# Precision Agriculture: A Remote Sensing Monitoring System Architecture +
## 1 Introduction  
Presently, the digital transformation of the agricultural sector is considered a priority to face the numerous challenges presented in the fields. Environmental monitoring and remote controlling in agriculture is rapidly growing towards developing more productive and competitive agricultural systems and tools. Precision Agriculture and Smart Farming can lead to this direction. These two terms refer to the integration of advanced technologies into existing agricultural practices to achieve fine-grid crops management. Smart farming systems can provide to farmers meaningful environmental data from the cultivation fields aiming to boost competitiveness and profit. Almost every aspect of the agricultural field can benefit from these kinds of technological advances ranging from planting and irrigation processes to plant protection and harvesting methods. The future of precision agriculture lies upon modern technological advancements and remote sensing techniques using Unmanned Aerial Vehicles (UAV) and different kind of smart sensors. Sensors are measuring devices that convert an external stimulus or else input signal, into an appropriately measurable output signal. Sensor devices can transform a macroscopic size (light, power, pressure, etc.) to an electrically measurable size. Once the electrical signal is processed, it is converted into a standardized signal with certain characteristics. The sensor's properties can be altered in a measurable manner, either directly or indirectly by the exposure to a particular analyzer or change in environmental conditions. UAVs are flying vehicles that do not have a pilot on their spindle. Instead they fly eitherautonomously or by means of remote control. Unmanned aircraft used for remote monitoring are part of Unmanned Aerial Systems (UASs). UASs involve all necessary devices and procedures for UAV operation, while managing data collection. UAVs enable Earth Observation (EO) towards improving accuracy, executing more frequent and better monitoring of the fields and cover large (not easily accessible) areas. Sensors and UAVs are a part of the Internet of Things (IoT) paradigm. The IoT is a modern communication network involving the employment of a vast number of distributed smart devices around a unified wide area network. Its basic characteristic stands upon the ability to recognize and notify users instantly about real-time events by the use of smart objects. Smart objects-devices have basic computational skills, constrained resources and unique identifiers for communication. The adoption of smart farming though is hampered because of the lack of models providing guidance to practitioners regarding the necessary components that constitute IoT-based monitoring systems. The typically dense and heterogeneous nature of IoT deployments poses immense challenges on interoperability among the desired components. However, an efficiently designed architecture based on modern enhanced IoT technologies can pave the way into easily adopting and deploying smart systems into our everyday life activities. The latest years a significant number of efforts were presented regarding the most suitable network structure and technologies for smart farming applications [1; 2; 3; 4; 5; 6; 7; 8; 9]. However, the architectural models presented in [1; 7; 8; 9] were based only on static sensor nodes, ignoring the advantage of UAVs in monitoring and failing to provide efficient mapping of the field to the farmer. Furthermore, no prediction mechanisms were employed in [2] towards improving production. Moreover, limited contribution was provided in [3; 4; 5] regarding energy saving and link layer IoT technologies in farm management information systems, while the data-driven agricultural model proposed in [6] did not discuss data security issues. In contrast to previous studies, the contribution of this paper lies upon the presentation of a detailed architectural model for an advanced smart farming monitoring system by using UAVs and taking into consideration energy-saving and security requirements.