Evaluating how the sources of uncertainty in solar modelling (e.g., input parameters, developed model chain) can influence the results’ accuracy is one of the main challenges when applied at high latitudes. In this study, a multi-stage validation workflow is implemented around five main stages: data...
In this work, industrially processed silicon kerf loss (abbreviated to silicon kerf) from the photovoltaic industry is assessed as an anode material for the lithium-ion battery (LIB). The study includes both a characterization of processed silicon kerf from different sources and a comparison with...
This article presents an industrial predictive maintenance (PdM) system used in soybean processing based on artificial intelligence (AI) and Industrial Internet of Things (IIoT) technologies. The PdM system allows for the continuous monitoring of relevant production equipment/motor parameters, such...
In this article, a soybean process optimisation solution using real-time artificial intelligence of things (RT-AIoT) technology at the edge is presented. Image classification, object detection and recognition are machine vision techniques implemented into industrial internet of things (IIoT) devices...
This article presents a novel approach to the acquisition, processing, and analytics of industrial food production by employing state-of-the-art artificial intelligence (AI) at the edge. Intelligent Industrial Internet of Things (IIoT) devices are used to gather relevant production parameters of...
This paper presents an artificial intelligence (AI) based edge processing real-time maintenance system for the purposes of industrial manufacturing control and diagnostics. The system is evaluated in a soybean processing manufacturing facility to identify abnormalities and possible breakdown...