In global manufacturing and commerce, raw materials, components, and final goods can travel long distances through warehouses and logistic hubs before arriving at their final destination. More often than not, the direct or indirect value of any particular item warrants certain costs associated with monitoring its condition and position. In the past years Artificial Intelligence has become a key factor to empower the transformation of asset-management. In fact, augmented assettracking represents a good solution to keep trace of physical assets, providing the location, the status and other important information. The main goal of this thesis is to implement an asset-tracking system augmented by Artificial Intelligence, based on STMicroelectronics hardware platforms and software already available.