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Kelvin Logo

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.

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