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The Internet of Things (IoT) is the most promising area which penetrates the advantages of Wireless Sensor and Actuator Networks and Pervasive Computing domains. Different applications of IoT have been developed and researchers of IoT well identified the opportunities, problems, challenges and the technology standards used in IoT such as Radio-Frequency Identification (RFID) tags, sensors, actuators, mobile phones, etc. (Porkodi, 2014). Internet of Things becomes a reality for many reasons: low powers processors, improvements in wireless communication technologies, electronic devices (Atzori, 2010; Vermesan, 2014; Al-Fuqaha, 2015). In the world of IoT, every object (thing) can communicate with other things or other resources in the Web, they can provide valuable information about the environment where they are installed, and provide much functionality for end-users. Due to utility and efficiency of IoT in the daily lives of human beings, they are increasingly being used in different important sectors such are healthcare, agricultural, security, transportation, performance, high assurance, financial (Porkodi, 2014).
One of the areas that can benefit from IoT solutions is the precision agriculture (smart agriculture), which can be defined as the use of information, communications technologies and electronic devices in agricultural practice, it can also include management decision support, processing collected data, and remote monitoring of agriculture machinery. It’s the term often used when we deal with IoT-based farming. There are key areas for precision agriculture: Productivity, pest control, water conservation, and continual value (see Figure 1).
Precision agriculture management practices can significantly reduce the amount of nutrient and improve crop inputs methods (seed planting, soil treatment, groundwater management) and contribute in the long term to environmental impact reduction. In the same order of idea, precision agriculture seeks to use high-tech systems in the goal of sustainable agriculture.
In one hand it seeks to assure a continued supply of food within the ecological, economic and social limits, hence this is required to sustain production in the long term. In the other hand, consumers demand for more information about their food while some smaller producers are struggling to respond to consumer demands for more information about how their food was produced because it requires detailed record-keeping and audits. All of those actors are important in the agriculture of the future; this field requires the help of Information Technologies (Big Data), communication (Networks, Wireless Networks and Cloud offerings) and software engineering theoretical supports (Agent technology and formal modelling...).
The IoT systems are used to monitor and observe factors such as humidity, temperature, and light for ensuring prevention of possible plant diseases and managing irrigation or frost risks as well as reducing labour costs.
As shown in Figure 1, processes in an IoT-based Agricultural Enterprise (A-Enterprise) will depend heavily on the interaction of heterogeneous smart devices, both among themselves and with the whole system. In current practice, interaction is defined rigidly and purely in operational terms. Consequently, the software components of the IoT-based system are tightly coupled with each other. Even small changes in one software component must be propagated to others, even when such changes are inconsequential to the business being conducted. Usually, software developers carry out the necessary changes manually, implying to a loss in time and productivity. In order to meet the requirements and challenges of different partners in such systems, A-Enterprises must be able to cooperate effectively and efficiently.