Abstract
The rapid development of information and communication technologies and wireless sensor networks has transformed agriculture practices. New tools and methods are used to support farmers in their activities. This paper presents a context-aware system that automates irrigation decisions based on sensor measurements. Automatic irrigation overcomes the water shortage problem, and automatic sensor measurements reduce the observational work of farmers. This paper focuses on a method for developing context-aware systems using ontologies. Ontologies are used to solve heterogeneity issues in sensor measurements. Their main goal is to propose a shared data schema that precisely describes measurements to ease their interpretations. These descriptions are reusable by any machine and understandable by humans. The context-aware system also contains a decision support system based on a rules inference engine. We propose two new ontologies: The Context-Aware System Ontology addresses the development of the context-aware system in general. The Irrigation ontology automates a manual irrigation method named IRRINOV®. These ontologies reuse well-known ontologies such as the Semantic Sensor Network (SSN) and Smart Appliance REFerence (SAREF). The decision support system uses a set of rules with ontologies to infer daily irrigation decisions for farmers. This project uses real experimental data to evaluate the implementation of the decision support system.
Highlights
In the agricultural domain, farmers need to observe natural phenomena to engage in appropriate activities on their fields
The comparison relies on the fact that when both the farmer and the decision support systems (DSSs) follow the same rules of the IRRINOV® method, the watering decisions on the same conditions should be equivalent
A Context-aware systems (CASs) that contains a wireless sensor network (WSN) and a DSS can reduce the work of farmers and improve precision in farming activities
Summary
Farmers need to observe natural phenomena to engage in appropriate activities on their fields. Sci. 2020, 10, 1803 the crop development stage and measure the soil moisture provided by probes in the soil. They use practical experience or follow an irrigation method to estimate manually the water needs of their crops. Based on their estimations, the farmers decide whether to irrigate the fields. The resource shortage problem demands that farmers use water sparingly. This smart irrigation system is based on a CAS and Syntax Warning (270594): Badly formatted number the IRRINOV® method. A DSS can (1) send notifications to farmers to support them in their decision-making process and (2) automatically make decisions and control the watering system
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