platform.
MQTT Connector	Intermediate	Publishes MQTT messages to the Kelvin Platform.

📤 Exporters

Application	Level	Description
AWS S3 Uploader	Intermediate	Uploads time-series data to an AWS S3 Bucket.
Azure Data Lake Gen2 Uploader	Intermediate	Uploads streaming data to Azure Data Lake Storage Gen2.
Databricks Delta Table Uploader	Intermediate	Uploads streaming data to Databricks Delta Table.
Databricks Volume Uploader	Intermediate	Uploads streaming data to a Databricks Volume.
Databricks Volume Uploader	Intermediate	Uploads streaming data to a Databricks Volume.
Resnet Custom Actions	Intermediate	Creates issues in the Resnet system.
Slack Custom Actions	Intermediate	Sends slack messages to a given channel.

🤖 Docker

Application	Level	Description
Mosquitto MQTT	Intermediate	Mosquitto MQTT Broker that supports SSL/TLS encryption

Contributing

1. Fork the project.
2. Create your feature branch (git checkout -b feature/YourFeature).
3. Commit your changes (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature/YourFeature).
5. Open a pull request.