Blog Post

Internet of Things Blog
2 MIN READ

Introducing KAN: An OSS project for Creation and Management of Computer Vision Edge Al Applications

penorouzi's avatar
penorouzi
Icon for Microsoft rankMicrosoft
Feb 02, 2023

To address challenges of building scalable computer vision AI solutions, we are releasing KubeAI Application Nucleus for edge (KAN - in Mandarin means “to watch”, “to see”) - a Kubernetes-native solution accelerator that enables you to easily develop, orchestrate, and operate computer vision Al applications for the edge with full control and flexibility.

 

Edge AI applications allow organizations to easily extract actionable insights from unstructured data streams right where the data is generated, enabling the creation of environmentally aware business solutions. Parking operators can improve parking lot utilization by analyzing vehicle patterns. Retailers can improve store operations, and customer satisfaction by continuously analyzing customer behavior in-store. However, as organizations increasingly rely on edge AI to process data closer to the source, developers and solution operators face the challenge of developing and operating scalable, distributed Al applications across heterogeneous and hybrid edge environments.

 

KAN-Portal.gif

 

End-to-End Development and Operation Environment

 

KAN reduces the complexity and radically simplifies the process of building AI solutions at scale. It does so by providing a single self-hosted place for both developing AI Applications (what we call AI Skills) and then deploying and operating such applications across all your edge environments.

 

KAN-Arch.png

 

With KAN, you have your own no- to low-code portal experience as well as APIs that you can use to develop custom AI applications in a matter of minutes. Your custom-developed application can ingest camera and sensor data, use AI models and various other processing techniques to analyze unstructured data and then export your structured output to your desired location locally, to other environments, or the cloud, all this happening close to your data source. When building your applications with KAN, you can leverage pre-built models from our partner’s Model Zoo or create your custom ML models with Azure Custom Vision or bring your existing ML Models developed externally. Your custom-created AI application can run accelerated on x64 CPU, Nvidia dGPU, Nvidia Jetson, and Intel iGPU out of the box.

 

KAN-Portal-AI-Skill.gif

 

KAN is designed with machine learning operations (MLOps) in mind, providing support for active learning, continuous training, and data gathering using your ML models running at the edge. It seamlessly integrates with standard technologies such as DaprMQTTONNXAkri, etc. As a self-managed solution, you can host it on your Kubernetes clusters anywhere across on-prem, cloud, and multi-cloud environments. It natively supports Azure Edge and Al Services like Azure loT HubAzure IoT EdgeAzure Cognitive ServicesAzure StorageAzure Arc, etc.

 

Get Started Even with no Azure Subscription or IoT Devices

 

Don't wait, try KAN today and experience the ease of developing and operating edge Al applications. You don’t need any edge hardware, you can get started with a few commands even without an Azure Subscription.

Updated Feb 02, 2023
Version 1.0
  • Thank you for trying our solution and sharing your feedback, Laziz. Currently, we don't have plans to add support for RTMP, HLS, and WebRTC, but we highly value contributions from our community. Your suggestion is a great enhancement, and we would be happy to see it added by someone from the community. If you'd like to contribute, we welcome you to add the issue in our repository with the "enhancement" label. Thank you for supporting our project and we look forward to your future contributions.

  • Great job! I've created pull requests to suggest some minor typo corrections and got now a fully functional Edge AI deployment on my AKS cluster :-).

     

    Quick question: current Camera setup supports RTSP only. Any plans to extend this in the future to enable support for some other popular protocols like RTMP, HLS and WebRTC ? Thanks.

     

     

  • Really interesting solution, thank you for sharing. Added one Patch to the Git repo with the actual symbol for Mandarin Chinese 看 character 🙂