The use of Machine Learning in IoT devices has become the only viable path in today's landscape, where millions of connected devices surround us and increasingly affect our lives. These resource-limited devices interact with the surrounding world via actuators and sensors. Many of these devices use Machine Learning techniques to be able to interpret the world and choose the appropriate action to take. Therefore the purpose of this work is to create a system that allows the application of Machine Learning algorithms directly to the ends of the network, where sensors and actuators reside. The system is designed to rely on the SENSIPLUS smart-sensor as a data acquisition device, and consists of an automatic code generation and compilation system, which through the use of a Toolchain, allows to run artificial intelligence algorithms directly on microcontroller devices.
An Open Source C Code Generator and a Tiny Machine Learning Toolchain for the SENSIPLUS Platform
Ria A.;Cicalini M.;Manfredini G.;Bruschi P.
2022-01-01
Abstract
The use of Machine Learning in IoT devices has become the only viable path in today's landscape, where millions of connected devices surround us and increasingly affect our lives. These resource-limited devices interact with the surrounding world via actuators and sensors. Many of these devices use Machine Learning techniques to be able to interpret the world and choose the appropriate action to take. Therefore the purpose of this work is to create a system that allows the application of Machine Learning algorithms directly to the ends of the network, where sensors and actuators reside. The system is designed to rely on the SENSIPLUS smart-sensor as a data acquisition device, and consists of an automatic code generation and compilation system, which through the use of a Toolchain, allows to run artificial intelligence algorithms directly on microcontroller devices.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.