# A Testbed to Evaluate the FIWARE-Based IoT Platform in the Domain of Precision Agriculture
## 1 Introduction  
The purpose of precision agriculture (PA) is to increase farm productivity by capturing and interpreting data concerning the climate, weather, terrain, water quality and crop status. In recent years, farmers have begun using information systems to improve crop management and increase productivity. These systems include sensors for monitoring the crops and for tracing the products from crops to shelves. As a result, agriculture is becoming a data-intensive industry. In this sense, precision agriculture poses many of the same problems as the other areas where IoT is being developed (industry 4.0, logistics, smart grids, smart cities, etc. ), as well as others of its own domain, such as those described in [1; 2]: (1) organization and operation of the farm, (2) traceability of products, (3) environmental requirements, (4) decision support to increase farm performance, (5) synchronization between sensors and agricultural machinery, (6) the automation of agricultural tasks, etc. The biggest challenge for PA is capturing enough high-quality data to make the right decisions. In open spaces, most of the data comes from aerial photographs taken by satellites and aircraft and from sensors and cameras mounted on agricultural machinery and, in recent times, even drones are being used. Precision agriculture calls for a wide array of technologies to capture data, contextualise them in time and space, statistically characterise them, save and merge them and finally analyse them for decision-making purposes. In this scenario, data processing is often based on statistical techniques and artificial vision where no particular attention is paid to latency. The authors' research group has quite a lot of experience in wireless sensor networks [3], one of the essential components of the Internet of Things (IoT) [4]. In the agricultural sector we have worked on improving crop and irrigation systems owing to their importance in the semiarid region of Murcia (Spain). Reference [5] presents a novel design for a wireless sensor node designed for precision horticulture applications allowing for the use of precision agriculture instruments. This sensor was integrated into the network of experimental sensors of an ecological horticulture undertaking in the Region of Murcia [6], validated in real operating conditions [7] and compared with other studies [8]. Currently, in situ wireless sensor networks (WSN) are not widespread due to the high price of the sensors and the problem of powering them in places where there are no electrical lines. In the absence of external power sources from which sensor can harvest energy, sensor activity (capturing and transmitting data) must be kept to a minimum However, these limitations may change significantly in coming years thanks to advances in the design of power systems and batteries and price reductions resulting from the mass production of miniaturised sensors. It is therefore possible to imagine a scenario in which many sensors measure parameters related to soil (moisture and nutrient levels), water (salinity) and plants (water stress) are deployed. Capturing, transmitting, storing and processing this volume of information collected by the WSN presents a number of challenges, especially regarding integration technologies, communications, databases and computing. Fortunately there are a number of middleware platforms capable of doing most of the work although only some of these are geared for the IoT. One such middleware technology is called FIWARE [9] whose architecture is still being implemented and whose development is being closely monitored by the authors' research group [10]. FIWARE is the technology promoted by the European Commission to make possible the IoT in the context of the Future Internet [11] in collaboration with the information and communication technology industry.