A cloud-based and flexible architecture for beans images processing

Abstract

Food quality is a paramount feature in agriculture technology, analyzing and classifying properly grains requires specialized work (Gomes and Leta, 2012). Nowadays, advanced computer vision technologies are available in vast life environments, however they require a software intensive approach to acquire and process a large amount of data at an acceptable level. In parallel, cloud-based services became full featured and highly available through different types of data networks. These advances together empower the Industry 4.0 solutions to accomplish flexible needs in modern factories. In this work we present an extensible architecture that allows decentralization of the digital image processing suitable in food quality context. We integrate modern computer technologies to decrease the latency between the Edge of image acquisition and Data Centers, leveraging IIoT technologies into the food quality control systems. This approach lets the end user capture images using low or high technology cameras and process them using cloud based technologies. The proposed approach, also, describes architectural components that allow an easy way of adding and combining new components for automatic image processing.

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Keywords

image processing, architecture, corn beans classification

Citation

WCCE11 — 11th World Congress of Chemical Engineering.

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Except where otherwised noted, this item's license is described as openAccess