Machine learning algorithms implementation into embedded systems with web application user interface
Kamil Židek, Ján Piteľ, Alexander Hošovský · 2017
The paper presents research in usability of web technologies for implementation of machine learning and clustering algorithms into embedded systems. The research work is divided into two main parts. The first part is devoted to designing backend system with fast C++ application for learning execution model. The second part of application is frontend based web application with PHP and AJAX to provide interface for virtual laboratory access via internet. This solution is implemented and tested on selected embedded systems (Orange PI Lite, Raspberry PI3).