Seamless Integration of AI for IoT Smart Objects
The SeamAI project develops a toolchain that brings advanced AI to resource-constrained IoT systems, enabling AI to operate directly on devices like robotic lawnmowers and smart door systems.
In the coming wave of smart, autonomous products, artificial intelligence is increasingly expected to run on devices that have minimal computing power. The RISE project SeamAI tackles this challenge head-on by developing a toolchain that brings advanced AI to resource-constrained IoT systems.
The Approach
The project, led by RISE together with industrial partners, including Husqvarna, explores how AI models can be optimized to run efficiently on embedded hardware without sacrificing performance.
By combining open-source frameworks such as TensorFlow Lite, TVM, and Kenning with hardware-aware techniques like pruning, quantization, and model compression, SeamAI enables AI to operate where it’s needed most: directly on devices like robotic lawnmowers and smart door systems.
Validation Tools
Simulation tools such as Renode allow developers to validate AI behavior before deploying to real hardware, reducing time and cost.
The Mission
The mission is clear: make embedded AI seamless, scalable, and energy-efficient, unlocking the next generation of intelligent everyday objects.
