Today we’re announcing that balena and Coral are partnering to simplify how developers deploy and manage AI applications at the edge.
is a platform of hardware
tools, and example models
for building devices with local AI. Coral's on-device ML acceleration technology helps developers build fast, efficient, and affordable solutions for the edge.
helps developers build, deploy, and manage IoT applications at scale. We simplify IoT fleet management with our edge-optimized OS, container-based delta updates, remote device management APIs, and more.
Together, Coral + balena simplify how edge developers provision, deploy, and manage their AI projects. We’re ready for any project, whether it’s working with early prototypes, or in production environments with many thousands of devices.
Deploy, manage, and scale an intelligent AI fleet
Combine the power and performance of Coral’s edge products with the flexibility and scalability of the balena platform to add fleet intelligence to your edge projects.
What is fleet intelligence at the edge?
Fleet intelligence gives IoT devices the capability to gather data, process and learn from it, and share information back to the entire fleet. The more models adapt and learn locally, the more beneficial the results -- and all without needing to send data back to the cloud. It’s like the AI or machine learning projects you’d see in huge data centers, but purpose-built for edge deployments, utilizing the distributed sensing, learning, and processing made possible by IoT.
To make the most of fleet intelligence, edge developers need the right software, hardware, and management platform to ensure maximum uptime, device health, and efficient maintenance. This is especially important in environments where data connectivity might be limited.
We’re excited to work with Coral to enable fleet intelligence for a number of TensorFlow and AutoML Vision Edge use cases
- Computer vision and imaging at the edge: detect or classify objects in real time in remote locations
- Machine learning-powered voice recognition
- Safety monitoring for human interaction within industrial and manufacturing settings
- Soil health and plant monitoring projects to use AI to improve agriculture
- ...and whatever else edge developers might come up with!
How to get started
Build a streaming object detector using local AI
Try this sample project
to set up your first device using local AI in a real-world setting. This project deploys a streaming camera feed with real-time people detection using a Coral product
Read the documentation or try a project today and let us know what you think on Twitter
, and our Forums
. For more information about Coral and to see more examples of their platform in action, visit coral.ai/examples