Hobbyists, developers and Raspberry Pi enthusiasts would like to learn more about the Internet of Things and machine learning, may be interested in a new article published to the official Raspberry Pi Blog this week by Ashley Whittaker. During which van Rust, Technology Ambassador for Edge Impulse explains more about how easy it is to run Edge Impulse machine learning on any operating system such as the Raspberry Pi OS. The reference project has been written to provide you with a guide for quickly getting started with Edge Impulse on Raspberry Pi 4 and Azure IoT, to train a model that is capable of reading real world indicators.
“Edge machine learning devices fall into two categories: some are able to run very simple models locally, and others have more advanced capabilities that allow them to be more powerful and have cloud connectivity. The second group is often expensive to develop and maintain, as training and deploying models can be an arduous process. That’s where Edge Impulse comes in to help to simplify the pipeline, as data can be gathered remotely, used effortlessly to train models, downloaded to the devices directly from the Azure IoT Hub, and then run – fast.”
“Building enterprise-grade IoT solutions takes a lot of practical effort and a healthy dose of imagination. As a foundation, you start with a highly secure and reliable communication between your IoT application and the devices it manages. We picked our favorite integration, the Microsoft Azure IoT Hub, which provides us with a cloud-hosted solution backend to connect virtually any device. For our hardware, we selected the ubiquitous Raspberry Pi 4, and of course Edge Impulse, which will connect to both platforms and extend our showcased solution from cloud to edge, including device authentication, out-of-box device management, and model provisioning.”
For more information and to learn about machine learning and the Internet of Things jump over to the official Raspberry Pi blog by following the link below.
Source : RPiBlog
Latest Geeky Gadgets Deals
Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.