(e) Cloud Computing System

This study sets up a cloud-based data platform, which is an ecosystem that incorporates data acquired in the field. The data platform supports end-to-end data needs, such as ingestion, processing, and storage, to provide the following:


These functionalities are ordered based on the strictness of real-time constraints.

The cloud-computing platform is based on the Hadoop stack and is powered by FIWARE. We adopted an open-source solution with well-known components that can be imported into different cloud service providers if no on-premises hardware is available. The core component of the platform is the (FIWARE) Orion Context Broker (OCB) from Telefonica [13], a publish/subscribe context broker that also provides an interface to query contextual information (e.g., obtain all images from the cameras in a specific farm), update context information (e.g., update the images), and be notified when the context is updated (e.g., when a new image is added into the platform). The images and raw data are stored in the HDFS (Hadoop distributed file system), while the NoSQL (not only structured query language) MongoDB database is used to collect the contextual data from FIWARE and further metadata necessary to manage the platform [14]. Additionally, we use Apache KAFKA, an open-source distributed event bus, to distribute context updates from FIWARE to all the modules/containers hosted on the cloud platform. The different cloud computing modules/containers used in this study are illustrated in Figure 5.
