Abstract
Modelling WSN data behaviour is relevant since it would allow to evaluate the capacity of an application for supplying the user needs, moreover, it could enable a transparent integration with different data-centric information systems. Therefore, this article proposes a data-centric UML profile for the design of wireless sensor nodes from the user point-of-view capable of representing the gathered and delivered data of the node. This profile considers different characteristics and configurations of frequency, aggregation, persistence and quality at the level of the wireless sensor nodes. Furthermore, this article validates the UML profile through a computer-aided software engineering (CASE) tool implementation and one case study, centred on the data collected by a real WSN implementation for precision agriculture and smart farming.
Highlights
The Agri-food sector plays a key role in the economy of almost every country in the world, for generating wealth and creating employment and for the nutrition of the population in developed and developing countries (Lehmann, Reiche, & Schiefer, 2012; Ramirez-Villegas, Salazar, Jarvis, & Navarro-Racines, 2012)
This article validates the Unified Modelling Language (UML) profile through a computer-aided software engineering (CASE) tool implementation and one case study, centred on the data collected by a real Wireless Sensor Networks (WSN) implementation for precision agriculture and smart farming
We propose a Data-centric Wireless-Sensor UML profile based on the features described in Section 2, which will act as a framework for modelling the data behaviour in Wireless Sensor node (WS) implemented on Agri-food-oriented Information and Communication Technologies (ICT) applications or even in different domains
Summary
The Agri-food sector plays a key role in the economy of almost every country in the world, for generating wealth and creating employment and for the nutrition of the population in developed and developing countries (Lehmann, Reiche, & Schiefer, 2012; Ramirez-Villegas, Salazar, Jarvis, & Navarro-Racines, 2012). Handling agricultural collected data is challenging since the monitoring sensors can collect and stream large amounts of raw data (e.g. embedded in tractors) and must deal with limited and depletable resources (e.g. deployed on the crop fields) (Anisi, Abdul-Salaam, & Abdullah, 2015; Jabeen & Nawaz, 2015) These big data heterogeneous streams must be correctly and timely processed in order to serve for the different applications aiming to improve the decision-making, control and definition of strategies in the Agri-food sector or any other domain, considering the end-user needs. They are not restricted to agriculture-oriented and smartfarming applications; thereby, these WS data features could be used to model WSN applications for various domains outside the Agri-food context
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