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Next generation of embedded Information and Communication Technology (ICT)systems are collaborative systems able to perform autonomous tasks. Theremarkable expansion of the embedded ICT market, together with the rise andbreakthroughs of Artificial Intelligence (AI), have put the focus on the Edgeas it stands as one of the keys for the next technological revolution: theseamless integration of AI in our daily life. However, training and deploymentof custom AI solutions on embedded devices require a fine-grained integrationof data, algorithms, and tools to achieve high accuracy. Such integrationrequires a high level of expertise that becomes a real bottleneck for small andmedium enterprises wanting to deploy AI solutions on the Edge which,ultimately, slows down the adoption of AI on daily-life applications. In thiswork, we present a modular AI pipeline as an integrating framework to bringdata, algorithms, and deployment tools together. By removing the integrationbarriers and lowering the required expertise, we can interconnect the differentstages of tools and provide a modular end-to-end development of AI products forembedded devices. Our AI pipeline consists of four modular main steps: i) dataingestion, ii) model training, iii) deployment optimization and, iv) the IoThub integration. To show the effectiveness of our pipeline, we provide examplesof different AI applications during each of the steps. Besides, we integrateour deployment framework, LPDNN, into the AI pipeline and present itslightweight architecture and deployment capabilities for embedded devices.Finally, we demonstrate the results of the AI pipeline by showing thedeployment of several AI applications such as keyword spotting, imageclassification and object detection on a set of well-known embedded platforms,where LPDNN consistently outperforms all other popular deployment frameworks.

Bonseyes AI Pipeline -- bringing AI to you. End-to-end integration of data, algorithms and deployment tools